feat: compression eval harness for agent/context_compressor.py

Ships a complete offline eval harness at scripts/compression_eval/. Runs
a real conversation fixture through ContextCompressor.compress(), asks
the compressor model to answer probe questions from the compressed
state, then has a judge model score each answer 0-5 on six dimensions
(accuracy, context_awareness, artifact_trail, completeness, continuity,
instruction_following). Methodology adapted from Factory's Dec 2025
write-up (https://factory.ai/news/evaluating-compression); the
scoreboard framing is not adopted.

Motivation: we edit context_compressor.py prompts and _template_sections
by hand and ship with no automated check that compression still
preserves file paths, error codes, or the active task. Until now there
has been no signal between 'test suite green' and 'a user hits a bad
summary in production.'

What's shipped
- DESIGN.md — full architecture, fixture/probe format, scrubber
  pipeline, grading rubric, open follow-ups
- README.md — usage, cost expectations, when to run it
- scrub_fixtures.py — reproducible pipeline that converts real sessions
  from ~/.hermes/sessions/*.jsonl into public-safe JSON fixtures. Applies
  agent.redact.redact_sensitive_text + username path normalisation +
  personal handle scrubbing + email/git-author normalisation + reasoning
  scratchpad stripping + platform-mention scrubbing + first-user
  paraphrase + system-prompt placeholder + orphan-message pruning + 2KB
  tool-output truncation
- fixtures/ — three scrubbed session snapshots covering three session
  shapes:
    feature-impl-context-priority  (75 msgs / ~17k tokens)
    debug-session-feishu-id-model  (59 msgs / ~13k tokens)
    config-build-competitive-scouts (61 msgs / ~23k tokens)
- probes/ — three probe banks (10-11 probes each) covering all four
  types (recall/artifact/continuation/decision) with expected_facts
  anchors (PR numbers, file paths, error codes, commands)
- rubric.py — six-dimension grading rubric, judge-prompt builder,
  JSON-with-fallback response parser
- compressor_driver.py — thin wrapper around ContextCompressor for
  forced single-shot compression (fixtures are below the default
  100k threshold so we force compress() to attribute score deltas
  to prompt changes, not threshold-fire variance)
- grader.py — two-phase continuation + grading calls via the OpenAI
  SDK directly against the resolved provider endpoint
- report.py — markdown report renderer (paste-ready for PR bodies),
  --compare-to delta mode, per-run JSON dumper
- run_eval.py — fire-style CLI (--fixtures, --runs, --judge-model,
  --compressor-model, --label, --focus-topic, --compare-to, --verbose)
- tests/scripts/test_compression_eval.py — 33 hermetic unit tests
  covering rubric parsing edge cases, judge-prompt building, report
  rendering, summariser medians, per-run JSON roundtrip, fixture and
  probe loading, and a PII smoke check on the checked-in fixtures

Non-LLM paths are covered by the 33-test suite that runs in CI. The
LLM paths (continuation + grading) require credentials and real API
calls, so they're exercised by running the eval itself — not by CI.

Validation
- 33/33 unit tests pass in 0.33s via scripts/run_tests.sh
- 50/50 adjacent tests (tests/agent/test_context_compressor.py) still
  pass — no regression introduced
- End-to-end dry run against debug-session-feishu-id-model with
  openai/gpt-5.4-mini via Nous Portal:
    Compression: 13081 -> 3055 tokens (76.6% ratio), 59 -> 10 messages
    Overall score: 3.25 (artifact_trail 1.50 is the weak spot,
    matching Factory's published observation)
    Specific probe misses surfaced with concrete judge notes

Noise floor (one empirical data point)
Same inputs re-run: overall 3.25 -> 3.17 (delta -0.08). Individual
dimensions varied up to ±0.5 between two single-run medians. Confirms
the DESIGN.md < 0.3 noise guidance is the right order of magnitude
for single-run comparisons. Tighter noise measurement (N=10) is
tracked as an open follow-up in DESIGN.md.

Why scripts/ and not tests/
Requires API credentials, costs ~$0.50-1.50 per run, minutes to
execute, LLM-graded (non-deterministic). Incompatible with
scripts/run_tests.sh which is hermetic, parallel, credential-free.
scripts/sample_and_compress.py is the existing precedent for offline
credentialed tooling.

Open follow-ups (tracked in DESIGN.md, not blocking this PR)
1. Iterative-merge fixture (two chained compressions on one session)
2. Precise noise-floor measurement at N=10
3. Scripted scrubber helpers to lower the cost of fixture #4+
4. Judge model selection policy (pin vs. per-user)

.gitignore

@@ -52,6 +52,10 @@ ignored/
 .worktrees/
 environments/benchmarks/evals/
 
+# Compression eval run outputs (harness lives in scripts/compression_eval/)
+scripts/compression_eval/results/*
+!scripts/compression_eval/results/.gitkeep
+
 # Web UI build output
 hermes_cli/web_dist/
 

AGENTS.md

@@ -240,19 +240,6 @@ npm run fmt       # prettier
 npm test          # vitest
 ```
 
-### TUI in the Dashboard (`hermes dashboard` → `/chat`)
-
-The dashboard embeds the real `hermes --tui` — **not** a rewrite.  See `hermes_cli/pty_bridge.py` + the `@app.websocket("/api/pty")` endpoint in `hermes_cli/web_server.py`.
-
-- Browser loads `web/src/pages/ChatPage.tsx`, which mounts xterm.js's `Terminal` with the WebGL renderer, `@xterm/addon-fit` for container-driven resize, and `@xterm/addon-unicode11` for modern wide-character widths.
-- `/api/pty?token=…` upgrades to a WebSocket; auth uses the same ephemeral `_SESSION_TOKEN` as REST, via query param (browsers can't set `Authorization` on WS upgrade).
-- The server spawns whatever `hermes --tui` would spawn, through `ptyprocess` (POSIX PTY — WSL works, native Windows does not).
-- Frames: raw PTY bytes each direction; resize via `\x1b[RESIZE:<cols>;<rows>]` intercepted on the server and applied with `TIOCSWINSZ`.
-
-**Do not re-implement the primary chat experience in React.** The main transcript, composer/input flow (including slash-command behavior), and PTY-backed terminal belong to the embedded `hermes --tui` — anything new you add to Ink shows up in the dashboard automatically. If you find yourself rebuilding the transcript or composer for the dashboard, stop and extend Ink instead.
-
-**Structured React UI around the TUI is allowed when it is not a second chat surface.** Sidebar widgets, inspectors, summaries, status panels, and similar supporting views (e.g. `ChatSidebar`, `ModelPickerDialog`, `ToolCall`) are fine when they complement the embedded TUI rather than replacing the transcript / composer / terminal. Keep their state independent of the PTY child's session and surface their failures non-destructively so the terminal pane keeps working unimpaired.
-
 ---
 
 ## Adding New Tools

agent/anthropic_adapter.py

@@ -390,16 +390,7 @@ def build_anthropic_client(api_key: str, base_url: str = None, timeout: float =
         "timeout": Timeout(timeout=float(_read_timeout), connect=10.0),
     }
     if normalized_base_url:
-        # Azure Anthropic endpoints require an ``api-version`` query parameter.
-        # Pass it via default_query so the SDK appends it to every request URL
-        # without corrupting the base_url (appending it directly produces
-        # malformed paths like /anthropic?api-version=.../v1/messages).
-        _is_azure_endpoint = "azure.com" in normalized_base_url.lower()
-        if _is_azure_endpoint and "api-version" not in normalized_base_url:
-            kwargs["base_url"] = normalized_base_url.rstrip("/")
-            kwargs["default_query"] = {"api-version": "2025-04-15"}
-        else:
-            kwargs["base_url"] = normalized_base_url
+        kwargs["base_url"] = normalized_base_url
     common_betas = _common_betas_for_base_url(normalized_base_url)
 
     if _is_kimi_coding_endpoint(base_url):
@@ -995,26 +986,6 @@ def read_hermes_oauth_credentials() -> Optional[Dict[str, Any]]:
 # ---------------------------------------------------------------------------
 
 
-def _is_bedrock_model_id(model: str) -> bool:
-    """Detect AWS Bedrock model IDs that use dots as namespace separators.
-
-    Bedrock model IDs come in two forms:
-    - Bare:    ``anthropic.claude-opus-4-7``
-    - Regional (inference profiles): ``us.anthropic.claude-sonnet-4-5-v1:0``
-
-    In both cases the dots separate namespace components, not version
-    numbers, and must be preserved verbatim for the Bedrock API.
-    """
-    lower = model.lower()
-    # Regional inference-profile prefixes
-    if any(lower.startswith(p) for p in ("global.", "us.", "eu.", "ap.", "jp.")):
-        return True
-    # Bare Bedrock model IDs: provider.model-family
-    if lower.startswith("anthropic."):
-        return True
-    return False
-
-
 def normalize_model_name(model: str, preserve_dots: bool = False) -> str:
     """Normalize a model name for the Anthropic API.
 
@@ -1022,19 +993,11 @@ def normalize_model_name(model: str, preserve_dots: bool = False) -> str:
     - Converts dots to hyphens in version numbers (OpenRouter uses dots,
       Anthropic uses hyphens: claude-opus-4.6 → claude-opus-4-6), unless
       preserve_dots is True (e.g. for Alibaba/DashScope: qwen3.5-plus).
-    - Preserves Bedrock model IDs (``anthropic.claude-opus-4-7``) and
-      regional inference profiles (``us.anthropic.claude-*``) whose dots
-      are namespace separators, not version separators.
     """
     lower = model.lower()
     if lower.startswith("anthropic/"):
         model = model[len("anthropic/"):]
     if not preserve_dots:
-        # Bedrock model IDs use dots as namespace separators
-        # (e.g. "anthropic.claude-opus-4-7", "us.anthropic.claude-*").
-        # These must not be converted to hyphens.  See issue #12295.
-        if _is_bedrock_model_id(model):
-            return model
         # OpenRouter uses dots for version separators (claude-opus-4.6),
         # Anthropic uses hyphens (claude-opus-4-6). Convert dots to hyphens.
         model = model.replace(".", "-")
@@ -1689,9 +1652,9 @@ def build_anthropic_kwargs(
 
     # ── Strip sampling params on 4.7+ ─────────────────────────────────
     # Opus 4.7 rejects any non-default temperature/top_p/top_k with a 400.
-    # Callers (auxiliary_client, etc.) may set these for older models;
-    # drop them here as a safety net so upstream 4.6 → 4.7 migrations
-    # don't require coordinated edits everywhere.
+    # Callers (auxiliary_client, flush_memories, etc.) may set these for
+    # older models; drop them here as a safety net so upstream 4.6 → 4.7
+    # migrations don't require coordinated edits everywhere.
     if _forbids_sampling_params(model):
         for _sampling_key in ("temperature", "top_p", "top_k"):
             kwargs.pop(_sampling_key, None)

agent/auxiliary_client.py

@@ -42,7 +42,6 @@ import time
 from pathlib import Path  # noqa: F401 — used by test mocks
 from types import SimpleNamespace
 from typing import Any, Dict, List, Optional, Tuple
-from urllib.parse import urlparse, parse_qs, urlunparse
 
 from openai import OpenAI
 
@@ -53,17 +52,6 @@ from utils import base_url_host_matches, base_url_hostname, normalize_proxy_env_
 
 logger = logging.getLogger(__name__)
 
-
-def _extract_url_query_params(url: str):
-    """Extract query params from URL, return (clean_url, default_query dict or None)."""
-    parsed = urlparse(url)
-    if parsed.query:
-        clean = urlunparse(parsed._replace(query=""))
-        params = {k: v[0] for k, v in parse_qs(parsed.query).items()}
-        return clean, params
-    return url, None
-
-
 # Module-level flag: only warn once per process about stale OPENAI_BASE_URL.
 _stale_base_url_warned = False
 
@@ -402,7 +390,7 @@ class _CodexCompletionsAdapter:
         # Note: the Codex endpoint (chatgpt.com/backend-api/codex) does NOT
         # support max_output_tokens or temperature — omit to avoid 400 errors.
 
-        # Tools support for auxiliary callers (e.g. skills_hub) that pass function schemas
+        # Tools support for flush_memories and similar callers
         tools = kwargs.get("tools")
         if tools:
             converted = []
@@ -1169,10 +1157,8 @@ def _try_custom_endpoint() -> Tuple[Optional[Any], Optional[str]]:
         return None, None
     model = _read_main_model() or "gpt-4o-mini"
     logger.debug("Auxiliary client: custom endpoint (%s, api_mode=%s)", model, custom_mode or "chat_completions")
-    _clean_base, _dq = _extract_url_query_params(custom_base)
-    _extra = {"default_query": _dq} if _dq else {}
     if custom_mode == "codex_responses":
-        real_client = OpenAI(api_key=custom_key, base_url=_clean_base, **_extra)
+        real_client = OpenAI(api_key=custom_key, base_url=custom_base)
         return CodexAuxiliaryClient(real_client, model), model
     if custom_mode == "anthropic_messages":
         # Third-party Anthropic-compatible gateway (MiniMax, Zhipu GLM,
@@ -1186,12 +1172,12 @@ def _try_custom_endpoint() -> Tuple[Optional[Any], Optional[str]]:
                 "Custom endpoint declares api_mode=anthropic_messages but the "
                 "anthropic SDK is not installed — falling back to OpenAI-wire."
             )
-            return OpenAI(api_key=custom_key, base_url=_clean_base, **_extra), model
+            return OpenAI(api_key=custom_key, base_url=custom_base), model
         return (
             AnthropicAuxiliaryClient(real_client, model, custom_key, custom_base, is_oauth=False),
             model,
         )
-    return OpenAI(api_key=custom_key, base_url=_clean_base, **_extra), model
+    return OpenAI(api_key=custom_key, base_url=custom_base), model
 
 
 def _try_codex() -> Tuple[Optional[Any], Optional[str]]:
@@ -1363,49 +1349,6 @@ def _is_auth_error(exc: Exception) -> bool:
     return "error code: 401" in err_lower or "authenticationerror" in type(exc).__name__.lower()
 
 
-def _is_unsupported_parameter_error(exc: Exception, param: str) -> bool:
-    """Detect provider 400s for an unsupported request parameter.
-
-    Different OpenAI-compatible endpoints phrase the same class of error a few
-    ways: ``Unsupported parameter: X``, ``unsupported_parameter`` with a
-    ``param`` field, ``X is not supported``, ``unknown parameter: X``,
-    ``unrecognized request argument: X``.  We match on both the parameter
-    name and a generic "unsupported/unknown/unrecognized parameter" marker so
-    call sites can reactively retry without the offending key instead of
-    surfacing a noisy auxiliary failure.
-
-    Generalizes the temperature-specific detector that originally shipped
-    with PR #15621 so the same retry strategy can cover ``max_tokens``,
-    ``seed``, ``top_p``, and any future quirk. Credit @nicholasrae (PR #15416)
-    for the generalization pattern.
-    """
-    param_lower = (param or "").lower()
-    if not param_lower:
-        return False
-    err_lower = str(exc).lower()
-    if param_lower not in err_lower:
-        return False
-    return any(marker in err_lower for marker in (
-        "unsupported parameter",
-        "unsupported_parameter",
-        "not supported",
-        "does not support",
-        "unknown parameter",
-        "unrecognized request argument",
-        "unrecognized parameter",
-        "invalid parameter",
-    ))
-
-
-def _is_unsupported_temperature_error(exc: Exception) -> bool:
-    """Back-compat wrapper: detect API errors where the model rejects ``temperature``.
-
-    Delegates to :func:`_is_unsupported_parameter_error`; kept as a separate
-    public symbol because existing tests and call sites import it by name.
-    """
-    return _is_unsupported_parameter_error(exc, "temperature")
-
-
 def _evict_cached_clients(provider: str) -> None:
     """Drop cached auxiliary clients for a provider so fresh creds are used."""
     normalized = _normalize_aux_provider(provider)
@@ -1839,15 +1782,12 @@ def resolve_provider_client(
                 provider,
             )
             extra = {}
-            _clean_base, _dq = _extract_url_query_params(custom_base)
-            if _dq:
-                extra["default_query"] = _dq
             if base_url_host_matches(custom_base, "api.kimi.com"):
                 extra["default_headers"] = {"User-Agent": "claude-code/0.1.0"}
             elif base_url_host_matches(custom_base, "api.githubcopilot.com"):
                 from hermes_cli.models import copilot_default_headers
                 extra["default_headers"] = copilot_default_headers()
-            client = OpenAI(api_key=custom_key, base_url=_clean_base, **extra)
+            client = OpenAI(api_key=custom_key, base_url=custom_base, **extra)
             client = _wrap_if_needed(client, final_model, custom_base)
             return (_to_async_client(client, final_model) if async_mode
                     else (client, final_model))
@@ -1884,8 +1824,6 @@ def resolve_provider_client(
                     model or custom_entry.get("model") or _read_main_model() or "gpt-4o-mini",
                     provider,
                 )
-                _clean_base2, _dq2 = _extract_url_query_params(custom_base)
-                _extra2 = {"default_query": _dq2} if _dq2 else {}
                 logger.debug(
                     "resolve_provider_client: named custom provider %r (%s, api_mode=%s)",
                     provider, final_model, entry_api_mode or "chat_completions")
@@ -1903,7 +1841,7 @@ def resolve_provider_client(
                             "installed — falling back to OpenAI-wire.",
                             provider,
                         )
-                        client = OpenAI(api_key=custom_key, base_url=_clean_base2, **_extra2)
+                        client = OpenAI(api_key=custom_key, base_url=custom_base)
                         return (_to_async_client(client, final_model) if async_mode
                                 else (client, final_model))
                     sync_anthropic = AnthropicAuxiliaryClient(
@@ -1912,7 +1850,7 @@ def resolve_provider_client(
                     if async_mode:
                         return AsyncAnthropicAuxiliaryClient(sync_anthropic), final_model
                     return sync_anthropic, final_model
-                client = OpenAI(api_key=custom_key, base_url=_clean_base2, **_extra2)
+                client = OpenAI(api_key=custom_key, base_url=custom_base)
                 # codex_responses or inherited auto-detect (via _wrap_if_needed).
                 # _wrap_if_needed reads the closed-over `api_mode` (the task-level
                 # override). Named-provider entry api_mode=codex_responses also
@@ -2055,39 +1993,6 @@ def resolve_provider_client(
                        "directly supported", provider)
         return None, None
 
-    elif pconfig.auth_type == "aws_sdk":
-        # AWS SDK providers (Bedrock) — use the Anthropic Bedrock client via
-        # boto3's credential chain (IAM roles, SSO, env vars, instance metadata).
-        try:
-            from agent.bedrock_adapter import has_aws_credentials, resolve_bedrock_region
-            from agent.anthropic_adapter import build_anthropic_bedrock_client
-        except ImportError:
-            logger.warning("resolve_provider_client: bedrock requested but "
-                           "boto3 or anthropic SDK not installed")
-            return None, None
-
-        if not has_aws_credentials():
-            logger.debug("resolve_provider_client: bedrock requested but "
-                         "no AWS credentials found")
-            return None, None
-
-        region = resolve_bedrock_region()
-        default_model = "anthropic.claude-haiku-4-5-20251001-v1:0"
-        final_model = _normalize_resolved_model(model or default_model, provider)
-        try:
-            real_client = build_anthropic_bedrock_client(region)
-        except ImportError as exc:
-            logger.warning("resolve_provider_client: cannot create Bedrock "
-                           "client: %s", exc)
-            return None, None
-        client = AnthropicAuxiliaryClient(
-            real_client, final_model, api_key="aws-sdk",
-            base_url=f"https://bedrock-runtime.{region}.amazonaws.com",
-        )
-        logger.debug("resolve_provider_client: bedrock (%s, %s)", final_model, region)
-        return (_to_async_client(client, final_model) if async_mode
-                else (client, final_model))
-
     elif pconfig.auth_type in ("oauth_device_code", "oauth_external"):
         # OAuth providers — route through their specific try functions
         if provider == "nous":
@@ -2822,8 +2727,8 @@ def _build_call_kwargs(
         temperature = fixed_temperature
 
     # Opus 4.7+ rejects any non-default temperature/top_p/top_k — silently
-    # drop here so auxiliary callers that hardcode temperature (e.g. 0 on
-    # structured-JSON extraction) don't 400 the moment
+    # drop here so auxiliary callers that hardcode temperature (e.g. 0.3 on
+    # flush_memories, 0 on structured-JSON extraction) don't 400 the moment
     # the aux model is flipped to 4.7.
     if temperature is not None:
         from agent.anthropic_adapter import _forbids_sampling_params
@@ -2911,7 +2816,7 @@ def call_llm(
 
     Args:
         task: Auxiliary task name ("compression", "vision", "web_extract",
-              "session_search", "skills_hub", "mcp", "title_generation").
+              "session_search", "skills_hub", "mcp", "flush_memories").
               Reads provider:model from config/env. Ignored if provider is set.
         provider: Explicit provider override.
         model: Explicit model override.
@@ -3014,45 +2919,13 @@ def call_llm(
     if _is_anthropic_compat_endpoint(resolved_provider, _client_base):
         kwargs["messages"] = _convert_openai_images_to_anthropic(kwargs["messages"])
 
-    # Handle unsupported temperature, max_tokens vs max_completion_tokens retry,
-    # then payment fallback.
+    # Handle max_tokens vs max_completion_tokens retry, then payment fallback.
     try:
         return _validate_llm_response(
             client.chat.completions.create(**kwargs), task)
     except Exception as first_err:
-        if "temperature" in kwargs and _is_unsupported_temperature_error(first_err):
-            retry_kwargs = dict(kwargs)
-            retry_kwargs.pop("temperature", None)
-            logger.info(
-                "Auxiliary %s: provider rejected temperature; retrying once without it",
-                task or "call",
-            )
-            try:
-                return _validate_llm_response(
-                    client.chat.completions.create(**retry_kwargs), task)
-            except Exception as retry_err:
-                retry_err_str = str(retry_err)
-                # If retry still fails, fall through to the max_tokens /
-                # payment / auth chains below using the temperature-stripped
-                # kwargs.  Re-raise only if the retry hit something those
-                # chains won't handle.
-                if not (
-                    _is_payment_error(retry_err)
-                    or _is_connection_error(retry_err)
-                    or _is_auth_error(retry_err)
-                    or "max_tokens" in retry_err_str
-                    or "unsupported_parameter" in retry_err_str
-                ):
-                    raise
-                first_err = retry_err
-                kwargs = retry_kwargs
-
         err_str = str(first_err)
-        if max_tokens is not None and (
-            "max_tokens" in err_str
-            or "unsupported_parameter" in err_str
-            or _is_unsupported_parameter_error(first_err, "max_tokens")
-        ):
+        if "max_tokens" in err_str or "unsupported_parameter" in err_str:
             kwargs.pop("max_tokens", None)
             kwargs["max_completion_tokens"] = max_tokens
             try:
@@ -3315,35 +3188,8 @@ async def async_call_llm(
         return _validate_llm_response(
             await client.chat.completions.create(**kwargs), task)
     except Exception as first_err:
-        if "temperature" in kwargs and _is_unsupported_temperature_error(first_err):
-            retry_kwargs = dict(kwargs)
-            retry_kwargs.pop("temperature", None)
-            logger.info(
-                "Auxiliary %s (async): provider rejected temperature; retrying once without it",
-                task or "call",
-            )
-            try:
-                return _validate_llm_response(
-                    await client.chat.completions.create(**retry_kwargs), task)
-            except Exception as retry_err:
-                retry_err_str = str(retry_err)
-                if not (
-                    _is_payment_error(retry_err)
-                    or _is_connection_error(retry_err)
-                    or _is_auth_error(retry_err)
-                    or "max_tokens" in retry_err_str
-                    or "unsupported_parameter" in retry_err_str
-                ):
-                    raise
-                first_err = retry_err
-                kwargs = retry_kwargs
-
         err_str = str(first_err)
-        if max_tokens is not None and (
-            "max_tokens" in err_str
-            or "unsupported_parameter" in err_str
-            or _is_unsupported_parameter_error(first_err, "max_tokens")
-        ):
+        if "max_tokens" in err_str or "unsupported_parameter" in err_str:
             kwargs.pop("max_tokens", None)
             kwargs["max_completion_tokens"] = max_tokens
             try:

agent/bedrock_adapter.py

@@ -87,114 +87,6 @@ def reset_client_cache():
     _bedrock_control_client_cache.clear()
 
 
-def invalidate_runtime_client(region: str) -> bool:
-    """Evict the cached ``bedrock-runtime`` client for a single region.
-
-    Per-region counterpart to :func:`reset_client_cache`. Used by the converse
-    call wrappers to discard clients whose underlying HTTP connection has
-    gone stale, so the next call allocates a fresh client (with a fresh
-    connection pool) instead of reusing a dead socket.
-
-    Returns True if a cached entry was evicted, False if the region was not
-    cached.
-    """
-    existed = region in _bedrock_runtime_client_cache
-    _bedrock_runtime_client_cache.pop(region, None)
-    return existed
-
-
-# ---------------------------------------------------------------------------
-# Stale-connection detection
-# ---------------------------------------------------------------------------
-#
-# boto3 caches its HTTPS connection pool inside the client object. When a
-# pooled connection is killed out from under us (NAT timeout, VPN flap,
-# server-side TCP RST, proxy idle cull, etc.), the next use surfaces as
-# one of a handful of low-level exceptions — most commonly
-# ``botocore.exceptions.ConnectionClosedError`` or
-# ``urllib3.exceptions.ProtocolError``. urllib3 also trips an internal
-# ``assert`` in a couple of paths (connection pool state checks, chunked
-# response readers) which bubbles up as a bare ``AssertionError`` with an
-# empty ``str(exc)``.
-#
-# In all of these cases the client is the problem, not the request: retrying
-# with the same cached client reproduces the failure until the process
-# restarts. The fix is to evict the region's cached client so the next
-# attempt builds a new one.
-
-_STALE_LIB_MODULE_PREFIXES = (
-    "urllib3.",
-    "botocore.",
-    "boto3.",
-)
-
-
-def _traceback_frames_modules(exc: BaseException):
-    """Yield ``__name__``-style module strings for each frame in exc's traceback."""
-    tb = getattr(exc, "__traceback__", None)
-    while tb is not None:
-        frame = tb.tb_frame
-        module = frame.f_globals.get("__name__", "")
-        yield module or ""
-        tb = tb.tb_next
-
-
-def is_stale_connection_error(exc: BaseException) -> bool:
-    """Return True if ``exc`` indicates a dead/stale Bedrock HTTP connection.
-
-    Matches:
-      * ``botocore.exceptions.ConnectionError`` and subclasses
-        (``ConnectionClosedError``, ``EndpointConnectionError``,
-        ``ReadTimeoutError``, ``ConnectTimeoutError``).
-      * ``urllib3.exceptions.ProtocolError`` / ``NewConnectionError`` /
-        ``ConnectionError`` (best-effort import — urllib3 is a transitive
-        dependency of botocore so it is always available in practice).
-      * Bare ``AssertionError`` raised from a frame inside urllib3, botocore,
-        or boto3. These are internal-invariant failures (typically triggered
-        by corrupted connection-pool state after a dropped socket) and are
-        recoverable by swapping the client.
-
-    Non-library ``AssertionError``s (from application code or tests) are
-    intentionally not matched — only library-internal asserts signal stale
-    connection state.
-    """
-    # botocore: the canonical signal — HTTPClientError is the umbrella for
-    # ConnectionClosedError, ReadTimeoutError, EndpointConnectionError,
-    # ConnectTimeoutError, and ProxyConnectionError. ConnectionError covers
-    # the same family via a different branch of the hierarchy.
-    try:
-        from botocore.exceptions import (
-            ConnectionError as BotoConnectionError,
-            HTTPClientError,
-        )
-        botocore_errors: tuple = (BotoConnectionError, HTTPClientError)
-    except ImportError:  # pragma: no cover — botocore always present with boto3
-        botocore_errors = ()
-    if botocore_errors and isinstance(exc, botocore_errors):
-        return True
-
-    # urllib3: low-level transport failures
-    try:
-        from urllib3.exceptions import (
-            ProtocolError,
-            NewConnectionError,
-            ConnectionError as Urllib3ConnectionError,
-        )
-        urllib3_errors = (ProtocolError, NewConnectionError, Urllib3ConnectionError)
-    except ImportError:  # pragma: no cover
-        urllib3_errors = ()
-    if urllib3_errors and isinstance(exc, urllib3_errors):
-        return True
-
-    # Library-internal AssertionError (urllib3 / botocore / boto3)
-    if isinstance(exc, AssertionError):
-        for module in _traceback_frames_modules(exc):
-            if any(module.startswith(prefix) for prefix in _STALE_LIB_MODULE_PREFIXES):
-                return True
-
-    return False
-
-
 # ---------------------------------------------------------------------------
 # AWS credential detection
 # ---------------------------------------------------------------------------
@@ -895,17 +787,7 @@ def call_converse(
         guardrail_config=guardrail_config,
     )
 
-    try:
-        response = client.converse(**kwargs)
-    except Exception as exc:
-        if is_stale_connection_error(exc):
-            logger.warning(
-                "bedrock: stale-connection error on converse(region=%s, model=%s): "
-                "%s — evicting cached client so the next call reconnects.",
-                region, model, type(exc).__name__,
-            )
-            invalidate_runtime_client(region)
-        raise
+    response = client.converse(**kwargs)
     return normalize_converse_response(response)
 
 
@@ -937,17 +819,7 @@ def call_converse_stream(
         guardrail_config=guardrail_config,
     )
 
-    try:
-        response = client.converse_stream(**kwargs)
-    except Exception as exc:
-        if is_stale_connection_error(exc):
-            logger.warning(
-                "bedrock: stale-connection error on converse_stream(region=%s, "
-                "model=%s): %s — evicting cached client so the next call reconnects.",
-                region, model, type(exc).__name__,
-            )
-            invalidate_runtime_client(region)
-        raise
+    response = client.converse_stream(**kwargs)
     return normalize_converse_stream_events(response)
 
 

agent/codex_responses_adapter.py

@@ -23,52 +23,26 @@ from agent.prompt_builder import DEFAULT_AGENT_IDENTITY
 logger = logging.getLogger(__name__)
 
 
-# Matches Codex/Harmony tool-call serialization that occasionally leaks into
-# assistant-message content when the model fails to emit a structured
-# ``function_call`` item.  Accepts the common forms:
-#
-#   to=functions.exec_command
-#   assistant to=functions.exec_command
-#   <|channel|>commentary to=functions.exec_command
-#
-# ``to=functions.<name>`` is the stable marker — the optional ``assistant`` or
-# Harmony channel prefix varies by degeneration mode.  Case-insensitive to
-# cover lowercase/uppercase ``assistant`` variants.
-_TOOL_CALL_LEAK_PATTERN = re.compile(
-    r"(?:^|[\s>|])to=functions\.[A-Za-z_][\w.]*",
-    re.IGNORECASE,
-)
-
-
 # ---------------------------------------------------------------------------
 # Multimodal content helpers
 # ---------------------------------------------------------------------------
 
-def _chat_content_to_responses_parts(content: Any, *, role: str = "user") -> List[Dict[str, Any]]:
+def _chat_content_to_responses_parts(content: Any) -> List[Dict[str, Any]]:
     """Convert chat-style multimodal content to Responses API input parts.
 
     Input:  ``[{"type":"text"|"image_url", ...}]`` (native OpenAI Chat format)
-    Output: ``[{"type":"input_text"|"output_text"|"input_image", ...}]`` (Responses format)
-
-    The ``role`` parameter controls the text content type:
-    - ``"user"`` (default) → ``"input_text"``
-    - ``"assistant"`` → ``"output_text"``
-
-    The Responses API rejects ``input_text`` inside assistant messages and
-    ``output_text`` inside user messages, so callers MUST pass the correct
-    role for the message being converted.
+    Output: ``[{"type":"input_text"|"input_image", ...}]`` (Responses format)
 
     Returns an empty list when ``content`` is not a list or contains no
     recognized parts — callers fall back to the string path.
     """
-    text_type = "output_text" if role == "assistant" else "input_text"
     if not isinstance(content, list):
         return []
     converted: List[Dict[str, Any]] = []
     for part in content:
         if isinstance(part, str):
             if part:
-                converted.append({"type": text_type, "text": part})
+                converted.append({"type": "input_text", "text": part})
             continue
         if not isinstance(part, dict):
             continue
@@ -76,7 +50,7 @@ def _chat_content_to_responses_parts(content: Any, *, role: str = "user") -> Lis
         if ptype in {"text", "input_text", "output_text"}:
             text = part.get("text")
             if isinstance(text, str) and text:
-                converted.append({"type": text_type, "text": text})
+                converted.append({"type": "input_text", "text": text})
             continue
         if ptype in {"image_url", "input_image"}:
             image_ref = part.get("image_url")
@@ -227,23 +201,6 @@ def _responses_tools(tools: Optional[List[Dict[str, Any]]] = None) -> Optional[L
 # Message format conversion
 # ---------------------------------------------------------------------------
 
-_RESPONSE_MESSAGE_STATUSES = {"completed", "incomplete", "in_progress"}
-
-
-def _normalize_responses_message_status(value: Any, *, default: str = "completed") -> str:
-    """Normalize a Responses assistant message status for replay.
-
-    The API accepts completed/incomplete/in_progress on replayed assistant
-    output messages.  Preserve those exactly (modulo case/hyphen spelling) so
-    incomplete Codex continuation turns don't get falsely marked completed.
-    """
-    if isinstance(value, str):
-        status = value.strip().lower().replace("-", "_").replace(" ", "_")
-        if status in _RESPONSE_MESSAGE_STATUSES:
-            return status
-    return default
-
-
 def _chat_messages_to_responses_input(messages: List[Dict[str, Any]]) -> List[Dict[str, Any]]:
     """Convert internal chat-style messages to Responses input items."""
     items: List[Dict[str, Any]] = []
@@ -259,10 +216,9 @@ def _chat_messages_to_responses_input(messages: List[Dict[str, Any]]) -> List[Di
         if role in {"user", "assistant"}:
             content = msg.get("content", "")
             if isinstance(content, list):
-                content_parts = _chat_content_to_responses_parts(content, role=role)
-                text_type = "output_text" if role == "assistant" else "input_text"
+                content_parts = _chat_content_to_responses_parts(content)
                 content_text = "".join(
-                    p.get("text", "") for p in content_parts if p.get("type") == text_type
+                    p.get("text", "") for p in content_parts if p.get("type") == "input_text"
                 )
             else:
                 content_parts = []
@@ -289,57 +245,7 @@ def _chat_messages_to_responses_input(messages: List[Dict[str, Any]]) -> List[Di
                                 seen_item_ids.add(item_id)
                             has_codex_reasoning = True
 
-                # Replay exact assistant message items (with id/phase) from
-                # previous turns so the API can maintain prefix-cache hits.
-                # OpenAI docs: "preserve and resend phase on all assistant
-                # messages — dropping it can degrade performance."
-                codex_message_items = msg.get("codex_message_items")
-                replayed_message_items = 0
-                if isinstance(codex_message_items, list):
-                    for raw_item in codex_message_items:
-                        if not isinstance(raw_item, dict):
-                            continue
-                        if raw_item.get("type") != "message" or raw_item.get("role") != "assistant":
-                            continue
-                        raw_content_parts = raw_item.get("content")
-                        if not isinstance(raw_content_parts, list):
-                            continue
-
-                        normalized_content_parts = []
-                        for part in raw_content_parts:
-                            if not isinstance(part, dict):
-                                continue
-                            part_type = str(part.get("type") or "").strip()
-                            if part_type not in {"output_text", "text"}:
-                                continue
-                            text = part.get("text", "")
-                            if text is None:
-                                text = ""
-                            if not isinstance(text, str):
-                                text = str(text)
-                            normalized_content_parts.append({"type": "output_text", "text": text})
-
-                        if not normalized_content_parts:
-                            continue
-
-                        replay_item = {
-                            "type": "message",
-                            "role": "assistant",
-                            "status": _normalize_responses_message_status(raw_item.get("status")),
-                            "content": normalized_content_parts,
-                        }
-                        item_id = raw_item.get("id")
-                        if isinstance(item_id, str) and item_id.strip():
-                            replay_item["id"] = item_id.strip()
-                        phase = raw_item.get("phase")
-                        if isinstance(phase, str) and phase.strip():
-                            replay_item["phase"] = phase.strip()
-                        items.append(replay_item)
-                        replayed_message_items += 1
-
-                if replayed_message_items > 0:
-                    pass
-                elif content_parts:
+                if content_parts:
                     items.append({"role": "assistant", "content": content_parts})
                 elif content_text.strip():
                     items.append({"role": "assistant", "content": content_text})
@@ -499,47 +405,6 @@ def _preflight_codex_input_items(raw_items: Any) -> List[Dict[str, Any]]:
                 normalized.append(reasoning_item)
             continue
 
-        if item_type == "message":
-            role = item.get("role")
-            if role != "assistant":
-                raise ValueError(f"Codex Responses input[{idx}] message items must have role='assistant'.")
-            content = item.get("content")
-            if not isinstance(content, list):
-                raise ValueError(f"Codex Responses input[{idx}] message item must have content list.")
-            normalized_content = []
-            for part_idx, part in enumerate(content):
-                if not isinstance(part, dict):
-                    raise ValueError(
-                        f"Codex Responses input[{idx}] message content[{part_idx}] must be an object."
-                    )
-                part_type = part.get("type")
-                if part_type not in {"output_text", "text"}:
-                    raise ValueError(
-                        f"Codex Responses input[{idx}] message content[{part_idx}] has unsupported type {part_type!r}."
-                    )
-                text = part.get("text", "")
-                if text is None:
-                    text = ""
-                if not isinstance(text, str):
-                    text = str(text)
-                normalized_content.append({"type": "output_text", "text": text})
-            if not normalized_content:
-                raise ValueError(f"Codex Responses input[{idx}] message item must contain at least one text part.")
-            normalized_item: Dict[str, Any] = {
-                "type": "message",
-                "role": "assistant",
-                "status": _normalize_responses_message_status(item.get("status")),
-                "content": normalized_content,
-            }
-            item_id = item.get("id")
-            if isinstance(item_id, str) and item_id.strip():
-                normalized_item["id"] = item_id.strip()
-            phase = item.get("phase")
-            if isinstance(phase, str) and phase.strip():
-                normalized_item["phase"] = phase.strip()
-            normalized.append(normalized_item)
-            continue
-
         role = item.get("role")
         if role in {"user", "assistant"}:
             content = item.get("content", "")
@@ -547,16 +412,13 @@ def _preflight_codex_input_items(raw_items: Any) -> List[Dict[str, Any]]:
                 content = ""
             if isinstance(content, list):
                 # Multimodal content from ``_chat_messages_to_responses_input``
-                # is already in Responses format (``input_text`` / ``output_text``
-                # / ``input_image``).  Validate each part and pass through.
-                # Use the correct text type for the role — ``output_text`` for
-                # assistant messages, ``input_text`` for user messages.
-                text_type = "output_text" if role == "assistant" else "input_text"
+                # is already in Responses format (``input_text`` / ``input_image``).
+                # Validate each part and pass through.
                 validated: List[Dict[str, Any]] = []
                 for part_idx, part in enumerate(content):
                     if isinstance(part, str):
                         if part:
-                            validated.append({"type": text_type, "text": part})
+                            validated.append({"type": "input_text", "text": part})
                         continue
                     if not isinstance(part, dict):
                         raise ValueError(
@@ -567,7 +429,7 @@ def _preflight_codex_input_items(raw_items: Any) -> List[Dict[str, Any]]:
                         text = part.get("text", "")
                         if not isinstance(text, str):
                             text = str(text or "")
-                        validated.append({"type": text_type, "text": text})
+                        validated.append({"type": "input_text", "text": text})
                     elif ptype in {"input_image", "image_url"}:
                         image_ref = part.get("image_url", "")
                         detail = part.get("detail")
@@ -824,7 +686,6 @@ def _normalize_codex_response(response: Any) -> tuple[Any, str]:
     content_parts: List[str] = []
     reasoning_parts: List[str] = []
     reasoning_items_raw: List[Dict[str, Any]] = []
-    message_items_raw: List[Dict[str, Any]] = []
     tool_calls: List[Any] = []
     has_incomplete_items = response_status in {"queued", "in_progress", "incomplete"}
     saw_commentary_phase = False
@@ -843,7 +704,6 @@ def _normalize_codex_response(response: Any) -> tuple[Any, str]:
 
         if item_type == "message":
             item_phase = getattr(item, "phase", None)
-            normalized_phase = None
             if isinstance(item_phase, str):
                 normalized_phase = item_phase.strip().lower()
                 if normalized_phase in {"commentary", "analysis"}:
@@ -853,18 +713,6 @@ def _normalize_codex_response(response: Any) -> tuple[Any, str]:
             message_text = _extract_responses_message_text(item)
             if message_text:
                 content_parts.append(message_text)
-                raw_message_item: Dict[str, Any] = {
-                    "type": "message",
-                    "role": "assistant",
-                    "status": _normalize_responses_message_status(item_status),
-                    "content": [{"type": "output_text", "text": message_text}],
-                }
-                item_id = getattr(item, "id", None)
-                if isinstance(item_id, str) and item_id:
-                    raw_message_item["id"] = item_id
-                if normalized_phase:
-                    raw_message_item["phase"] = normalized_phase
-                message_items_raw.append(raw_message_item)
         elif item_type == "reasoning":
             reasoning_text = _extract_responses_reasoning_text(item)
             if reasoning_text:
@@ -939,37 +787,6 @@ def _normalize_codex_response(response: Any) -> tuple[Any, str]:
         if isinstance(out_text, str):
             final_text = out_text.strip()
 
-    # ── Tool-call leak recovery ──────────────────────────────────
-    # gpt-5.x on the Codex Responses API sometimes degenerates and emits
-    # what should be a structured `function_call` item as plain assistant
-    # text using the Harmony/Codex serialization (``to=functions.foo
-    # {json}`` or ``assistant to=functions.foo {json}``). The model
-    # intended to call a tool, but the intent never made it into
-    # ``response.output`` as a ``function_call`` item, so ``tool_calls``
-    # is empty here. If we pass this through, the parent sees a
-    # confident-looking summary with no audit trail (empty ``tool_trace``)
-    # and no tools actually ran — the Taiwan-embassy-email incident.
-    #
-    # Detection: leaked tokens always contain ``to=functions.<name>`` and
-    # the assistant message has no real tool calls. Treat it as incomplete
-    # so the existing Codex-incomplete continuation path (3 retries,
-    # handled in run_agent.py) gets a chance to re-elicit a proper
-    # ``function_call`` item. The existing loop already handles message
-    # append, dedup, and retry budget.
-    leaked_tool_call_text = False
-    if final_text and not tool_calls and _TOOL_CALL_LEAK_PATTERN.search(final_text):
-        leaked_tool_call_text = True
-        logger.warning(
-            "Codex response contains leaked tool-call text in assistant content "
-            "(no structured function_call items). Treating as incomplete so the "
-            "continuation path can re-elicit a proper tool call. Leaked snippet: %r",
-            final_text[:300],
-        )
-        # Clear the text so downstream code doesn't surface the garbage as
-        # a summary. The encrypted reasoning items (if any) are preserved
-        # so the model keeps its chain-of-thought on the retry.
-        final_text = ""
-
     assistant_message = SimpleNamespace(
         content=final_text,
         tool_calls=tool_calls,
@@ -977,13 +794,10 @@ def _normalize_codex_response(response: Any) -> tuple[Any, str]:
         reasoning_content=None,
         reasoning_details=None,
         codex_reasoning_items=reasoning_items_raw or None,
-        codex_message_items=message_items_raw or None,
     )
 
     if tool_calls:
         finish_reason = "tool_calls"
-    elif leaked_tool_call_text:
-        finish_reason = "incomplete"
     elif has_incomplete_items or (saw_commentary_phase and not saw_final_answer_phase):
         finish_reason = "incomplete"
     elif reasoning_items_raw and not final_text:

agent/context_compressor.py

@@ -294,7 +294,6 @@ class ContextCompressor(ContextEngine):
         self._context_probed = False
         self._context_probe_persistable = False
         self._previous_summary = None
-        self._last_summary_error = None
         self._last_compression_savings_pct = 100.0
         self._ineffective_compression_count = 0
 
@@ -318,13 +317,6 @@ class ContextCompressor(ContextEngine):
             int(context_length * self.threshold_percent),
             MINIMUM_CONTEXT_LENGTH,
         )
-        # Recalculate token budgets for the new context length so the
-        # compressor stays calibrated after a model switch (e.g. 200K → 32K).
-        target_tokens = int(self.threshold_tokens * self.summary_target_ratio)
-        self.tail_token_budget = target_tokens
-        self.max_summary_tokens = min(
-            int(context_length * 0.05), _SUMMARY_TOKENS_CEILING,
-        )
 
     def __init__(
         self,
@@ -397,7 +389,6 @@ class ContextCompressor(ContextEngine):
         self._last_compression_savings_pct: float = 100.0
         self._ineffective_compression_count: int = 0
         self._summary_failure_cooldown_until: float = 0.0
-        self._last_summary_error: Optional[str] = None
 
     def update_from_response(self, usage: Dict[str, Any]):
         """Update tracked token usage from API response."""
@@ -821,12 +812,10 @@ The user has requested that this compaction PRIORITISE preserving all informatio
             self._previous_summary = summary
             self._summary_failure_cooldown_until = 0.0
             self._summary_model_fallen_back = False
-            self._last_summary_error = None
             return self._with_summary_prefix(summary)
         except RuntimeError:
             # No provider configured — long cooldown, unlikely to self-resolve
             self._summary_failure_cooldown_until = time.monotonic() + _SUMMARY_FAILURE_COOLDOWN_SECONDS
-            self._last_summary_error = "no auxiliary LLM provider configured"
             logging.warning("Context compression: no provider available for "
                             "summary. Middle turns will be dropped without summary "
                             "for %d seconds.",
@@ -864,10 +853,6 @@ The user has requested that this compaction PRIORITISE preserving all informatio
             # Transient errors (timeout, rate limit, network) — shorter cooldown
             _transient_cooldown = 60
             self._summary_failure_cooldown_until = time.monotonic() + _transient_cooldown
-            err_text = str(e).strip() or e.__class__.__name__
-            if len(err_text) > 220:
-                err_text = err_text[:217].rstrip() + "..."
-            self._last_summary_error = err_text
             logging.warning(
                 "Failed to generate context summary: %s. "
                 "Further summary attempts paused for %d seconds.",

agent/memory_manager.py

@@ -31,7 +31,6 @@ from __future__ import annotations
 import json
 import logging
 import re
-import inspect
 from typing import Any, Dict, List, Optional
 
 from agent.memory_provider import MemoryProvider
@@ -313,39 +312,7 @@ class MemoryManager:
                 )
         return "\n\n".join(parts)
 
-    @staticmethod
-    def _provider_memory_write_metadata_mode(provider: MemoryProvider) -> str:
-        """Return how to pass metadata to a provider's memory-write hook."""
-        try:
-            signature = inspect.signature(provider.on_memory_write)
-        except (TypeError, ValueError):
-            return "keyword"
-
-        params = list(signature.parameters.values())
-        if any(p.kind == inspect.Parameter.VAR_KEYWORD for p in params):
-            return "keyword"
-        if "metadata" in signature.parameters:
-            return "keyword"
-
-        accepted = [
-            p for p in params
-            if p.kind in (
-                inspect.Parameter.POSITIONAL_ONLY,
-                inspect.Parameter.POSITIONAL_OR_KEYWORD,
-                inspect.Parameter.KEYWORD_ONLY,
-            )
-        ]
-        if len(accepted) >= 4:
-            return "positional"
-        return "legacy"
-
-    def on_memory_write(
-        self,
-        action: str,
-        target: str,
-        content: str,
-        metadata: Optional[Dict[str, Any]] = None,
-    ) -> None:
+    def on_memory_write(self, action: str, target: str, content: str) -> None:
         """Notify external providers when the built-in memory tool writes.
 
         Skips the builtin provider itself (it's the source of the write).
@@ -354,15 +321,7 @@ class MemoryManager:
             if provider.name == "builtin":
                 continue
             try:
-                metadata_mode = self._provider_memory_write_metadata_mode(provider)
-                if metadata_mode == "keyword":
-                    provider.on_memory_write(
-                        action, target, content, metadata=dict(metadata or {})
-                    )
-                elif metadata_mode == "positional":
-                    provider.on_memory_write(action, target, content, dict(metadata or {}))
-                else:
-                    provider.on_memory_write(action, target, content)
+                provider.on_memory_write(action, target, content)
             except Exception as e:
                 logger.debug(
                     "Memory provider '%s' on_memory_write failed: %s",

agent/memory_provider.py

@@ -26,7 +26,7 @@ Optional hooks (override to opt in):
   on_turn_start(turn, message, **kwargs) — per-turn tick with runtime context
   on_session_end(messages)               — end-of-session extraction
   on_pre_compress(messages) -> str       — extract before context compression
-  on_memory_write(action, target, content, metadata=None) — mirror built-in memory writes
+  on_memory_write(action, target, content) — mirror built-in memory writes
   on_delegation(task, result, **kwargs)  — parent-side observation of subagent work
 """
 
@@ -34,7 +34,7 @@ from __future__ import annotations
 
 import logging
 from abc import ABC, abstractmethod
-from typing import Any, Dict, List, Optional
+from typing import Any, Dict, List
 
 logger = logging.getLogger(__name__)
 
@@ -220,21 +220,12 @@ class MemoryProvider(ABC):
           should all have ``env_var`` set and this method stays no-op).
         """
 
-    def on_memory_write(
-        self,
-        action: str,
-        target: str,
-        content: str,
-        metadata: Optional[Dict[str, Any]] = None,
-    ) -> None:
+    def on_memory_write(self, action: str, target: str, content: str) -> None:
         """Called when the built-in memory tool writes an entry.
 
         action: 'add', 'replace', or 'remove'
         target: 'memory' or 'user'
         content: the entry content
-        metadata: structured provenance for the write, when available. Common
-          keys include ``write_origin``, ``execution_context``, ``session_id``,
-          ``parent_session_id``, ``platform``, and ``tool_name``.
 
         Use to mirror built-in memory writes to your backend.
         """

agent/model_metadata.py

@@ -106,11 +106,9 @@ _endpoint_model_metadata_cache_time: Dict[str, float] = {}
 _ENDPOINT_MODEL_CACHE_TTL = 300
 
 # Descending tiers for context length probing when the model is unknown.
-# We start at 256K (covers GPT-5.x, many current large-context models) and
-# step down on context-length errors until one works.  Tier[0] is also the
-# default fallback when no detection method succeeds.
+# We start at 128K (a safe default for most modern models) and step down
+# on context-length errors until one works.
 CONTEXT_PROBE_TIERS = [
-    256_000,
     128_000,
     64_000,
     32_000,
@@ -145,11 +143,10 @@ DEFAULT_CONTEXT_LENGTHS = {
     "claude": 200000,
     # OpenAI — GPT-5 family (most have 400k; specific overrides first)
     # Source: https://developers.openai.com/api/docs/models
-    # GPT-5.5 (launched Apr 23 2026) is 1.05M on the direct OpenAI API and
-    # ChatGPT Codex OAuth caps it at 272K; both paths resolve via their own
-    # provider-aware branches (_resolve_codex_oauth_context_length + models.dev).
-    # This hardcoded value is only reached when every probe misses.
-    "gpt-5.5": 1050000,
+    # GPT-5.5 (launched Apr 23 2026). 400k is the fallback for providers we
+    # can't probe live. ChatGPT Codex OAuth actually caps lower (272k as of
+    # Apr 2026) and is resolved via _resolve_codex_oauth_context_length().
+    "gpt-5.5": 400000,
     "gpt-5.4-nano": 400000,           # 400k (not 1.05M like full 5.4)
     "gpt-5.4-mini": 400000,           # 400k (not 1.05M like full 5.4)
     "gpt-5.4": 1050000,               # GPT-5.4, GPT-5.4 Pro (1.05M context)
@@ -165,17 +162,7 @@ DEFAULT_CONTEXT_LENGTHS = {
     "gemma-4-31b": 256000,
     "gemma-3": 131072,
     "gemma": 8192,  # fallback for older gemma models
-    # DeepSeek — V4 family ships with a 1M context window. The legacy
-    # aliases ``deepseek-chat`` / ``deepseek-reasoner`` are server-side
-    # mapped to the non-thinking / thinking modes of ``deepseek-v4-flash``
-    # and inherit the same 1M window. The ``deepseek`` substring entry
-    # below remains as a 128K fallback for older / unknown DeepSeek model
-    # ids (e.g. via custom endpoints).
-    # https://api-docs.deepseek.com/zh-cn/quick_start/pricing
-    "deepseek-v4-pro": 1_000_000,
-    "deepseek-v4-flash": 1_000_000,
-    "deepseek-chat": 1_000_000,
-    "deepseek-reasoner": 1_000_000,
+    # DeepSeek
     "deepseek": 128000,
     # Meta
     "llama": 131072,
@@ -1206,14 +1193,12 @@ def get_model_context_length(
     api_key: str = "",
     config_context_length: int | None = None,
     provider: str = "",
-    custom_providers: list | None = None,
 ) -> int:
     """Get the context length for a model.
 
     Resolution order:
     0. Explicit config override (model.context_length or custom_providers per-model)
     1. Persistent cache (previously discovered via probing)
-    1b. AWS Bedrock static table (must precede custom-endpoint probe)
     2. Active endpoint metadata (/models for explicit custom endpoints)
     3. Local server query (for local endpoints)
     4. Anthropic /v1/models API (API-key users only, not OAuth)
@@ -1227,23 +1212,6 @@ def get_model_context_length(
     if config_context_length is not None and isinstance(config_context_length, int) and config_context_length > 0:
         return config_context_length
 
-    # 0b. custom_providers per-model override — check before any probe.
-    # This closes the gap where /model switch and display paths used to fall
-    # back to 128K despite the user having a per-model context_length set.
-    # See #15779.
-    if custom_providers and base_url and model:
-        try:
-            from hermes_cli.config import get_custom_provider_context_length
-            cp_ctx = get_custom_provider_context_length(
-                model=model,
-                base_url=base_url,
-                custom_providers=custom_providers,
-            )
-            if cp_ctx:
-                return cp_ctx
-        except Exception:
-            pass  # fall through to probing
-
     # Normalise provider-prefixed model names (e.g. "local:model-name" →
     # "model-name") so cache lookups and server queries use the bare ID that
     # local servers actually know about.  Ollama "model:tag" colons are preserved.
@@ -1269,26 +1237,6 @@ def get_model_context_length(
             else:
                 return cached
 
-    # 1b. AWS Bedrock — use static context length table.
-    # Bedrock's ListFoundationModels API doesn't expose context window sizes,
-    # so we maintain a curated table in bedrock_adapter.py that reflects
-    # AWS-imposed limits (e.g. 200K for Claude models vs 1M on the native
-    # Anthropic API).  This must run BEFORE the custom-endpoint probe at
-    # step 2 — bedrock-runtime.<region>.amazonaws.com is not in
-    # _URL_TO_PROVIDER, so it would otherwise be treated as a custom endpoint,
-    # fail the /models probe (Bedrock doesn't expose that shape), and fall
-    # back to the 128K default before reaching the original step 4b branch.
-    if provider == "bedrock" or (
-        base_url
-        and base_url_hostname(base_url).startswith("bedrock-runtime.")
-        and base_url_host_matches(base_url, "amazonaws.com")
-    ):
-        try:
-            from agent.bedrock_adapter import get_bedrock_context_length
-            return get_bedrock_context_length(model)
-        except ImportError:
-            pass  # boto3 not installed — fall through to generic resolution
-
     # 2. Active endpoint metadata for truly custom/unknown endpoints.
     # Known providers (Copilot, OpenAI, Anthropic, etc.) skip this — their
     # /models endpoint may report a provider-imposed limit (e.g. Copilot
@@ -1334,7 +1282,19 @@ def get_model_context_length(
         if ctx:
             return ctx
 
-    # 4b. (Bedrock handled earlier at step 1b — before custom-endpoint probe.)
+    # 4b. AWS Bedrock — use static context length table.
+    # Bedrock's ListFoundationModels doesn't expose context window sizes,
+    # so we maintain a curated table in bedrock_adapter.py.
+    if provider == "bedrock" or (
+        base_url
+        and base_url_hostname(base_url).startswith("bedrock-runtime.")
+        and base_url_host_matches(base_url, "amazonaws.com")
+    ):
+        try:
+            from agent.bedrock_adapter import get_bedrock_context_length
+            return get_bedrock_context_length(model)
+        except ImportError:
+            pass  # boto3 not installed — fall through to generic resolution
 
     # 5. Provider-aware lookups (before generic OpenRouter cache)
     # These are provider-specific and take priority over the generic OR cache,
@@ -1383,7 +1343,7 @@ def get_model_context_length(
     # 6. OpenRouter live API metadata (provider-unaware fallback)
     metadata = fetch_model_metadata()
     if model in metadata:
-        return metadata[model].get("context_length", DEFAULT_FALLBACK_CONTEXT)
+        return metadata[model].get("context_length", 128000)
 
     # 8. Hardcoded defaults (fuzzy match — longest key first for specificity)
     # Only check `default_model in model` (is the key a substring of the input).

agent/nous_rate_guard.py

@@ -180,145 +180,3 @@ def format_remaining(seconds: float) -> str:
     h, remainder = divmod(s, 3600)
     m = remainder // 60
     return f"{h}h {m}m" if m else f"{h}h"
-
-
-# Buckets with reset windows shorter than this are treated as transient
-# (upstream jitter, secondary throttling) rather than a genuine quota
-# exhaustion worth a cross-session breaker trip.
-_MIN_RESET_FOR_BREAKER_SECONDS = 60.0
-
-
-def is_genuine_nous_rate_limit(
-    *,
-    headers: Optional[Mapping[str, str]] = None,
-    last_known_state: Optional[Any] = None,
-) -> bool:
-    """Decide whether a 429 from Nous Portal is a real account rate limit.
-
-    Nous Portal multiplexes multiple upstream providers (DeepSeek, Kimi,
-    MiMo, Hermes, ...) behind one endpoint.  A 429 can mean either:
-
-      (a) The caller's own RPM / RPH / TPM / TPH bucket on Nous is
-          exhausted — a genuine rate limit that will last until the
-          bucket resets.
-      (b) The upstream provider is out of capacity for a specific model
-          — transient, clears in seconds, and has nothing to do with
-          the caller's quota on Nous.
-
-    Tripping the cross-session breaker on (b) blocks ALL Nous requests
-    (and all models, since Nous is one provider key) for minutes even
-    though the caller's account is healthy and a different model would
-    have worked.  That's the bug users hit when DeepSeek V4 Pro 429s
-    trigger a breaker that then blocks Kimi 2.6 and MiMo V2.5 Pro.
-
-    We tell the two apart by looking at:
-
-      1. The 429 response's own ``x-ratelimit-*`` headers.  Nous emits
-         the full suite on every response including 429s.  An exhausted
-         bucket (``remaining == 0`` with a reset window >= 60s) is
-         proof of (a).
-      2. The last-known-good rate-limit state captured by
-         ``_capture_rate_limits()`` on the previous successful
-         response.  If any bucket there was already near-exhausted with
-         a substantial reset window, the current 429 is almost
-         certainly (a) continuing from that condition.
-
-    If neither signal fires, we treat the 429 as (b): fail the single
-    request, let the retry loop or model-switch proceed, and do NOT
-    write the cross-session breaker file.
-
-    Returns True when the evidence points at (a).
-    """
-    # Signal 1: current 429 response headers.
-    state = _parse_buckets_from_headers(headers)
-    if _has_exhausted_bucket(state):
-        return True
-
-    # Signal 2: last-known-good state from a recent successful response.
-    # Accepts either a RateLimitState (dataclass from rate_limit_tracker)
-    # or a dict of bucket snapshots.
-    if last_known_state is not None and _has_exhausted_bucket_in_object(last_known_state):
-        return True
-
-    return False
-
-
-def _parse_buckets_from_headers(
-    headers: Optional[Mapping[str, str]],
-) -> dict[str, tuple[Optional[int], Optional[float]]]:
-    """Extract (remaining, reset_seconds) per bucket from x-ratelimit-* headers.
-
-    Returns empty dict when no rate-limit headers are present.
-    """
-    if not headers:
-        return {}
-
-    lowered = {k.lower(): v for k, v in headers.items()}
-    if not any(k.startswith("x-ratelimit-") for k in lowered):
-        return {}
-
-    def _maybe_int(raw: Optional[str]) -> Optional[int]:
-        if raw is None:
-            return None
-        try:
-            return int(float(raw))
-        except (TypeError, ValueError):
-            return None
-
-    def _maybe_float(raw: Optional[str]) -> Optional[float]:
-        if raw is None:
-            return None
-        try:
-            return float(raw)
-        except (TypeError, ValueError):
-            return None
-
-    result: dict[str, tuple[Optional[int], Optional[float]]] = {}
-    for tag in ("requests", "requests-1h", "tokens", "tokens-1h"):
-        remaining = _maybe_int(lowered.get(f"x-ratelimit-remaining-{tag}"))
-        reset = _maybe_float(lowered.get(f"x-ratelimit-reset-{tag}"))
-        if remaining is not None or reset is not None:
-            result[tag] = (remaining, reset)
-    return result
-
-
-def _has_exhausted_bucket(
-    buckets: Mapping[str, tuple[Optional[int], Optional[float]]],
-) -> bool:
-    """Return True when any bucket has remaining == 0 AND a meaningful reset window."""
-    for remaining, reset in buckets.values():
-        if remaining is None or remaining > 0:
-            continue
-        if reset is None:
-            continue
-        if reset >= _MIN_RESET_FOR_BREAKER_SECONDS:
-            return True
-    return False
-
-
-def _has_exhausted_bucket_in_object(state: Any) -> bool:
-    """Check a RateLimitState-like object for an exhausted bucket.
-
-    Accepts the dataclass from ``agent.rate_limit_tracker`` (buckets
-    exposed as attributes ``requests_min``, ``requests_hour``,
-    ``tokens_min``, ``tokens_hour``) and falls back gracefully for any
-    object missing those attributes.
-    """
-    for attr in ("requests_min", "requests_hour", "tokens_min", "tokens_hour"):
-        bucket = getattr(state, attr, None)
-        if bucket is None:
-            continue
-        limit = getattr(bucket, "limit", 0) or 0
-        remaining = getattr(bucket, "remaining", 0) or 0
-        # Prefer the adjusted "remaining_seconds_now" property when present;
-        # fall back to raw reset_seconds.
-        reset = getattr(bucket, "remaining_seconds_now", None)
-        if reset is None:
-            reset = getattr(bucket, "reset_seconds", 0.0) or 0.0
-        if limit <= 0:
-            continue
-        if remaining > 0:
-            continue
-        if reset >= _MIN_RESET_FOR_BREAKER_SECONDS:
-            return True
-    return False

agent/onboarding.py

@@ -1,144 +0,0 @@
-"""
-Contextual first-touch onboarding hints.
-
-Instead of blocking first-run questionnaires, show a one-time hint the *first*
-time a user hits a behavior fork — message-while-running, first long-running
-tool, etc.  Each hint is shown once per install (tracked in ``config.yaml`` under
-``onboarding.seen.<flag>``) and then never again.
-
-Keep this module tiny and dependency-free so both the CLI and gateway can import
-it without pulling in heavy modules.
-"""
-
-from __future__ import annotations
-
-import logging
-from pathlib import Path
-from typing import Any, Mapping, Optional
-
-logger = logging.getLogger(__name__)
-
-
-# -------------------------------------------------------------------------
-# Flag names (stable — used as config.yaml keys under onboarding.seen)
-# -------------------------------------------------------------------------
-
-BUSY_INPUT_FLAG = "busy_input_prompt"
-TOOL_PROGRESS_FLAG = "tool_progress_prompt"
-
-
-# -------------------------------------------------------------------------
-# Hint content
-# -------------------------------------------------------------------------
-
-def busy_input_hint_gateway(mode: str) -> str:
-    """Hint shown the first time a user messages while the agent is busy.
-
-    ``mode`` is the effective busy_input_mode that was just applied, so the
-    message matches reality ("I just interrupted…" vs "I just queued…").
-    """
-    if mode == "queue":
-        return (
-            "💡 First-time tip — I queued your message instead of interrupting. "
-            "Send `/busy interrupt` to make new messages stop the current task "
-            "immediately, or `/busy status` to check. This notice won't appear again."
-        )
-    return (
-        "💡 First-time tip — I just interrupted my current task to answer you. "
-        "Send `/busy queue` to queue follow-ups for after the current task instead, "
-        "or `/busy status` to check. This notice won't appear again."
-    )
-
-
-def busy_input_hint_cli(mode: str) -> str:
-    """CLI version of the busy-input hint (plain text, no markdown)."""
-    if mode == "queue":
-        return (
-            "(tip) Your message was queued for the next turn. "
-            "Use /busy interrupt to make Enter stop the current run instead. "
-            "This tip only shows once."
-        )
-    return (
-        "(tip) Your message interrupted the current run. "
-        "Use /busy queue to queue messages for the next turn instead. "
-        "This tip only shows once."
-    )
-
-
-def tool_progress_hint_gateway() -> str:
-    return (
-        "💡 First-time tip — that tool took a while and I'm streaming every step. "
-        "If the progress messages feel noisy, send `/verbose` to cycle modes "
-        "(all → new → off). This notice won't appear again."
-    )
-
-
-def tool_progress_hint_cli() -> str:
-    return (
-        "(tip) That tool ran for a while. Use /verbose to cycle tool-progress "
-        "display modes (all -> new -> off -> verbose). This tip only shows once."
-    )
-
-
-# -------------------------------------------------------------------------
-# State read / write
-# -------------------------------------------------------------------------
-
-def _get_seen_dict(config: Mapping[str, Any]) -> Mapping[str, Any]:
-    onboarding = config.get("onboarding") if isinstance(config, Mapping) else None
-    if not isinstance(onboarding, Mapping):
-        return {}
-    seen = onboarding.get("seen")
-    return seen if isinstance(seen, Mapping) else {}
-
-
-def is_seen(config: Mapping[str, Any], flag: str) -> bool:
-    """Return True if the user has already been shown this first-touch hint."""
-    return bool(_get_seen_dict(config).get(flag))
-
-
-def mark_seen(config_path: Path, flag: str) -> bool:
-    """Persist ``onboarding.seen.<flag> = True`` to ``config_path``.
-
-    Uses the atomic YAML writer so a concurrent process can't observe a
-    partially-written file.  Returns True on success, False on any error
-    (including the config file being absent — onboarding is best-effort).
-    """
-    try:
-        import yaml
-        from utils import atomic_yaml_write
-    except Exception as e:  # pragma: no cover — dependency issue
-        logger.debug("onboarding: failed to import yaml/utils: %s", e)
-        return False
-
-    try:
-        cfg: dict = {}
-        if config_path.exists():
-            with open(config_path, encoding="utf-8") as f:
-                cfg = yaml.safe_load(f) or {}
-        if not isinstance(cfg.get("onboarding"), dict):
-            cfg["onboarding"] = {}
-        seen = cfg["onboarding"].get("seen")
-        if not isinstance(seen, dict):
-            seen = {}
-            cfg["onboarding"]["seen"] = seen
-        if seen.get(flag) is True:
-            return True  # already marked — nothing to do
-        seen[flag] = True
-        atomic_yaml_write(config_path, cfg)
-        return True
-    except Exception as e:
-        logger.debug("onboarding: failed to mark flag %s: %s", flag, e)
-        return False
-
-
-__all__ = [
-    "BUSY_INPUT_FLAG",
-    "TOOL_PROGRESS_FLAG",
-    "busy_input_hint_gateway",
-    "busy_input_hint_cli",
-    "tool_progress_hint_gateway",
-    "tool_progress_hint_cli",
-    "is_seen",
-    "mark_seen",
-]

agent/prompt_builder.py

@@ -176,64 +176,6 @@ SKILLS_GUIDANCE = (
     "Skills that aren't maintained become liabilities."
 )
 
-KANBAN_GUIDANCE = (
-    "# You are a Kanban worker\n"
-    "You were spawned by the Hermes Kanban dispatcher to execute ONE task from "
-    "the shared board at `~/.hermes/kanban.db`. Your task id is in "
-    "`$HERMES_KANBAN_TASK`; your workspace is `$HERMES_KANBAN_WORKSPACE`. "
-    "The `kanban_*` tools in your schema are your primary coordination surface — "
-    "they write directly to the shared SQLite DB and work regardless of terminal "
-    "backend (local/docker/modal/ssh).\n"
-    "\n"
-    "## Lifecycle\n"
-    "\n"
-    "1. **Orient.** Call `kanban_show()` first (no args — it defaults to your "
-    "task). The response includes title, body, parent-task handoffs (summary + "
-    "metadata), any prior attempts on this task if you're a retry, the full "
-    "comment thread, and a pre-formatted `worker_context` you can treat as "
-    "ground truth.\n"
-    "2. **Work inside the workspace.** `cd $HERMES_KANBAN_WORKSPACE` before "
-    "any file operations. The workspace is yours for this run. Don't modify "
-    "files outside it unless the task explicitly asks.\n"
-    "3. **Heartbeat on long operations.** Call `kanban_heartbeat(note=...)` "
-    "every few minutes during long subprocesses (training, encoding, crawling). "
-    "Skip heartbeats for short tasks.\n"
-    "4. **Block on genuine ambiguity.** If you need a human decision you cannot "
-    "infer (missing credentials, UX choice, paywalled source, peer output you "
-    "need first), call `kanban_block(reason=\"...\")` and stop. Don't guess. "
-    "The user will unblock with context and the dispatcher will respawn you.\n"
-    "5. **Complete with structured handoff.** Call `kanban_complete(summary=..., "
-    "metadata=...)`. `summary` is 1–3 human-readable sentences naming concrete "
-    "artifacts. `metadata` is machine-readable facts "
-    "(`{changed_files: [...], tests_run: N, decisions: [...]}`). Downstream "
-    "workers read both via their own `kanban_show`. Never put secrets / "
-    "tokens / raw PII in either field — run rows are durable forever.\n"
-    "6. **If follow-up work appears, create it; don't do it.** Use "
-    "`kanban_create(title=..., assignee=<right-profile>, parents=[your-task-id])` "
-    "to spawn a child task for the appropriate specialist profile instead of "
-    "scope-creeping into the next thing.\n"
-    "\n"
-    "## Orchestrator mode\n"
-    "\n"
-    "If your task is itself a decomposition task (e.g. a planner profile given "
-    "a high-level goal), use `kanban_create` to fan out into child tasks — one "
-    "per specialist, each with an explicit `assignee` and `parents=[...]` to "
-    "express dependencies. Then `kanban_complete` your own task with a summary "
-    "of the decomposition. Do NOT execute the work yourself; your job is "
-    "routing, not implementation.\n"
-    "\n"
-    "## Do NOT\n"
-    "\n"
-    "- Do not shell out to `hermes kanban <verb>` for board operations. Use "
-    "the `kanban_*` tools — they work across all terminal backends.\n"
-    "- Do not complete a task you didn't actually finish. Block it.\n"
-    "- Do not assign follow-up work to yourself. Assign it to the right "
-    "specialist profile.\n"
-    "- Do not call `delegate_task` as a board substitute. `delegate_task` is "
-    "for short reasoning subtasks inside your own run; board tasks are for "
-    "cross-agent handoffs that outlive one API loop."
-)
-
 TOOL_USE_ENFORCEMENT_GUIDANCE = (
     "# Tool-use enforcement\n"
     "You MUST use your tools to take action — do not describe what you would do "

agent/skill_commands.py

@@ -7,15 +7,11 @@ can invoke skills via /skill-name commands.
 import json
 import logging
 import re
+import subprocess
 from pathlib import Path
 from typing import Any, Dict, Optional
 
 from hermes_constants import display_hermes_home
-from agent.skill_preprocessing import (
-    expand_inline_shell as _expand_inline_shell,
-    load_skills_config as _load_skills_config,
-    substitute_template_vars as _substitute_template_vars,
-)
 
 logger = logging.getLogger(__name__)
 
@@ -24,6 +20,111 @@ _skill_commands: Dict[str, Dict[str, Any]] = {}
 _SKILL_INVALID_CHARS = re.compile(r"[^a-z0-9-]")
 _SKILL_MULTI_HYPHEN = re.compile(r"-{2,}")
 
+# Matches ${HERMES_SKILL_DIR} / ${HERMES_SESSION_ID} tokens in SKILL.md.
+# Tokens that don't resolve (e.g. ${HERMES_SESSION_ID} with no session) are
+# left as-is so the user can debug them.
+_SKILL_TEMPLATE_RE = re.compile(r"\$\{(HERMES_SKILL_DIR|HERMES_SESSION_ID)\}")
+
+# Matches inline shell snippets like:  !`date +%Y-%m-%d`
+# Non-greedy, single-line only — no newlines inside the backticks.
+_INLINE_SHELL_RE = re.compile(r"!`([^`\n]+)`")
+
+# Cap inline-shell output so a runaway command can't blow out the context.
+_INLINE_SHELL_MAX_OUTPUT = 4000
+
+
+def _load_skills_config() -> dict:
+    """Load the ``skills`` section of config.yaml (best-effort)."""
+    try:
+        from hermes_cli.config import load_config
+
+        cfg = load_config() or {}
+        skills_cfg = cfg.get("skills")
+        if isinstance(skills_cfg, dict):
+            return skills_cfg
+    except Exception:
+        logger.debug("Could not read skills config", exc_info=True)
+    return {}
+
+
+def _substitute_template_vars(
+    content: str,
+    skill_dir: Path | None,
+    session_id: str | None,
+) -> str:
+    """Replace ${HERMES_SKILL_DIR} / ${HERMES_SESSION_ID} in skill content.
+
+    Only substitutes tokens for which a concrete value is available —
+    unresolved tokens are left in place so the author can spot them.
+    """
+    if not content:
+        return content
+
+    skill_dir_str = str(skill_dir) if skill_dir else None
+
+    def _replace(match: re.Match) -> str:
+        token = match.group(1)
+        if token == "HERMES_SKILL_DIR" and skill_dir_str:
+            return skill_dir_str
+        if token == "HERMES_SESSION_ID" and session_id:
+            return str(session_id)
+        return match.group(0)
+
+    return _SKILL_TEMPLATE_RE.sub(_replace, content)
+
+
+def _run_inline_shell(command: str, cwd: Path | None, timeout: int) -> str:
+    """Execute a single inline-shell snippet and return its stdout (trimmed).
+
+    Failures return a short ``[inline-shell error: ...]`` marker instead of
+    raising, so one bad snippet can't wreck the whole skill message.
+    """
+    try:
+        completed = subprocess.run(
+            ["bash", "-c", command],
+            cwd=str(cwd) if cwd else None,
+            capture_output=True,
+            text=True,
+            timeout=max(1, int(timeout)),
+            check=False,
+        )
+    except subprocess.TimeoutExpired:
+        return f"[inline-shell timeout after {timeout}s: {command}]"
+    except FileNotFoundError:
+        return f"[inline-shell error: bash not found]"
+    except Exception as exc:
+        return f"[inline-shell error: {exc}]"
+
+    output = (completed.stdout or "").rstrip("\n")
+    if not output and completed.stderr:
+        output = completed.stderr.rstrip("\n")
+    if len(output) > _INLINE_SHELL_MAX_OUTPUT:
+        output = output[:_INLINE_SHELL_MAX_OUTPUT] + "…[truncated]"
+    return output
+
+
+def _expand_inline_shell(
+    content: str,
+    skill_dir: Path | None,
+    timeout: int,
+) -> str:
+    """Replace every !`cmd` snippet in ``content`` with its stdout.
+
+    Runs each snippet with the skill directory as CWD so relative paths in
+    the snippet work the way the author expects.
+    """
+    if "!`" not in content:
+        return content
+
+    def _replace(match: re.Match) -> str:
+        cmd = match.group(1).strip()
+        if not cmd:
+            return ""
+        return _run_inline_shell(cmd, skill_dir, timeout)
+
+    return _INLINE_SHELL_RE.sub(_replace, content)
+
+
 def _load_skill_payload(skill_identifier: str, task_id: str | None = None) -> tuple[dict[str, Any], Path | None, str] | None:
     """Load a skill by name/path and return (loaded_payload, skill_dir, display_name)."""
     raw_identifier = (skill_identifier or "").strip()
@@ -42,9 +143,7 @@ def _load_skill_payload(skill_identifier: str, task_id: str | None = None) -> tu
         else:
             normalized = raw_identifier.lstrip("/")
 
-        loaded_skill = json.loads(
-            skill_view(normalized, task_id=task_id, preprocess=False)
-        )
+        loaded_skill = json.loads(skill_view(normalized, task_id=task_id))
     except Exception:
         return None
 

agent/skill_preprocessing.py

@@ -1,131 +0,0 @@
-"""Shared SKILL.md preprocessing helpers."""
-
-import logging
-import re
-import subprocess
-from pathlib import Path
-
-logger = logging.getLogger(__name__)
-
-# Matches ${HERMES_SKILL_DIR} / ${HERMES_SESSION_ID} tokens in SKILL.md.
-# Tokens that don't resolve (e.g. ${HERMES_SESSION_ID} with no session) are
-# left as-is so the user can debug them.
-_SKILL_TEMPLATE_RE = re.compile(r"\$\{(HERMES_SKILL_DIR|HERMES_SESSION_ID)\}")
-
-# Matches inline shell snippets like:  !`date +%Y-%m-%d`
-# Non-greedy, single-line only -- no newlines inside the backticks.
-_INLINE_SHELL_RE = re.compile(r"!`([^`\n]+)`")
-
-# Cap inline-shell output so a runaway command can't blow out the context.
-_INLINE_SHELL_MAX_OUTPUT = 4000
-
-
-def load_skills_config() -> dict:
-    """Load the ``skills`` section of config.yaml (best-effort)."""
-    try:
-        from hermes_cli.config import load_config
-
-        cfg = load_config() or {}
-        skills_cfg = cfg.get("skills")
-        if isinstance(skills_cfg, dict):
-            return skills_cfg
-    except Exception:
-        logger.debug("Could not read skills config", exc_info=True)
-    return {}
-
-
-def substitute_template_vars(
-    content: str,
-    skill_dir: Path | None,
-    session_id: str | None,
-) -> str:
-    """Replace ${HERMES_SKILL_DIR} / ${HERMES_SESSION_ID} in skill content.
-
-    Only substitutes tokens for which a concrete value is available --
-    unresolved tokens are left in place so the author can spot them.
-    """
-    if not content:
-        return content
-
-    skill_dir_str = str(skill_dir) if skill_dir else None
-
-    def _replace(match: re.Match) -> str:
-        token = match.group(1)
-        if token == "HERMES_SKILL_DIR" and skill_dir_str:
-            return skill_dir_str
-        if token == "HERMES_SESSION_ID" and session_id:
-            return str(session_id)
-        return match.group(0)
-
-    return _SKILL_TEMPLATE_RE.sub(_replace, content)
-
-
-def run_inline_shell(command: str, cwd: Path | None, timeout: int) -> str:
-    """Execute a single inline-shell snippet and return its stdout (trimmed).
-
-    Failures return a short ``[inline-shell error: ...]`` marker instead of
-    raising, so one bad snippet can't wreck the whole skill message.
-    """
-    try:
-        completed = subprocess.run(
-            ["bash", "-c", command],
-            cwd=str(cwd) if cwd else None,
-            capture_output=True,
-            text=True,
-            timeout=max(1, int(timeout)),
-            check=False,
-        )
-    except subprocess.TimeoutExpired:
-        return f"[inline-shell timeout after {timeout}s: {command}]"
-    except FileNotFoundError:
-        return "[inline-shell error: bash not found]"
-    except Exception as exc:
-        return f"[inline-shell error: {exc}]"
-
-    output = (completed.stdout or "").rstrip("\n")
-    if not output and completed.stderr:
-        output = completed.stderr.rstrip("\n")
-    if len(output) > _INLINE_SHELL_MAX_OUTPUT:
-        output = output[:_INLINE_SHELL_MAX_OUTPUT] + "...[truncated]"
-    return output
-
-
-def expand_inline_shell(
-    content: str,
-    skill_dir: Path | None,
-    timeout: int,
-) -> str:
-    """Replace every !`cmd` snippet in ``content`` with its stdout.
-
-    Runs each snippet with the skill directory as CWD so relative paths in
-    the snippet work the way the author expects.
-    """
-    if "!`" not in content:
-        return content
-
-    def _replace(match: re.Match) -> str:
-        cmd = match.group(1).strip()
-        if not cmd:
-            return ""
-        return run_inline_shell(cmd, skill_dir, timeout)
-
-    return _INLINE_SHELL_RE.sub(_replace, content)
-
-
-def preprocess_skill_content(
-    content: str,
-    skill_dir: Path | None,
-    session_id: str | None = None,
-    skills_cfg: dict | None = None,
-) -> str:
-    """Apply configured SKILL.md template and inline-shell preprocessing."""
-    if not content:
-        return content
-
-    cfg = skills_cfg if isinstance(skills_cfg, dict) else load_skills_config()
-    if cfg.get("template_vars", True):
-        content = substitute_template_vars(content, skill_dir, session_id)
-    if cfg.get("inline_shell", False):
-        timeout = int(cfg.get("inline_shell_timeout", 10) or 10)
-        content = expand_inline_shell(content, skill_dir, timeout)
-    return content

agent/transports/__init__.py

@@ -23,14 +23,9 @@ def get_transport(api_mode: str):
     This allows gradual migration — call sites can check for None
     and fall back to the legacy code path.
     """
-    cls = _REGISTRY.get(api_mode)
-    if cls is None:
-        # The registry can be partially populated when a specific transport
-        # module was imported directly (for example chat_completions before
-        # codex).  Discover on misses, not only when the registry is empty, so
-        # test/order-dependent imports do not make valid api_modes unavailable.
+    if not _REGISTRY:
         _discover_transports()
-        cls = _REGISTRY.get(api_mode)
+    cls = _REGISTRY.get(api_mode)
     if cls is None:
         return None
     return cls()

agent/transports/chat_completions.py

@@ -31,15 +31,15 @@ class ChatCompletionsTransport(ProviderTransport):
     def convert_messages(self, messages: List[Dict[str, Any]], **kwargs) -> List[Dict[str, Any]]:
         """Messages are already in OpenAI format — sanitize Codex leaks only.
 
-        Strips Codex Responses API fields (``codex_reasoning_items`` /
-        ``codex_message_items`` on the message, ``call_id``/``response_item_id``
-        on tool_calls) that strict chat-completions providers reject with 400/422.
+        Strips Codex Responses API fields (``codex_reasoning_items`` on the
+        message, ``call_id``/``response_item_id`` on tool_calls) that strict
+        chat-completions providers reject with 400/422.
         """
         needs_sanitize = False
         for msg in messages:
             if not isinstance(msg, dict):
                 continue
-            if "codex_reasoning_items" in msg or "codex_message_items" in msg:
+            if "codex_reasoning_items" in msg:
                 needs_sanitize = True
                 break
             tool_calls = msg.get("tool_calls")
@@ -59,7 +59,6 @@ class ChatCompletionsTransport(ProviderTransport):
             if not isinstance(msg, dict):
                 continue
             msg.pop("codex_reasoning_items", None)
-            msg.pop("codex_message_items", None)
             tool_calls = msg.get("tool_calls")
             if isinstance(tool_calls, list):
                 for tc in tool_calls:

agent/transports/codex.py

@@ -120,24 +120,6 @@ class ResponsesApiTransport(ProviderTransport):
         if request_overrides:
             kwargs.update(request_overrides)
 
-        if is_codex_backend:
-            prompt_cache_key = kwargs.get("prompt_cache_key")
-            cache_scope_id = str(prompt_cache_key or session_id or "").strip()
-            if cache_scope_id:
-                existing_extra_headers = kwargs.get("extra_headers")
-                merged_extra_headers: Dict[str, str] = {}
-                if isinstance(existing_extra_headers, dict):
-                    merged_extra_headers.update(
-                        {
-                            str(key): str(value)
-                            for key, value in existing_extra_headers.items()
-                            if key and value is not None
-                        }
-                    )
-                merged_extra_headers["session_id"] = cache_scope_id
-                merged_extra_headers["x-client-request-id"] = cache_scope_id
-                kwargs["extra_headers"] = merged_extra_headers
-
         max_tokens = params.get("max_tokens")
         if max_tokens is not None and not is_codex_backend:
             kwargs["max_output_tokens"] = max_tokens
@@ -178,8 +160,6 @@ class ResponsesApiTransport(ProviderTransport):
         provider_data = {}
         if msg and hasattr(msg, "codex_reasoning_items") and msg.codex_reasoning_items:
             provider_data["codex_reasoning_items"] = msg.codex_reasoning_items
-        if msg and hasattr(msg, "codex_message_items") and msg.codex_message_items:
-            provider_data["codex_message_items"] = msg.codex_message_items
         if msg and hasattr(msg, "reasoning_details") and msg.reasoning_details:
             provider_data["reasoning_details"] = msg.reasoning_details
 

agent/transports/types.py

@@ -97,7 +97,7 @@ class NormalizedResponse:
     Response-level ``provider_data`` examples:
 
     * Anthropic: ``{"reasoning_details": [...]}``
-    * Codex: ``{"codex_reasoning_items": [...], "codex_message_items": [...]}``
+    * Codex: ``{"codex_reasoning_items": [...]}``
     * Others: ``None``
     """
 
@@ -126,11 +126,6 @@ class NormalizedResponse:
         pd = self.provider_data or {}
         return pd.get("codex_reasoning_items")
 
-    @property
-    def codex_message_items(self):
-        pd = self.provider_data or {}
-        return pd.get("codex_message_items")
-
 
 # ---------------------------------------------------------------------------
 # Factory helpers

batch_runner.py

@@ -951,9 +951,13 @@ class BatchRunner:
                     root_logger.setLevel(original_level)
         
         # Aggregate all batch statistics and update checkpoint
+        all_completed_prompts = list(completed_prompts_set)
         total_reasoning_stats = {"total_assistant_turns": 0, "turns_with_reasoning": 0, "turns_without_reasoning": 0}
-
+        
         for batch_result in results:
+            # Add newly completed prompts
+            all_completed_prompts.extend(batch_result.get("completed_prompts", []))
+            
             # Aggregate tool stats
             for tool_name, stats in batch_result.get("tool_stats", {}).items():
                 if tool_name not in total_tool_stats:
@@ -973,7 +977,7 @@ class BatchRunner:
         
         # Save final checkpoint (best-effort; incremental writes already happened)
         try:
-            checkpoint_data["completed_prompts"] = sorted(completed_prompts_set)
+            checkpoint_data["completed_prompts"] = all_completed_prompts
             self._save_checkpoint(checkpoint_data, lock=checkpoint_lock)
         except Exception as ckpt_err:
             print(f"⚠️  Warning: Failed to save final checkpoint: {ckpt_err}")

cli-config.yaml.example

@@ -790,16 +790,9 @@ code_execution:
 # Supports single tasks and batch mode (default 3 parallel, configurable).
 delegation:
   max_iterations: 50                          # Max tool-calling turns per child (default: 50)
-  # max_concurrent_children: 3                # Max parallel child agents per batch (default: 3, floor: 1, no ceiling).
-                                              # WARNING: values above 10 multiply API cost linearly.
-  # max_spawn_depth: 1                        # Delegation tree depth cap (range: 1-3, default: 1 = flat).
-                                              # Raise to 2 to allow workers to spawn their own subagents.
-                                              # Requires role="orchestrator" on intermediate agents.
+  # max_concurrent_children: 3                # Max parallel child agents (default: 3)
+  # max_spawn_depth: 1                        # Tree depth cap (1-3, default: 1 = flat). Raise to 2 or 3 to allow orchestrator children to spawn their own workers.
   # orchestrator_enabled: true                # Kill switch for role="orchestrator" children (default: true).
-  # subagent_auto_approve: false              # When a subagent hits a dangerous-command approval prompt, auto-deny (default: false)
-                                              # or auto-approve "once" (true) instead of blocking on stdin.
-                                              # The parent TUI owns stdin, so blocking would deadlock; non-interactive resolution is required.
-                                              # Both choices emit a logger.warning audit line. Flip to true only for cron/batch pipelines.
   # inherit_mcp_toolsets: true                # When explicit child toolsets are narrowed, also keep the parent's MCP toolsets (default: true). Set false for strict intersection.
   # model: "google/gemini-3-flash-preview"    # Override model for subagents (empty = inherit parent)
   # provider: "openrouter"                    # Override provider for subagents (empty = inherit parent)
@@ -824,9 +817,7 @@ delegation:
 # Display
 # =============================================================================
 display:
-  # Use compact banner mode (hides the ASCII-art banner, shows a single line).
-  #   true:  Compact single-line banner
-  #   false: Full ASCII banner with tool/skill summary (default)
+  # Use compact banner mode
   compact: false
 
   # Tool progress display level (CLI and gateway)
@@ -840,15 +831,12 @@ display:
   # Gateway-only natural mid-turn assistant updates.
   # When true, completed assistant status messages are sent as separate chat
   # messages. This is independent of tool_progress and gateway streaming.
-  #   true:  Send mid-turn assistant updates as separate messages (default)
-  #   false: Only send the final response
   interim_assistant_messages: true
 
-  # What Enter does when Hermes is already busy (CLI and gateway platforms).
+  # What Enter does when Hermes is already busy in the CLI.
   #   interrupt: Interrupt the current run and redirect Hermes (default)
   #   queue:     Queue your message for the next turn
-  # Ctrl+C (or /stop in gateway) always interrupts regardless of this setting.
-  # Toggle at runtime with /busy_input_mode <interrupt|queue>.
+  # Ctrl+C always interrupts regardless of this setting.
   busy_input_mode: interrupt
 
   # Background process notifications (gateway/messaging only).
@@ -864,22 +852,17 @@ display:
   # Play terminal bell when agent finishes a response.
   # Useful for long-running tasks — your terminal will ding when the agent is done.
   # Works over SSH. Most terminals can be configured to flash the taskbar or play a sound.
-  #   true:  Ring the terminal bell on each response
-  #   false: Silent (default)
   bell_on_complete: false
 
   # Show model reasoning/thinking before each response.
   # When enabled, a dim box shows the model's thought process above the response.
   # Toggle at runtime with /reasoning show or /reasoning hide.
-  #   true:  Show the reasoning box
-  #   false: Hide reasoning (default)
   show_reasoning: false
 
   # Stream tokens to the terminal as they arrive instead of waiting for the
   # full response. The response box opens on first token and text appears
   # line-by-line. Tool calls are still captured silently.
-  #   true:  Stream tokens as they arrive (default)
-  #   false: Wait for the full response before rendering
+  # Stream tokens to the terminal in real-time. Disable to wait for full responses.
   streaming: true
 
   # ───────────────────────────────────────────────────────────────────────────
@@ -889,15 +872,10 @@ display:
   # response box label, and branding text. Change at runtime with /skin <name>.
   #
   # Built-in skins:
-  #   default        — Classic Hermes gold/kawaii
-  #   ares           — Crimson/bronze war-god theme with spinner wings
-  #   mono           — Clean grayscale monochrome
-  #   slate          — Cool blue developer-focused
-  #   daylight       — Bright light-mode theme
-  #   warm-lightmode — Warm paper-tone light-mode theme
-  #   poseidon       — Sea-green/teal Olympian theme
-  #   sisyphus       — Earthy stone-and-moss theme
-  #   charizard      — Fiery orange dragon theme
+  #   default  — Classic Hermes gold/kawaii
+  #   ares     — Crimson/bronze war-god theme with spinner wings
+  #   mono     — Clean grayscale monochrome
+  #   slate    — Cool blue developer-focused
   #
   # Custom skins: drop a YAML file in ~/.hermes/skins/<name>.yaml
   # Schema (all fields optional, missing values inherit from default):

cli.py

@@ -22,7 +22,6 @@ import re
 import concurrent.futures
 import base64
 import atexit
-import errno
 import tempfile
 import time
 import uuid
@@ -417,11 +416,6 @@ def load_cli_config() -> Dict[str, Any]:
             "base_url": "",    # Direct OpenAI-compatible endpoint for subagents
             "api_key": "",     # API key for delegation.base_url (falls back to OPENAI_API_KEY)
         },
-        "onboarding": {
-            # First-touch hint flags (see agent/onboarding.py).  Each hint is
-            # shown once per install then latched here.
-            "seen": {},
-        },
     }
     
     # Track whether the config file explicitly set terminal config.
@@ -3182,14 +3176,7 @@ class HermesCLI:
         # the configured model (e.g. "qwen3.6-plus"), causing 400 errors.
         runtime_model = runtime.get("model")
         if runtime_model and isinstance(runtime_model, str):
-            # Only use runtime model if: model is unset, or model equals provider name
-            should_use_runtime_model = (
-                not self.model or  # No model configured yet
-                self.model == self.provider or  # Model is the provider slug
-                self.model == runtime.get("name")  # Model matches provider display name
-            )
-            if should_use_runtime_model:
-                self.model = runtime_model
+            self.model = runtime_model
 
         # If model is still empty (e.g. user ran `hermes auth add openai-codex`
         # without `hermes model`), fall back to the provider's first catalog
@@ -4324,7 +4311,7 @@ class HermesCLI:
 
         _cprint(f"\n  {_DIM}Tip: Just type your message to chat with Hermes!{_RST}")
         _cprint(f"  {_DIM}Multi-line: Alt+Enter for a new line{_RST}")
-        _cprint(f"  {_DIM}Draft editor: Ctrl+G (Alt+G in VSCode/Cursor){_RST}")
+        _cprint(f"  {_DIM}Draft editor: Ctrl+G{_RST}")
         if _is_termux_environment():
             _cprint(f"  {_DIM}Attach image: /image {_termux_example_image_path()} or start your prompt with a local image path{_RST}\n")
         else:
@@ -4674,6 +4661,10 @@ class HermesCLI:
     def new_session(self, silent=False):
         """Start a fresh session with a new session ID and cleared agent state."""
         if self.agent and self.conversation_history:
+            try:
+                self.agent.flush_memories(self.conversation_history)
+            except (Exception, KeyboardInterrupt):
+                pass
             # Trigger memory extraction on the old session before session_id rotates.
             self.agent.commit_memory_session(self.conversation_history)
             self._notify_session_boundary("on_session_finalize")
@@ -5158,29 +5149,27 @@ class HermesCLI:
         _cprint(f"  ✓ Model switched: {result.new_model}")
         _cprint(f"    Provider: {provider_label}")
 
-        # Context: always resolve via the provider-aware chain so Codex OAuth,
-        # Copilot, and Nous-enforced caps win over the raw models.dev entry
-        # (e.g. gpt-5.5 is 1.05M on openai but 272K on Codex OAuth).
         mi = result.model_info
-        try:
-            from hermes_cli.model_switch import resolve_display_context_length
-            ctx = resolve_display_context_length(
-                result.new_model,
-                result.target_provider,
-                base_url=result.base_url or self.base_url or "",
-                api_key=result.api_key or self.api_key or "",
-                model_info=mi,
-            )
-            if ctx:
-                _cprint(f"    Context: {ctx:,} tokens")
-        except Exception:
-            pass
         if mi:
+            if mi.context_window:
+                _cprint(f"    Context: {mi.context_window:,} tokens")
             if mi.max_output:
                 _cprint(f"    Max output: {mi.max_output:,} tokens")
             if mi.has_cost_data():
                 _cprint(f"    Cost: {mi.format_cost()}")
             _cprint(f"    Capabilities: {mi.format_capabilities()}")
+        else:
+            try:
+                from agent.model_metadata import get_model_context_length
+                ctx = get_model_context_length(
+                    result.new_model,
+                    base_url=result.base_url or self.base_url,
+                    api_key=result.api_key or self.api_key,
+                    provider=result.target_provider,
+                )
+                _cprint(f"    Context: {ctx:,} tokens")
+            except Exception:
+                pass
 
         cache_enabled = (
             (base_url_host_matches(result.base_url or "", "openrouter.ai") and "claude" in result.new_model.lower())
@@ -5281,22 +5270,24 @@ class HermesCLI:
         # Parse --provider and --global flags
         model_input, explicit_provider, persist_global = parse_model_flags(raw_args)
 
-        # Load providers for switch_model (picker path needs them below)
         user_provs = None
         custom_provs = None
-        try:
-            from hermes_cli.config import get_compatible_custom_providers, load_config
-            cfg = load_config()
-            user_provs = cfg.get("providers")
-            custom_provs = get_compatible_custom_providers(cfg)
-        except Exception:
-            pass
 
         # No args at all: open prompt_toolkit-native picker modal
         if not model_input and not explicit_provider:
             model_display = self.model or "unknown"
             provider_display = get_label(self.provider) if self.provider else "unknown"
 
+            user_provs = None
+            custom_provs = None
+            try:
+                from hermes_cli.config import get_compatible_custom_providers, load_config
+                cfg = load_config()
+                user_provs = cfg.get("providers")
+                custom_provs = get_compatible_custom_providers(cfg)
+            except Exception:
+                pass
+
             try:
                 providers = list_authenticated_providers(
                     current_provider=self.provider or "",
@@ -5383,26 +5374,29 @@ class HermesCLI:
         _cprint(f"  ✓ Model switched: {result.new_model}")
         _cprint(f"    Provider: {provider_label}")
 
-        # Context: always resolve via the provider-aware chain so Codex OAuth,
-        # Copilot, and Nous-enforced caps win over the raw models.dev entry
-        # (e.g. gpt-5.5 is 1.05M on openai but 272K on Codex OAuth).
+        # Rich metadata from models.dev
         mi = result.model_info
-        from hermes_cli.model_switch import resolve_display_context_length
-        ctx = resolve_display_context_length(
-            result.new_model,
-            result.target_provider,
-            base_url=result.base_url or self.base_url or "",
-            api_key=result.api_key or self.api_key or "",
-            model_info=mi,
-        )
-        if ctx:
-            _cprint(f"    Context: {ctx:,} tokens")
         if mi:
+            if mi.context_window:
+                _cprint(f"    Context: {mi.context_window:,} tokens")
             if mi.max_output:
                 _cprint(f"    Max output: {mi.max_output:,} tokens")
             if mi.has_cost_data():
                 _cprint(f"    Cost: {mi.format_cost()}")
             _cprint(f"    Capabilities: {mi.format_capabilities()}")
+        else:
+            # Fallback to old context length lookup
+            try:
+                from agent.model_metadata import get_model_context_length
+                ctx = get_model_context_length(
+                    result.new_model,
+                    base_url=result.base_url or self.base_url,
+                    api_key=result.api_key or self.api_key,
+                    provider=result.target_provider,
+                )
+                _cprint(f"    Context: {ctx:,} tokens")
+            except Exception:
+                pass
 
         # Cache notice
         cache_enabled = (
@@ -5818,28 +5812,7 @@ class HermesCLI:
 
         print(f"(._.) Unknown cron command: {subcommand}")
         print("  Available: list, add, edit, pause, resume, run, remove")
-
-    def _handle_kanban_command(self, cmd: str):
-        """Handle the /kanban command — delegate to the shared kanban CLI.
-
-        The string form passed here is the user's full ``/kanban ...``
-        including the leading slash; we strip it and hand the remainder
-        to ``kanban.run_slash`` which returns a single formatted string.
-        """
-        from hermes_cli.kanban import run_slash
-
-        rest = cmd.strip()
-        if rest.startswith("/"):
-            rest = rest.lstrip("/")
-        if rest.startswith("kanban"):
-            rest = rest[len("kanban"):].lstrip()
-        try:
-            output = run_slash(rest)
-        except Exception as exc:  # pragma: no cover - defensive
-            output = f"(._.) kanban error: {exc}"
-        if output:
-            print(output)
-
+    
     def _handle_skills_command(self, cmd: str):
         """Handle /skills slash command — delegates to hermes_cli.skills_hub."""
         from hermes_cli.skills_hub import handle_skills_slash
@@ -6076,8 +6049,6 @@ class HermesCLI:
             self.save_conversation()
         elif canonical == "cron":
             self._handle_cron_command(cmd_original)
-        elif canonical == "kanban":
-            self._handle_kanban_command(cmd_original)
         elif canonical == "skills":
             with self._busy_command(self._slow_command_status(cmd_original)):
                 self._handle_skills_command(cmd_original)
@@ -6152,6 +6123,8 @@ class HermesCLI:
             self._handle_agents_command()
         elif canonical == "background":
             self._handle_background_command(cmd_original)
+        elif canonical == "btw":
+            self._handle_btw_command(cmd_original)
         elif canonical == "queue":
             # Extract prompt after "/queue " or "/q "
             parts = cmd_original.split(None, 1)
@@ -6192,8 +6165,6 @@ class HermesCLI:
             self._handle_skin_command(cmd_original)
         elif canonical == "voice":
             self._handle_voice_command(cmd_original)
-        elif canonical == "busy":
-            self._handle_busy_command(cmd_original)
         else:
             # Check for user-defined quick commands (bypass agent loop, no LLM call)
             base_cmd = cmd_lower.split()[0]
@@ -6438,6 +6409,122 @@ class HermesCLI:
         self._background_tasks[task_id] = thread
         thread.start()
 
+    def _handle_btw_command(self, cmd: str):
+        """Handle /btw <question> — ephemeral side question using session context.
+
+        Snapshots the current conversation history, spawns a no-tools agent in
+        a background thread, and prints the answer without persisting anything
+        to the main session.
+        """
+        parts = cmd.strip().split(maxsplit=1)
+        if len(parts) < 2 or not parts[1].strip():
+            _cprint("  Usage: /btw <question>")
+            _cprint("  Example: /btw what module owns session title sanitization?")
+            _cprint("  Answers using session context. No tools, not persisted.")
+            return
+
+        question = parts[1].strip()
+        task_id = f"btw_{datetime.now().strftime('%H%M%S')}_{uuid.uuid4().hex[:6]}"
+
+        if not self._ensure_runtime_credentials():
+            _cprint("  (>_<) Cannot start /btw: no valid credentials.")
+            return
+
+        turn_route = self._resolve_turn_agent_config(question)
+        history_snapshot = list(self.conversation_history)
+
+        preview = question[:60] + ("..." if len(question) > 60 else "")
+        _cprint(f'  💬 /btw: "{preview}"')
+
+        def run_btw():
+            try:
+                btw_agent = AIAgent(
+                    model=turn_route["model"],
+                    api_key=turn_route["runtime"].get("api_key"),
+                    base_url=turn_route["runtime"].get("base_url"),
+                    provider=turn_route["runtime"].get("provider"),
+                    api_mode=turn_route["runtime"].get("api_mode"),
+                    acp_command=turn_route["runtime"].get("command"),
+                    acp_args=turn_route["runtime"].get("args"),
+                    max_iterations=8,
+                    enabled_toolsets=[],
+                    quiet_mode=True,
+                    verbose_logging=False,
+                    session_id=task_id,
+                    platform="cli",
+                    reasoning_config=self.reasoning_config,
+                    service_tier=self.service_tier,
+                    request_overrides=turn_route.get("request_overrides"),
+                    providers_allowed=self._providers_only,
+                    providers_ignored=self._providers_ignore,
+                    providers_order=self._providers_order,
+                    provider_sort=self._provider_sort,
+                    provider_require_parameters=self._provider_require_params,
+                    provider_data_collection=self._provider_data_collection,
+                    fallback_model=self._fallback_model,
+                    session_db=None,
+                    skip_memory=True,
+                    skip_context_files=True,
+                    persist_session=False,
+                )
+
+                btw_prompt = (
+                    "[Ephemeral /btw side question. Answer using the conversation "
+                    "context. No tools available. Be direct and concise.]\n\n"
+                    + question
+                )
+                result = btw_agent.run_conversation(
+                    user_message=btw_prompt,
+                    conversation_history=history_snapshot,
+                    task_id=task_id,
+                )
+
+                response = (result.get("final_response") or "") if result else ""
+                if not response and result and result.get("error"):
+                    response = f"Error: {result['error']}"
+
+                # TUI refresh before printing
+                if self._app:
+                    self._app.invalidate()
+                    time.sleep(0.05)
+                print()
+
+                if response:
+                    try:
+                        from hermes_cli.skin_engine import get_active_skin
+                        _skin = get_active_skin()
+                        _resp_color = _skin.get_color("response_border", "#4F6D4A")
+                    except Exception:
+                        _resp_color = "#4F6D4A"
+
+                    ChatConsole().print(Panel(
+                        _render_final_assistant_content(response, mode=self.final_response_markdown),
+                        title=f"[{_resp_color} bold]⚕ /btw[/]",
+                        title_align="left",
+                        border_style=_resp_color,
+                        box=rich_box.HORIZONTALS,
+                        padding=(1, 4),
+                    ))
+                else:
+                    _cprint("  💬 /btw: (no response)")
+
+                if self.bell_on_complete:
+                    sys.stdout.write("\a")
+                    sys.stdout.flush()
+
+            except Exception as e:
+                if self._app:
+                    self._app.invalidate()
+                    time.sleep(0.05)
+                print()
+                _cprint(f"  ❌ /btw failed: {e}")
+            finally:
+                if self._app:
+                    self._invalidate(min_interval=0)
+
+        thread = threading.Thread(target=run_btw, daemon=True, name=f"btw-{task_id}")
+        thread.start()
+
     @staticmethod
     def _try_launch_chrome_debug(port: int, system: str) -> bool:
         """Try to launch Chrome/Chromium with remote debugging enabled.
@@ -6814,36 +6901,6 @@ class HermesCLI:
         else:
             _cprint(f"  {_ACCENT}✓ Reasoning effort set to '{arg}' (session only){_RST}")
 
-    def _handle_busy_command(self, cmd: str):
-        """Handle /busy — control what Enter does while Hermes is working.
-
-        Usage:
-            /busy               Show current busy input mode
-            /busy status        Show current busy input mode
-            /busy queue         Queue input for the next turn instead of interrupting
-            /busy interrupt     Interrupt the current run on Enter (default)
-        """
-        parts = cmd.strip().split(maxsplit=1)
-        if len(parts) < 2 or parts[1].strip().lower() == "status":
-            _cprint(f"  {_ACCENT}Busy input mode: {self.busy_input_mode}{_RST}")
-            _cprint(f"  {_DIM}Enter while busy: {'queues for next turn' if self.busy_input_mode == 'queue' else 'interrupts current run'}{_RST}")
-            _cprint(f"  {_DIM}Usage: /busy [queue|interrupt|status]{_RST}")
-            return
-
-        arg = parts[1].strip().lower()
-        if arg not in {"queue", "interrupt"}:
-            _cprint(f"  {_DIM}(._.) Unknown argument: {arg}{_RST}")
-            _cprint(f"  {_DIM}Usage: /busy [queue|interrupt|status]{_RST}")
-            return
-
-        self.busy_input_mode = arg
-        if save_config_value("display.busy_input_mode", arg):
-            behavior = "Enter will queue follow-up input while Hermes is busy." if arg == "queue" else "Enter will interrupt the current run while Hermes is busy."
-            _cprint(f"  {_ACCENT}✓ Busy input mode set to '{arg}' (saved to config){_RST}")
-            _cprint(f"  {_DIM}{behavior}{_RST}")
-        else:
-            _cprint(f"  {_ACCENT}✓ Busy input mode set to '{arg}' (session only){_RST}")
-
     def _handle_fast_command(self, cmd: str):
         """Handle /fast — toggle fast mode (OpenAI Priority Processing / Anthropic Fast Mode)."""
         if not self._fast_command_available():
@@ -6922,52 +6979,51 @@ class HermesCLI:
                 focus_topic = parts[1].strip()
 
         original_count = len(self.conversation_history)
-        with self._busy_command("Compressing context..."):
-            try:
-                from agent.model_metadata import estimate_messages_tokens_rough
-                from agent.manual_compression_feedback import summarize_manual_compression
-                original_history = list(self.conversation_history)
-                approx_tokens = estimate_messages_tokens_rough(original_history)
-                if focus_topic:
-                    print(f"🗜️  Compressing {original_count} messages (~{approx_tokens:,} tokens), "
-                          f"focus: \"{focus_topic}\"...")
-                else:
-                    print(f"🗜️  Compressing {original_count} messages (~{approx_tokens:,} tokens)...")
+        try:
+            from agent.model_metadata import estimate_messages_tokens_rough
+            from agent.manual_compression_feedback import summarize_manual_compression
+            original_history = list(self.conversation_history)
+            approx_tokens = estimate_messages_tokens_rough(original_history)
+            if focus_topic:
+                print(f"🗜️  Compressing {original_count} messages (~{approx_tokens:,} tokens), "
+                      f"focus: \"{focus_topic}\"...")
+            else:
+                print(f"🗜️  Compressing {original_count} messages (~{approx_tokens:,} tokens)...")
 
-                compressed, _ = self.agent._compress_context(
-                    original_history,
-                    self.agent._cached_system_prompt or "",
-                    approx_tokens=approx_tokens,
-                    focus_topic=focus_topic or None,
-                )
-                self.conversation_history = compressed
-                # _compress_context ends the old session and creates a new child
-                # session on the agent (run_agent.py::_compress_context). Sync the
-                # CLI's session_id so /status, /resume, exit summary, and title
-                # generation all point at the live continuation session, not the
-                # ended parent. Without this, subsequent end_session() calls target
-                # the already-closed parent and the child is orphaned.
-                if (
-                    getattr(self.agent, "session_id", None)
-                    and self.agent.session_id != self.session_id
-                ):
-                    self.session_id = self.agent.session_id
-                    self._pending_title = None
-                new_tokens = estimate_messages_tokens_rough(self.conversation_history)
-                summary = summarize_manual_compression(
-                    original_history,
-                    self.conversation_history,
-                    approx_tokens,
-                    new_tokens,
-                )
-                icon = "🗜️" if summary["noop"] else "✅"
-                print(f"  {icon} {summary['headline']}")
-                print(f"     {summary['token_line']}")
-                if summary["note"]:
-                    print(f"     {summary['note']}")
+            compressed, _ = self.agent._compress_context(
+                original_history,
+                self.agent._cached_system_prompt or "",
+                approx_tokens=approx_tokens,
+                focus_topic=focus_topic or None,
+            )
+            self.conversation_history = compressed
+            # _compress_context ends the old session and creates a new child
+            # session on the agent (run_agent.py::_compress_context). Sync the
+            # CLI's session_id so /status, /resume, exit summary, and title
+            # generation all point at the live continuation session, not the
+            # ended parent. Without this, subsequent end_session() calls target
+            # the already-closed parent and the child is orphaned.
+            if (
+                getattr(self.agent, "session_id", None)
+                and self.agent.session_id != self.session_id
+            ):
+                self.session_id = self.agent.session_id
+                self._pending_title = None
+            new_tokens = estimate_messages_tokens_rough(self.conversation_history)
+            summary = summarize_manual_compression(
+                original_history,
+                self.conversation_history,
+                approx_tokens,
+                new_tokens,
+            )
+            icon = "🗜️" if summary["noop"] else "✅"
+            print(f"  {icon} {summary['headline']}")
+            print(f"     {summary['token_line']}")
+            if summary["note"]:
+                print(f"     {summary['note']}")
 
-            except Exception as e:
-                print(f"  ❌ Compression failed: {e}")
+        except Exception as e:
+            print(f"  ❌ Compression failed: {e}")
 
     def _handle_debug_command(self):
         """Handle /debug — upload debug report + logs and print paste URLs."""
@@ -7322,31 +7378,6 @@ class HermesCLI:
                     _cprint(f"  {line}")
                 except Exception:
                     pass
-                # First-touch onboarding: on the first tool in this process
-                # that takes longer than the threshold while we're in the
-                # noisiest progress mode, print a one-time hint about
-                # /verbose.  Latched on self so it fires at most once per
-                # process; persisted to config.yaml so it never fires again
-                # across processes either.
-                try:
-                    if (
-                        not getattr(self, "_long_tool_hint_fired", False)
-                        and self.tool_progress_mode == "all"
-                        and duration >= 30.0
-                    ):
-                        from agent.onboarding import (
-                            TOOL_PROGRESS_FLAG,
-                            is_seen,
-                            mark_seen,
-                            tool_progress_hint_cli,
-                        )
-                        if not is_seen(CLI_CONFIG, TOOL_PROGRESS_FLAG):
-                            self._long_tool_hint_fired = True
-                            _cprint(f"  {_DIM}{tool_progress_hint_cli()}{_RST}")
-                            mark_seen(_hermes_home / "config.yaml", TOOL_PROGRESS_FLAG)
-                            CLI_CONFIG.setdefault("onboarding", {}).setdefault("seen", {})[TOOL_PROGRESS_FLAG] = True
-                except Exception:
-                    pass
             self._invalidate()
             return
         if event_type != "tool.started":
@@ -9230,24 +9261,6 @@ class HermesCLI:
                                          f"agent_running={self._agent_running}\n")
                         except Exception:
                             pass
-                    # First-touch onboarding: on the very first busy-while-running
-                    # event for this install, print a one-line tip explaining the
-                    # /busy knob.  Flag persists to config.yaml and never fires
-                    # again.  Guarded for exceptions so onboarding can't break
-                    # the input loop.
-                    try:
-                        from agent.onboarding import (
-                            BUSY_INPUT_FLAG,
-                            busy_input_hint_cli,
-                            is_seen,
-                            mark_seen,
-                        )
-                        if not is_seen(CLI_CONFIG, BUSY_INPUT_FLAG):
-                            _cprint(f"  {_DIM}{busy_input_hint_cli(self.busy_input_mode)}{_RST}")
-                            mark_seen(_hermes_home / "config.yaml", BUSY_INPUT_FLAG)
-                            CLI_CONFIG.setdefault("onboarding", {}).setdefault("seen", {})[BUSY_INPUT_FLAG] = True
-                    except Exception:
-                        pass
                 else:
                     self._pending_input.put(payload)
                 event.app.current_buffer.reset(append_to_history=True)
@@ -9262,18 +9275,14 @@ class HermesCLI:
             """Ctrl+Enter (c-j) inserts a newline. Most terminals send c-j for Ctrl+Enter."""
             event.current_buffer.insert_text('\n')
 
-        # VSCode/Cursor bind Ctrl+G to "Find Next" at the editor level, so
-        # the keystroke never reaches the embedded terminal. Alt+G is unbound
-        # in those IDEs and arrives here as ('escape', 'g') — register it as
-        # a fallback so the editor handoff works inside Cursor/VSCode too.
-        _editor_filter = Condition(
-            lambda: not self._clarify_state and not self._approval_state and not self._sudo_state and not self._secret_state
+        @kb.add(
+            'c-g',
+            filter=Condition(
+                lambda: not self._clarify_state and not self._approval_state and not self._sudo_state and not self._secret_state
+            ),
         )
-
-        @kb.add('c-g', filter=_editor_filter)
-        @kb.add('escape', 'g', filter=_editor_filter)
         def handle_open_in_editor(event):
-            """Ctrl+G (or Alt+G in VSCode/Cursor) opens the current draft in an external editor."""
+            """Ctrl+G opens the current draft in an external editor."""
             cli_ref._open_external_editor(event.current_buffer)
 
         @kb.add('tab', eager=True)
@@ -9516,20 +9525,9 @@ class HermesCLI:
         
         @kb.add('c-d')
         def handle_ctrl_d(event):
-            """Ctrl+D: delete char under cursor (standard readline behaviour).
-            Only exit when the input is empty — same as bash/zsh. Pending
-            attached images count as input and block the EOF-exit so the
-            user doesn't lose them silently.
-            """
-            buf = event.app.current_buffer
-            if buf.text:
-                buf.delete()
-            elif self._attached_images:
-                # Empty text but pending attachments — no-op, don't exit.
-                return
-            else:
-                self._should_exit = True
-                event.app.exit()
+            """Handle Ctrl+D - exit."""
+            self._should_exit = True
+            event.app.exit()
 
         _modal_prompt_active = Condition(
             lambda: bool(self._secret_state or self._sudo_state)
@@ -9737,11 +9735,6 @@ class HermesCLI:
                 completer=_completer,
             ),
         )
-        # Keep prompt_toolkit on its simple tempfile path. Setting
-        # buffer.tempfile = "prompt.md" triggers its complex-tempfile branch,
-        # which tries to mkdir() the mkdtemp() directory again and raises
-        # EEXIST. The suffix keeps markdown highlighting without that bug.
-        input_area.buffer.tempfile_suffix = '.md'
 
         # Dynamic height: accounts for both explicit newlines AND visual
         # wrapping of long lines so the input area always fits its content.
@@ -10694,8 +10687,6 @@ class HermesCLI:
                 return  # silently suppress
             if isinstance(exc, KeyError) and "is not registered" in str(exc):
                 return  # suppress selector registration failures (#6393)
-            if isinstance(exc, OSError) and getattr(exc, "errno", None) == errno.EIO:
-                return  # suppress I/O errors from broken stdout on interrupt (#13710)
             # Fall back to default handler for everything else
             loop.default_exception_handler(context)
 
@@ -10728,11 +10719,9 @@ class HermesCLI:
         except (EOFError, KeyboardInterrupt, BrokenPipeError):
             pass
         except (KeyError, OSError) as _stdin_err:
-            # Catch selector registration failures from broken stdin (#6393)
-            # and I/O errors from broken stdout during interrupt (#13710).
-            if isinstance(_stdin_err, OSError) and getattr(_stdin_err, "errno", None) == errno.EIO:
-                pass  # suppress broken-stdout I/O errors on interrupt (#13710)
-            elif "is not registered" in str(_stdin_err) or "Bad file descriptor" in str(_stdin_err):
+            # Catch selector registration failures from broken stdin (#6393).
+            # This is the fallback for cases that slip past the fstat() guard.
+            if "is not registered" in str(_stdin_err) or "Bad file descriptor" in str(_stdin_err):
                 print(
                     f"\nError: stdin is not usable ({_stdin_err}).\n"
                     "This can happen with certain Python installations (e.g. uv-managed cPython on macOS).\n"
@@ -10751,6 +10740,12 @@ class HermesCLI:
                     self.agent.interrupt()
                 except Exception:
                     pass
+            # Flush memories before exit (only for substantial conversations)
+            if self.agent and self.conversation_history:
+                try:
+                    self.agent.flush_memories(self.conversation_history)
+                except (Exception, KeyboardInterrupt):
+                    pass
             # Shut down voice recorder (release persistent audio stream)
             if hasattr(self, '_voice_recorder') and self._voice_recorder:
                 try:

cron/jobs.py

@@ -16,7 +16,7 @@ import uuid
 from datetime import datetime, timedelta
 from pathlib import Path
 from hermes_constants import get_hermes_home
-from typing import Optional, Dict, List, Any, Union
+from typing import Optional, Dict, List, Any
 
 logger = logging.getLogger(__name__)
 
@@ -417,7 +417,6 @@ def create_job(
     provider: Optional[str] = None,
     base_url: Optional[str] = None,
     script: Optional[str] = None,
-    context_from: Optional[Union[str, List[str]]] = None,
     enabled_toolsets: Optional[List[str]] = None,
     workdir: Optional[str] = None,
 ) -> Dict[str, Any]:
@@ -439,9 +438,6 @@ def create_job(
         script: Optional path to a Python script whose stdout is injected into the
                 prompt each run.  The script runs before the agent turn, and its output
                 is prepended as context.  Useful for data collection / change detection.
-        context_from: Optional job ID (or list of job IDs) whose most recent output
-                      is injected into the prompt as context before each run.
-                      Useful for chaining cron jobs: job A finds data, job B processes it.
         enabled_toolsets: Optional list of toolset names to restrict the agent to.
                           When set, only tools from these toolsets are loaded, reducing
                           token overhead. When omitted, all default tools are loaded.
@@ -485,14 +481,6 @@ def create_job(
     normalized_toolsets = normalized_toolsets or None
     normalized_workdir = _normalize_workdir(workdir)
 
-    # Normalize context_from: accept str or list of str, store as list or None
-    if isinstance(context_from, str):
-        context_from = [context_from.strip()] if context_from.strip() else None
-    elif isinstance(context_from, list):
-        context_from = [str(j).strip() for j in context_from if str(j).strip()] or None
-    else:
-        context_from = None
-
     label_source = (prompt or (normalized_skills[0] if normalized_skills else None)) or "cron job"
     job = {
         "id": job_id,
@@ -504,7 +492,6 @@ def create_job(
         "provider": normalized_provider,
         "base_url": normalized_base_url,
         "script": normalized_script,
-        "context_from": context_from,
         "schedule": parsed_schedule,
         "schedule_display": parsed_schedule.get("display", schedule),
         "repeat": {

cron/scheduler.py

@@ -671,47 +671,6 @@ def _build_job_prompt(job: dict, prerun_script: Optional[tuple] = None) -> str:
                 f"{prompt}"
             )
 
-    # Inject output from referenced cron jobs as context.
-    context_from = job.get("context_from")
-    if context_from:
-        from cron.jobs import OUTPUT_DIR
-        if isinstance(context_from, str):
-            context_from = [context_from]
-        for source_job_id in context_from:
-            # Guard against path traversal — valid job IDs are 12-char hex strings
-            if not source_job_id or not all(c in "0123456789abcdef" for c in source_job_id):
-                logger.warning("context_from: skipping invalid job_id %r", source_job_id)
-                continue
-            try:
-                job_output_dir = OUTPUT_DIR / source_job_id
-                if not job_output_dir.exists():
-                    continue  # silent skip — no output yet
-                output_files = sorted(
-                    job_output_dir.glob("*.md"),
-                    key=lambda f: f.stat().st_mtime,
-                    reverse=True,
-                )
-                if not output_files:
-                    continue  # silent skip — no output yet
-                latest_output = output_files[0].read_text(encoding="utf-8").strip()
-                # Truncate to 8K characters to avoid prompt bloat
-                _MAX_CONTEXT_CHARS = 8000
-                if len(latest_output) > _MAX_CONTEXT_CHARS:
-                    latest_output = latest_output[:_MAX_CONTEXT_CHARS] + "\n\n[... output truncated ...]"
-                if latest_output:
-                    prompt = (
-                        f"## Output from job '{source_job_id}'\n"
-                        "The following is the most recent output from a preceding "
-                        "cron job. Use it as context for your analysis.\n\n"
-                        f"```\n{latest_output}\n```\n\n"
-                        f"{prompt}"
-                    )
-                else:
-                    continue  # silent skip — empty output
-            except (OSError, PermissionError) as e:
-                logger.warning("context_from: failed to read output for job %r: %s", source_job_id, e)
-                # silent skip — do not pollute the prompt with error messages
-
     # Always prepend cron execution guidance so the agent knows how
     # delivery works and can suppress delivery when appropriate.
     cron_hint = (

docker/entrypoint.sh

@@ -41,15 +41,6 @@ if [ "$(id -u)" = "0" ]; then
             echo "Warning: chown failed (rootless container?) — continuing anyway"
     fi
 
-    # Ensure config.yaml is readable by the hermes runtime user even if it was
-    # edited on the host after initial ownership setup. Must run here (as root)
-    # rather than after the gosu drop, otherwise a non-root caller like
-    # `docker run -u $(id -u):$(id -g)` hits "Operation not permitted" (#15865).
-    if [ -f "$HERMES_HOME/config.yaml" ]; then
-        chown hermes:hermes "$HERMES_HOME/config.yaml" 2>/dev/null || true
-        chmod 640 "$HERMES_HOME/config.yaml" 2>/dev/null || true
-    fi
-
     echo "Dropping root privileges"
     exec gosu hermes "$0" "$@"
 fi
@@ -76,6 +67,13 @@ if [ ! -f "$HERMES_HOME/config.yaml" ]; then
     cp "$INSTALL_DIR/cli-config.yaml.example" "$HERMES_HOME/config.yaml"
 fi
 
+# Ensure the main config file remains accessible to the hermes runtime user
+# even if it was edited on the host after initial ownership setup.
+if [ -f "$HERMES_HOME/config.yaml" ]; then
+    chown hermes:hermes "$HERMES_HOME/config.yaml"
+    chmod 640 "$HERMES_HOME/config.yaml"
+fi
+
 # SOUL.md
 if [ ! -f "$HERMES_HOME/SOUL.md" ]; then
     cp "$INSTALL_DIR/docker/SOUL.md" "$HERMES_HOME/SOUL.md"

gateway/config.py

@@ -135,7 +135,7 @@ class SessionResetPolicy:
             mode=mode if mode is not None else "both",
             at_hour=at_hour if at_hour is not None else 4,
             idle_minutes=idle_minutes if idle_minutes is not None else 1440,
-            notify=_coerce_bool(notify, True),
+            notify=notify if notify is not None else True,
             notify_exclude_platforms=tuple(exclude) if exclude is not None else ("api_server", "webhook"),
         )
 
@@ -178,7 +178,7 @@ class PlatformConfig:
             home_channel = HomeChannel.from_dict(data["home_channel"])
         
         return cls(
-            enabled=_coerce_bool(data.get("enabled"), False),
+            enabled=data.get("enabled", False),
             token=data.get("token"),
             api_key=data.get("api_key"),
             home_channel=home_channel,
@@ -435,7 +435,7 @@ class GatewayConfig:
             reset_triggers=data.get("reset_triggers", ["/new", "/reset"]),
             quick_commands=quick_commands,
             sessions_dir=sessions_dir,
-            always_log_local=_coerce_bool(data.get("always_log_local"), True),
+            always_log_local=data.get("always_log_local", True),
             stt_enabled=_coerce_bool(stt_enabled, True),
             group_sessions_per_user=_coerce_bool(group_sessions_per_user, True),
             thread_sessions_per_user=_coerce_bool(thread_sessions_per_user, False),
@@ -687,11 +687,6 @@ def load_gateway_config() -> GatewayConfig:
                     os.environ["TELEGRAM_REACTIONS"] = str(telegram_cfg["reactions"]).lower()
                 if "proxy_url" in telegram_cfg and not os.getenv("TELEGRAM_PROXY"):
                     os.environ["TELEGRAM_PROXY"] = str(telegram_cfg["proxy_url"]).strip()
-                if "group_allowed_chats" in telegram_cfg and not os.getenv("TELEGRAM_GROUP_ALLOWED_USERS"):
-                    gac = telegram_cfg["group_allowed_chats"]
-                    if isinstance(gac, list):
-                        gac = ",".join(str(v) for v in gac)
-                    os.environ["TELEGRAM_GROUP_ALLOWED_USERS"] = str(gac)
                 if "disable_link_previews" in telegram_cfg:
                     plat_data = platforms_data.setdefault(Platform.TELEGRAM.value, {})
                     if not isinstance(plat_data, dict):

gateway/hooks.py

@@ -21,7 +21,6 @@ Errors in hooks are caught and logged but never block the main pipeline.
 
 import asyncio
 import importlib.util
-import sys
 from typing import Any, Callable, Dict, List, Optional
 
 import yaml
@@ -104,28 +103,16 @@ class HookRegistry:
                     print(f"[hooks] Skipping {hook_name}: no events declared", flush=True)
                     continue
 
-                # Dynamically load the handler module.
-                # Register in sys.modules BEFORE exec_module so Pydantic /
-                # dataclasses / typing introspection can resolve forward
-                # references (triggered by `from __future__ import annotations`
-                # in the handler). Without this, a handler that declares a
-                # Pydantic BaseModel for webhook/event payloads fails at first
-                # dispatch with "TypeAdapter ... is not fully defined".
-                module_name = f"hermes_hook_{hook_name}"
+                # Dynamically load the handler module
                 spec = importlib.util.spec_from_file_location(
-                    module_name, handler_path
+                    f"hermes_hook_{hook_name}", handler_path
                 )
                 if spec is None or spec.loader is None:
                     print(f"[hooks] Skipping {hook_name}: could not load handler.py", flush=True)
                     continue
 
                 module = importlib.util.module_from_spec(spec)
-                sys.modules[module_name] = module
-                try:
-                    spec.loader.exec_module(module)
-                except Exception:
-                    sys.modules.pop(module_name, None)
-                    raise
+                spec.loader.exec_module(module)
 
                 handle_fn = getattr(module, "handle", None)
                 if handle_fn is None:

gateway/platforms/api_server.py

@@ -9,7 +9,6 @@ Exposes an HTTP server with endpoints:
 - GET  /v1/models                  — lists hermes-agent as an available model
 - POST /v1/runs                    — start a run, returns run_id immediately (202)
 - GET  /v1/runs/{run_id}/events    — SSE stream of structured lifecycle events
-- POST /v1/runs/{run_id}/stop    — interrupt a running agent
 - GET  /health                     — health check
 - GET  /health/detailed            — rich status for cross-container dashboard probing
 
@@ -587,9 +586,6 @@ class APIServerAdapter(BasePlatformAdapter):
         self._run_streams: Dict[str, "asyncio.Queue[Optional[Dict]]"] = {}
         # Creation timestamps for orphaned-run TTL sweep
         self._run_streams_created: Dict[str, float] = {}
-        # Active run agent/task references for stop support
-        self._active_run_agents: Dict[str, Any] = {}
-        self._active_run_tasks: Dict[str, "asyncio.Task"] = {}
         self._session_db: Optional[Any] = None  # Lazy-init SessionDB for session continuity
 
     @staticmethod
@@ -1208,12 +1204,10 @@ class APIServerAdapter(BasePlatformAdapter):
 
         If the client disconnects mid-stream, ``agent.interrupt()`` is
         called so the agent stops issuing upstream LLM calls, then the
-        asyncio task is cancelled.  When ``store=True`` an initial
-        ``in_progress`` snapshot is persisted immediately after
-        ``response.created`` and disconnects update it to an
-        ``incomplete`` snapshot so GET /v1/responses/{id} and
-        ``previous_response_id`` chaining still have something to
-        recover from.
+        asyncio task is cancelled.  When ``store=True`` the full response
+        is persisted to the ResponseStore in a ``finally`` block so GET
+        /v1/responses/{id} and ``previous_response_id`` chaining work the
+        same as the batch path.
         """
         import queue as _q
 
@@ -1275,60 +1269,6 @@ class APIServerAdapter(BasePlatformAdapter):
         final_response_text = ""
         agent_error: Optional[str] = None
         usage: Dict[str, int] = {"input_tokens": 0, "output_tokens": 0, "total_tokens": 0}
-        terminal_snapshot_persisted = False
-
-        def _persist_response_snapshot(
-            response_env: Dict[str, Any],
-            *,
-            conversation_history_snapshot: Optional[List[Dict[str, Any]]] = None,
-        ) -> None:
-            if not store:
-                return
-            if conversation_history_snapshot is None:
-                conversation_history_snapshot = list(conversation_history)
-                conversation_history_snapshot.append({"role": "user", "content": user_message})
-            self._response_store.put(response_id, {
-                "response": response_env,
-                "conversation_history": conversation_history_snapshot,
-                "instructions": instructions,
-                "session_id": session_id,
-            })
-            if conversation:
-                self._response_store.set_conversation(conversation, response_id)
-
-        def _persist_incomplete_if_needed() -> None:
-            """Persist an ``incomplete`` snapshot if no terminal one was written.
-
-            Called from both the client-disconnect (``ConnectionResetError``)
-            and server-cancellation (``asyncio.CancelledError``) paths so
-            GET /v1/responses/{id} and ``previous_response_id`` chaining keep
-            working after abrupt stream termination.
-            """
-            if not store or terminal_snapshot_persisted:
-                return
-            incomplete_text = "".join(final_text_parts) or final_response_text
-            incomplete_items: List[Dict[str, Any]] = list(emitted_items)
-            if incomplete_text:
-                incomplete_items.append({
-                    "type": "message",
-                    "role": "assistant",
-                    "content": [{"type": "output_text", "text": incomplete_text}],
-                })
-            incomplete_env = _envelope("incomplete")
-            incomplete_env["output"] = incomplete_items
-            incomplete_env["usage"] = {
-                "input_tokens": usage.get("input_tokens", 0),
-                "output_tokens": usage.get("output_tokens", 0),
-                "total_tokens": usage.get("total_tokens", 0),
-            }
-            incomplete_history = list(conversation_history)
-            incomplete_history.append({"role": "user", "content": user_message})
-            if incomplete_text:
-                incomplete_history.append({"role": "assistant", "content": incomplete_text})
-            _persist_response_snapshot(
-                incomplete_env,
-                conversation_history_snapshot=incomplete_history,
-            )
 
         try:
             # response.created — initial envelope, status=in_progress
@@ -1338,7 +1278,6 @@ class APIServerAdapter(BasePlatformAdapter):
                 "type": "response.created",
                 "response": created_env,
             })
-            _persist_response_snapshot(created_env)
             last_activity = time.monotonic()
 
             async def _open_message_item() -> None:
@@ -1595,18 +1534,6 @@ class APIServerAdapter(BasePlatformAdapter):
                     "output_tokens": usage.get("output_tokens", 0),
                     "total_tokens": usage.get("total_tokens", 0),
                 }
-                _failed_history = list(conversation_history)
-                _failed_history.append({"role": "user", "content": user_message})
-                if final_response_text or agent_error:
-                    _failed_history.append({
-                        "role": "assistant",
-                        "content": final_response_text or agent_error,
-                    })
-                _persist_response_snapshot(
-                    failed_env,
-                    conversation_history_snapshot=_failed_history,
-                )
-                terminal_snapshot_persisted = True
                 await _write_event("response.failed", {
                     "type": "response.failed",
                     "response": failed_env,
@@ -1619,24 +1546,30 @@ class APIServerAdapter(BasePlatformAdapter):
                     "output_tokens": usage.get("output_tokens", 0),
                     "total_tokens": usage.get("total_tokens", 0),
                 }
-                full_history = list(conversation_history)
-                full_history.append({"role": "user", "content": user_message})
-                if isinstance(result, dict) and result.get("messages"):
-                    full_history.extend(result["messages"])
-                else:
-                    full_history.append({"role": "assistant", "content": final_response_text})
-                _persist_response_snapshot(
-                    completed_env,
-                    conversation_history_snapshot=full_history,
-                )
-                terminal_snapshot_persisted = True
                 await _write_event("response.completed", {
                     "type": "response.completed",
                     "response": completed_env,
                 })
 
+                # Persist for future chaining / GET retrieval, mirroring
+                # the batch path behavior.
+                if store:
+                    full_history = list(conversation_history)
+                    full_history.append({"role": "user", "content": user_message})
+                    if isinstance(result, dict) and result.get("messages"):
+                        full_history.extend(result["messages"])
+                    else:
+                        full_history.append({"role": "assistant", "content": final_response_text})
+                    self._response_store.put(response_id, {
+                        "response": completed_env,
+                        "conversation_history": full_history,
+                        "instructions": instructions,
+                        "session_id": session_id,
+                    })
+                    if conversation:
+                        self._response_store.set_conversation(conversation, response_id)
+
         except (ConnectionResetError, ConnectionAbortedError, BrokenPipeError, OSError):
-            _persist_incomplete_if_needed()
             # Client disconnected — interrupt the agent so it stops
             # making upstream LLM calls, then cancel the task.
             agent = agent_ref[0] if agent_ref else None
@@ -1652,22 +1585,6 @@ class APIServerAdapter(BasePlatformAdapter):
                 except (asyncio.CancelledError, Exception):
                     pass
             logger.info("SSE client disconnected; interrupted agent task %s", response_id)
-        except asyncio.CancelledError:
-            # Server-side cancellation (e.g. shutdown, request timeout) —
-            # persist an incomplete snapshot so GET /v1/responses/{id} and
-            # previous_response_id chaining still work, then re-raise so the
-            # runtime's cancellation semantics are respected.
-            _persist_incomplete_if_needed()
-            agent = agent_ref[0] if agent_ref else None
-            if agent is not None:
-                try:
-                    agent.interrupt("SSE task cancelled")
-                except Exception:
-                    pass
-            if not agent_task.done():
-                agent_task.cancel()
-            logger.info("SSE task cancelled; persisted incomplete snapshot for %s", response_id)
-            raise
 
         return response
 
@@ -2445,7 +2362,6 @@ class APIServerAdapter(BasePlatformAdapter):
                     stream_delta_callback=_text_cb,
                     tool_progress_callback=event_cb,
                 )
-                self._active_run_agents[run_id] = agent
                 def _run_sync():
                     r = agent.run_conversation(
                         user_message=user_message,
@@ -2485,11 +2401,8 @@ class APIServerAdapter(BasePlatformAdapter):
                     q.put_nowait(None)
                 except Exception:
                     pass
-                self._active_run_agents.pop(run_id, None)
-                self._active_run_tasks.pop(run_id, None)
 
         task = asyncio.create_task(_run_and_close())
-        self._active_run_tasks[run_id] = task
         try:
             self._background_tasks.add(task)
         except TypeError:
@@ -2548,44 +2461,6 @@ class APIServerAdapter(BasePlatformAdapter):
 
         return response
 
-    async def _handle_stop_run(self, request: "web.Request") -> "web.Response":
-        """POST /v1/runs/{run_id}/stop — interrupt a running agent."""
-        auth_err = self._check_auth(request)
-        if auth_err:
-            return auth_err
-
-        run_id = request.match_info["run_id"]
-        agent = self._active_run_agents.get(run_id)
-        task = self._active_run_tasks.get(run_id)
-
-        if agent is None and task is None:
-            return web.json_response(_openai_error(f"Run not found: {run_id}", code="run_not_found"), status=404)
-
-        if agent is not None:
-            try:
-                agent.interrupt("Stop requested via API")
-            except Exception:
-                pass
-
-        if task is not None and not task.done():
-            task.cancel()
-            # Bounded wait: run_conversation() executes in the default
-            # executor thread which task.cancel() cannot preempt — we rely on
-            # agent.interrupt() above to break the loop. Cap the wait so a
-            # slow/unresponsive interrupt can't hang this handler.
-            try:
-                await asyncio.wait_for(asyncio.shield(task), timeout=5.0)
-            except asyncio.TimeoutError:
-                logger.warning(
-                    "[api_server] stop for run %s timed out after 5s; "
-                    "agent may still be finishing the current step",
-                    run_id,
-                )
-            except (asyncio.CancelledError, Exception):
-                pass
-
-        return web.json_response({"run_id": run_id, "status": "stopping"})
-
     async def _sweep_orphaned_runs(self) -> None:
         """Periodically clean up run streams that were never consumed."""
         while True:
@@ -2600,8 +2475,6 @@ class APIServerAdapter(BasePlatformAdapter):
                 logger.debug("[api_server] sweeping orphaned run %s", run_id)
                 self._run_streams.pop(run_id, None)
                 self._run_streams_created.pop(run_id, None)
-                self._active_run_agents.pop(run_id, None)
-                self._active_run_tasks.pop(run_id, None)
 
     # ------------------------------------------------------------------
     # BasePlatformAdapter interface
@@ -2637,7 +2510,6 @@ class APIServerAdapter(BasePlatformAdapter):
             # Structured event streaming
             self._app.router.add_post("/v1/runs", self._handle_runs)
             self._app.router.add_get("/v1/runs/{run_id}/events", self._handle_run_events)
-            self._app.router.add_post("/v1/runs/{run_id}/stop", self._handle_stop_run)
             # Start background sweep to clean up orphaned (unconsumed) run streams
             sweep_task = asyncio.create_task(self._sweep_orphaned_runs())
             try:

gateway/platforms/base.py

@@ -148,102 +148,7 @@ def _detect_macos_system_proxy() -> str | None:
     return None
 
 
-def _split_host_port(value: str) -> tuple[str, int | None]:
-    raw = str(value or "").strip()
-    if not raw:
-        return "", None
-    if "://" in raw:
-        parsed = urlsplit(raw)
-        return (parsed.hostname or "").lower().rstrip("."), parsed.port
-    if raw.startswith("[") and "]" in raw:
-        host, _, rest = raw[1:].partition("]")
-        port = None
-        if rest.startswith(":") and rest[1:].isdigit():
-            port = int(rest[1:])
-        return host.lower().rstrip("."), port
-    if raw.count(":") == 1:
-        host, _, maybe_port = raw.rpartition(":")
-        if maybe_port.isdigit():
-            return host.lower().rstrip("."), int(maybe_port)
-    return raw.lower().strip("[]").rstrip("."), None
-
-
-def _no_proxy_entries() -> list[str]:
-    entries: list[str] = []
-    for key in ("NO_PROXY", "no_proxy"):
-        raw = os.environ.get(key, "")
-        entries.extend(part.strip() for part in raw.split(",") if part.strip())
-    return entries
-
-
-def _no_proxy_entry_matches(entry: str, host: str, port: int | None = None) -> bool:
-    token = str(entry or "").strip().lower()
-    if not token:
-        return False
-    if token == "*":
-        return True
-
-    token_host, token_port = _split_host_port(token)
-    if token_port is not None and port is not None and token_port != port:
-        return False
-    if token_port is not None and port is None:
-        return False
-    if not token_host:
-        return False
-
-    try:
-        network = ipaddress.ip_network(token_host, strict=False)
-        try:
-            return ipaddress.ip_address(host) in network
-        except ValueError:
-            return False
-    except ValueError:
-        pass
-
-    try:
-        token_ip = ipaddress.ip_address(token_host)
-        try:
-            return ipaddress.ip_address(host) == token_ip
-        except ValueError:
-            return False
-    except ValueError:
-        pass
-
-    if token_host.startswith("*."):
-        suffix = token_host[1:]
-        return host.endswith(suffix)
-    if token_host.startswith("."):
-        return host == token_host[1:] or host.endswith(token_host)
-    return host == token_host or host.endswith(f".{token_host}")
-
-
-def should_bypass_proxy(target_hosts: str | list[str] | tuple[str, ...] | set[str] | None) -> bool:
-    """Return True when NO_PROXY/no_proxy matches at least one target host.
-
-    Supports exact hosts, domain suffixes, wildcard suffixes, IP literals,
-    CIDR ranges, optional host:port entries, and ``*``.
-    """
-    entries = _no_proxy_entries()
-    if not entries or not target_hosts:
-        return False
-    if isinstance(target_hosts, str):
-        candidates = [target_hosts]
-    else:
-        candidates = list(target_hosts)
-    for candidate in candidates:
-        host, port = _split_host_port(str(candidate))
-        if not host:
-            continue
-        if any(_no_proxy_entry_matches(entry, host, port) for entry in entries):
-            return True
-    return False
-
-
-def resolve_proxy_url(
-    platform_env_var: str | None = None,
-    *,
-    target_hosts: str | list[str] | tuple[str, ...] | set[str] | None = None,
-) -> str | None:
+def resolve_proxy_url(platform_env_var: str | None = None) -> str | None:
     """Return a proxy URL from env vars, or macOS system proxy.
 
     Check order:
@@ -251,26 +156,18 @@ def resolve_proxy_url(
       1. HTTPS_PROXY / HTTP_PROXY / ALL_PROXY (and lowercase variants)
       2. macOS system proxy via ``scutil --proxy`` (auto-detect)
 
-    Returns *None* if no proxy is found, or if NO_PROXY/no_proxy matches one
-    of ``target_hosts``.
+    Returns *None* if no proxy is found.
     """
     if platform_env_var:
         value = (os.environ.get(platform_env_var) or "").strip()
         if value:
-            if should_bypass_proxy(target_hosts):
-                return None
             return normalize_proxy_url(value)
     for key in ("HTTPS_PROXY", "HTTP_PROXY", "ALL_PROXY",
                 "https_proxy", "http_proxy", "all_proxy"):
         value = (os.environ.get(key) or "").strip()
         if value:
-            if should_bypass_proxy(target_hosts):
-                return None
             return normalize_proxy_url(value)
-    detected = normalize_proxy_url(_detect_macos_system_proxy())
-    if detected and should_bypass_proxy(target_hosts):
-        return None
-    return detected
+    return normalize_proxy_url(_detect_macos_system_proxy())
 
 
 def proxy_kwargs_for_bot(proxy_url: str | None) -> dict:
@@ -1025,20 +922,7 @@ class BasePlatformAdapter(ABC):
         self._post_delivery_callbacks: Dict[str, Any] = {}
         self._expected_cancelled_tasks: set[asyncio.Task] = set()
         self._busy_session_handler: Optional[Callable[[MessageEvent, str], Awaitable[bool]]] = None
-        # Auto-TTS on voice input: ``_auto_tts_default`` is the global default
-        # (``voice.auto_tts`` in config.yaml, pushed by GatewayRunner on connect).
-        # Per-chat overrides live in two sets populated from ``_voice_mode``:
-        #   - ``_auto_tts_enabled_chats``: chat explicitly opted in via ``/voice on``
-        #     or ``/voice tts`` (mode is ``voice_only`` or ``all``). Fires even when
-        #     the global default is False.
-        #   - ``_auto_tts_disabled_chats``: chat explicitly opted out via
-        #     ``/voice off`` (mode is ``off``). Suppresses auto-TTS even when the
-        #     global default is True.
-        # The gate in _process_message() is:
-        #   fire if chat in _auto_tts_enabled_chats
-        #     OR (_auto_tts_default and chat not in _auto_tts_disabled_chats)
-        self._auto_tts_default: bool = False
-        self._auto_tts_enabled_chats: set = set()
+        # Chats where auto-TTS on voice input is disabled (set by /voice off)
         self._auto_tts_disabled_chats: set = set()
         # Chats where typing indicator is paused (e.g. during approval waits).
         # _keep_typing skips send_typing when the chat_id is in this set.
@@ -1060,21 +944,6 @@ class BasePlatformAdapter(ABC):
     def fatal_error_retryable(self) -> bool:
         return self._fatal_error_retryable
 
-    def _should_auto_tts_for_chat(self, chat_id: str) -> bool:
-        """Whether auto-TTS on voice input should fire for ``chat_id``.
-
-        Decision layers (Issue #16007):
-          1. Explicit ``/voice on`` or ``/voice tts`` → always fire (even if
-             ``voice.auto_tts`` is False).
-          2. Explicit ``/voice off`` → never fire.
-          3. Fall back to the global ``voice.auto_tts`` config default.
-        """
-        if chat_id in self._auto_tts_enabled_chats:
-            return True
-        if chat_id in self._auto_tts_disabled_chats:
-            return False
-        return bool(self._auto_tts_default)
-
     def set_fatal_error_handler(self, handler: Callable[["BasePlatformAdapter"], Awaitable[None] | None]) -> None:
         self._fatal_error_handler = handler
 
@@ -2242,14 +2111,12 @@ class BasePlatformAdapter(ABC):
                     logger.info("[%s] extract_local_files found %d file(s) in response", self.name, len(local_files))
                 
                 # Auto-TTS: if voice message, generate audio FIRST (before sending text)
-                # Gated via ``_should_auto_tts_for_chat``: fires when the chat has
-                # an explicit ``/voice on|tts`` opt-in OR when ``voice.auto_tts`` is
-                # True globally and no ``/voice off`` has been issued.
+                # Skipped when the chat has voice mode disabled (/voice off)
                 _tts_path = None
-                if (self._should_auto_tts_for_chat(event.source.chat_id)
-                        and event.message_type == MessageType.VOICE
+                if (event.message_type == MessageType.VOICE
                         and text_content
-                        and not media_files):
+                        and not media_files
+                        and event.source.chat_id not in self._auto_tts_disabled_chats):
                     try:
                         from tools.tts_tool import text_to_speech_tool, check_tts_requirements
                         if check_tts_requirements():
@@ -2573,9 +2440,6 @@ class BasePlatformAdapter(ABC):
         user_id_alt: Optional[str] = None,
         chat_id_alt: Optional[str] = None,
         is_bot: bool = False,
-        guild_id: Optional[str] = None,
-        parent_chat_id: Optional[str] = None,
-        message_id: Optional[str] = None,
     ) -> SessionSource:
         """Helper to build a SessionSource for this platform."""
         # Normalize empty topic to None
@@ -2593,9 +2457,6 @@ class BasePlatformAdapter(ABC):
             user_id_alt=user_id_alt,
             chat_id_alt=chat_id_alt,
             is_bot=is_bot,
-            guild_id=str(guild_id) if guild_id else None,
-            parent_chat_id=str(parent_chat_id) if parent_chat_id else None,
-            message_id=str(message_id) if message_id else None,
         )
     
     @abstractmethod

gateway/platforms/bluebubbles.py

@@ -99,7 +99,6 @@ def _normalize_server_url(raw: str) -> str:
 
 class BlueBubblesAdapter(BasePlatformAdapter):
     platform = Platform.BLUEBUBBLES
-    SUPPORTS_MESSAGE_EDITING = False
     MAX_MESSAGE_LENGTH = MAX_TEXT_LENGTH
 
     def __init__(self, config: PlatformConfig):
@@ -392,13 +391,6 @@ class BlueBubblesAdapter(BasePlatformAdapter):
     # Text sending
     # ------------------------------------------------------------------
 
-    @staticmethod
-    def truncate_message(content: str, max_length: int = MAX_TEXT_LENGTH) -> List[str]:
-        # Use the base splitter but skip pagination indicators — iMessage
-        # bubbles flow naturally without "(1/3)" suffixes.
-        chunks = BasePlatformAdapter.truncate_message(content, max_length)
-        return [re.sub(r"\s*\(\d+/\d+\)$", "", c) for c in chunks]
-
     async def send(
         self,
         chat_id: str,
@@ -406,19 +398,10 @@ class BlueBubblesAdapter(BasePlatformAdapter):
         reply_to: Optional[str] = None,
         metadata: Optional[Dict[str, Any]] = None,
     ) -> SendResult:
-        text = self.format_message(content)
+        text = strip_markdown(content or "")
         if not text:
             return SendResult(success=False, error="BlueBubbles send requires text")
-        # Split on paragraph breaks first (double newlines) so each thought
-        # becomes its own iMessage bubble, then truncate any that are still
-        # too long.
-        paragraphs = [p.strip() for p in re.split(r'\n\s*\n', text) if p.strip()]
-        chunks: List[str] = []
-        for para in (paragraphs or [text]):
-            if len(para) <= self.MAX_MESSAGE_LENGTH:
-                chunks.append(para)
-            else:
-                chunks.extend(self.truncate_message(para, max_length=self.MAX_MESSAGE_LENGTH))
+        chunks = self.truncate_message(text, max_length=self.MAX_MESSAGE_LENGTH)
         last = SendResult(success=True)
         for chunk in chunks:
             guid = await self._resolve_chat_guid(chat_id)

gateway/platforms/discord.py

@@ -2315,6 +2315,11 @@ class DiscordAdapter(BasePlatformAdapter):
         async def slash_background(interaction: discord.Interaction, prompt: str):
             await self._run_simple_slash(interaction, f"/background {prompt}", "Background task started~")
 
+        @tree.command(name="btw", description="Ephemeral side question using session context")
+        @discord.app_commands.describe(question="Your side question (no tools, not persisted)")
+        async def slash_btw(interaction: discord.Interaction, question: str):
+            await self._run_simple_slash(interaction, f"/btw {question}")
+
         # ── Auto-register any gateway-available commands not yet on the tree ──
         # This ensures new commands added to COMMAND_REGISTRY in
         # hermes_cli/commands.py automatically appear as Discord slash
@@ -3256,7 +3261,6 @@ class DiscordAdapter(BasePlatformAdapter):
             if auto_thread and not skip_thread and not is_voice_linked_channel and not is_reply_message:
                 thread = await self._auto_create_thread(message)
                 if thread:
-                    parent_channel_id = str(message.channel.id)
                     is_thread = True
                     thread_id = str(thread.id)
                     auto_threaded_channel = thread
@@ -3316,9 +3320,6 @@ class DiscordAdapter(BasePlatformAdapter):
             thread_id=thread_id,
             chat_topic=chat_topic,
             is_bot=getattr(message.author, "bot", False),
-            guild_id=str(message.guild.id) if message.guild else None,
-            parent_chat_id=parent_channel_id,
-            message_id=str(message.id),
         )
 
         # Build media URLs -- download image attachments to local cache so the

gateway/platforms/matrix.py

@@ -532,20 +532,6 @@ class MatrixAdapter(BasePlatformAdapter):
                 )
                 await crypto_store.open()
 
-                # Bind the store to the runtime device_id before any
-                # put_account() runs. PgCryptoStore defaults _device_id
-                # to "" and its crypto_account UPSERT never updates the
-                # device_id column on conflict — so once put_account
-                # writes blank, it stays blank forever. That breaks
-                # every downstream device-scoped olm operation: peer
-                # to-device ciphertext can't find our identity key and
-                # no megolm sessions ever land. Setting _device_id here
-                # (in-memory; the on-disk row may not exist yet) makes
-                # the first put_account write the correct value.
-                # DeviceID is a NewType(str) so plain str works at runtime.
-                if client.device_id:
-                    await crypto_store.put_device_id(client.device_id)
-
                 crypto_state = _CryptoStateStore(state_store, self._joined_rooms)
                 olm = OlmMachine(client, crypto_store, crypto_state)
 

gateway/platforms/telegram.py

@@ -703,6 +703,7 @@ class TelegramAdapter(BasePlatformAdapter):
                 "write_timeout": _env_float("HERMES_TELEGRAM_HTTP_WRITE_TIMEOUT", 20.0),
             }
 
+            proxy_url = resolve_proxy_url("TELEGRAM_PROXY")
             disable_fallback = (os.getenv("HERMES_TELEGRAM_DISABLE_FALLBACK_IPS", "").strip().lower() in ("1", "true", "yes", "on"))
             fallback_ips = self._fallback_ips()
             if not fallback_ips:
@@ -713,8 +714,6 @@ class TelegramAdapter(BasePlatformAdapter):
                     ", ".join(fallback_ips),
                 )
 
-            proxy_targets = ["api.telegram.org", *fallback_ips]
-            proxy_url = resolve_proxy_url("TELEGRAM_PROXY", target_hosts=proxy_targets)
             if fallback_ips and not proxy_url and not disable_fallback:
                 logger.info(
                     "[%s] Telegram fallback IPs active: %s",

gateway/platforms/telegram_network.py

@@ -43,10 +43,10 @@ _DOH_PROVIDERS: list[dict] = [
 _SEED_FALLBACK_IPS: list[str] = ["149.154.167.220"]
 
 
-def _resolve_proxy_url(target_hosts=None) -> str | None:
+def _resolve_proxy_url() -> str | None:
     # Delegate to shared implementation (env vars + macOS system proxy detection)
     from gateway.platforms.base import resolve_proxy_url
-    return resolve_proxy_url("TELEGRAM_PROXY", target_hosts=target_hosts)
+    return resolve_proxy_url("TELEGRAM_PROXY")
 
 
 class TelegramFallbackTransport(httpx.AsyncBaseTransport):
@@ -60,7 +60,7 @@ class TelegramFallbackTransport(httpx.AsyncBaseTransport):
 
     def __init__(self, fallback_ips: Iterable[str], **transport_kwargs):
         self._fallback_ips = [ip for ip in dict.fromkeys(_normalize_fallback_ips(fallback_ips))]
-        proxy_url = _resolve_proxy_url(target_hosts=[_TELEGRAM_API_HOST, *self._fallback_ips])
+        proxy_url = _resolve_proxy_url()
         if proxy_url and "proxy" not in transport_kwargs:
             transport_kwargs["proxy"] = proxy_url
         self._primary = httpx.AsyncHTTPTransport(**transport_kwargs)

gateway/session.py

@@ -60,10 +60,6 @@ from .config import (
     SessionResetPolicy,  # noqa: F401 — re-exported via gateway/__init__.py
     HomeChannel,
 )
-from .whatsapp_identity import (
-    canonical_whatsapp_identifier,
-    normalize_whatsapp_identifier,
-)
 
 
 @dataclass
@@ -87,9 +83,6 @@ class SessionSource:
     user_id_alt: Optional[str] = None  # Platform-specific stable alt ID (Signal UUID, Feishu union_id)
     chat_id_alt: Optional[str] = None  # Signal group internal ID
     is_bot: bool = False  # True when the message author is a bot/webhook (Discord)
-    guild_id: Optional[str] = None  # Discord guild / Slack workspace / Matrix server scope
-    parent_chat_id: Optional[str] = None  # Parent channel when chat_id refers to a thread
-    message_id: Optional[str] = None  # ID of the triggering message (for pin/reply/react)
     
     @property
     def description(self) -> str:
@@ -127,14 +120,8 @@ class SessionSource:
             d["user_id_alt"] = self.user_id_alt
         if self.chat_id_alt:
             d["chat_id_alt"] = self.chat_id_alt
-        if self.guild_id:
-            d["guild_id"] = self.guild_id
-        if self.parent_chat_id:
-            d["parent_chat_id"] = self.parent_chat_id
-        if self.message_id:
-            d["message_id"] = self.message_id
         return d
-
+    
     @classmethod
     def from_dict(cls, data: Dict[str, Any]) -> "SessionSource":
         return cls(
@@ -148,9 +135,6 @@ class SessionSource:
             chat_topic=data.get("chat_topic"),
             user_id_alt=data.get("user_id_alt"),
             chat_id_alt=data.get("chat_id_alt"),
-            guild_id=data.get("guild_id"),
-            parent_chat_id=data.get("parent_chat_id"),
-            message_id=data.get("message_id"),
         )
     
 
@@ -202,31 +186,6 @@ that requires raw IDs).  Discord is excluded because mentions use ``<@user_id>``
 and the LLM needs the real ID to tag users."""
 
 
-def _discord_tools_loaded() -> bool:
-    """True iff the agent will actually have Discord tools this session.
-
-    Two conditions must hold:
-      1. The `discord` or `discord_admin` toolset is enabled for the
-         Discord platform via `hermes tools` (opt-in, default OFF).
-      2. `DISCORD_BOT_TOKEN` is set — the tool's `check_fn` gates on it
-         at registry time, so the toolset being enabled in config is not
-         enough if the token isn't configured.
-
-    Returns False (safe default — keeps the stale-API disclaimer) on any
-    error so a bad config can't silently promise tools the agent lacks.
-    """
-    if not (os.environ.get("DISCORD_BOT_TOKEN") or "").strip():
-        return False
-    try:
-        from hermes_cli.config import load_config
-        from hermes_cli.tools_config import _get_platform_tools
-        cfg = load_config()
-        enabled = _get_platform_tools(cfg, "discord", include_default_mcp_servers=False)
-        return "discord" in enabled or "discord_admin" in enabled
-    except Exception:
-        return False
-
-
 def build_session_context_prompt(
     context: SessionContext,
     *,
@@ -314,44 +273,13 @@ def build_session_context_prompt(
             "that you can only read messages sent directly to you and respond."
         )
     elif context.source.platform == Platform.DISCORD:
-        # Inject the Discord IDs block only when the agent actually has
-        # Discord tools loaded this session — i.e. the user opted into
-        # `discord` / `discord_admin` via `hermes tools` AND the bot
-        # token is configured.  Otherwise keep the stale-API disclaimer
-        # honest so we never promise tools the agent lacks.
-        if _discord_tools_loaded():
-            src = context.source
-            id_lines = ["", "**Discord IDs (for the `discord` / `discord_admin` tools):**"]
-            if src.guild_id:
-                id_lines.append(f"  - Guild: `{src.guild_id}`")
-            if src.thread_id and src.parent_chat_id:
-                id_lines.append(f"  - Parent channel: `{src.parent_chat_id}`")
-                id_lines.append(f"  - Thread: `{src.thread_id}` (use as `channel_id` for fetch_messages etc.)")
-            else:
-                id_lines.append(f"  - Channel: `{src.chat_id}`")
-            if src.message_id:
-                id_lines.append(f"  - Triggering message: `{src.message_id}`")
-            lines.extend(id_lines)
-        else:
-            lines.append("")
-            lines.append(
-                "**Platform notes:** You are running inside Discord. "
-                "You do NOT have access to Discord-specific APIs — you cannot search "
-                "channel history, pin messages, manage roles, or list server members. "
-                "Do not promise to perform these actions. If the user asks, explain "
-                "that you can only read messages sent directly to you and respond."
-            )
-    elif context.source.platform == Platform.BLUEBUBBLES:
         lines.append("")
         lines.append(
-            "**Platform notes:** You are responding via iMessage. "
-            "Keep responses short and conversational — think texts, not essays. "
-            "Structure longer replies as separate short thoughts, each separated "
-            "by a blank line (double newline). Each block between blank lines "
-            "will be delivered as its own iMessage bubble, so write accordingly: "
-            "one idea per bubble, 1–3 sentences each. "
-            "If the user needs a detailed answer, give the short version first "
-            "and offer to elaborate."
+            "**Platform notes:** You are running inside Discord. "
+            "You do NOT have access to Discord-specific APIs — you cannot search "
+            "channel history, pin messages, manage roles, or list server members. "
+            "Do not promise to perform these actions. If the user asks, explain "
+            "that you can only read messages sent directly to you and respond."
         )
 
     # Connected platforms
@@ -439,11 +367,11 @@ class SessionEntry:
     auto_reset_reason: Optional[str] = None  # "idle" or "daily"
     reset_had_activity: bool = False  # whether the expired session had any messages
     
-    # Set by the background expiry watcher after it finalizes an expired
-    # session (invoking on_session_finalize hooks and evicting the cached
-    # agent).  Persisted to sessions.json so the flag survives gateway
-    # restarts — prevents redundant finalization runs.
-    expiry_finalized: bool = False
+    # Set by the background expiry watcher after it successfully flushes
+    # memories for this session.  Persisted to sessions.json so the flag
+    # survives gateway restarts (the old in-memory _pre_flushed_sessions
+    # set was lost on restart, causing redundant re-flushes).
+    memory_flushed: bool = False
 
     # When True the next call to get_or_create_session() will auto-reset
     # this session (create a new session_id) so the user starts fresh.
@@ -479,7 +407,7 @@ class SessionEntry:
             "last_prompt_tokens": self.last_prompt_tokens,
             "estimated_cost_usd": self.estimated_cost_usd,
             "cost_status": self.cost_status,
-            "expiry_finalized": self.expiry_finalized,
+            "memory_flushed": self.memory_flushed,
             "suspended": self.suspended,
             "resume_pending": self.resume_pending,
             "resume_reason": self.resume_reason,
@@ -531,7 +459,7 @@ class SessionEntry:
             last_prompt_tokens=data.get("last_prompt_tokens", 0),
             estimated_cost_usd=data.get("estimated_cost_usd", 0.0),
             cost_status=data.get("cost_status", "unknown"),
-            expiry_finalized=data.get("expiry_finalized", data.get("memory_flushed", False)),
+            memory_flushed=data.get("memory_flushed", False),
             suspended=data.get("suspended", False),
             resume_pending=data.get("resume_pending", False),
             resume_reason=data.get("resume_reason"),
@@ -590,24 +518,15 @@ def build_session_key(
     """
     platform = source.platform.value
     if source.chat_type == "dm":
-        dm_chat_id = source.chat_id
-        if source.platform == Platform.WHATSAPP:
-            dm_chat_id = canonical_whatsapp_identifier(source.chat_id)
-
-        if dm_chat_id:
+        if source.chat_id:
             if source.thread_id:
-                return f"agent:main:{platform}:dm:{dm_chat_id}:{source.thread_id}"
-            return f"agent:main:{platform}:dm:{dm_chat_id}"
+                return f"agent:main:{platform}:dm:{source.chat_id}:{source.thread_id}"
+            return f"agent:main:{platform}:dm:{source.chat_id}"
         if source.thread_id:
             return f"agent:main:{platform}:dm:{source.thread_id}"
         return f"agent:main:{platform}:dm"
 
     participant_id = source.user_id_alt or source.user_id
-    if participant_id and source.platform == Platform.WHATSAPP:
-        # Same JID/LID-flip bug as the DM case: without canonicalisation, a
-        # single group member gets two isolated per-user sessions when the
-        # bridge reshuffles alias forms.
-        participant_id = canonical_whatsapp_identifier(str(participant_id)) or participant_id
     key_parts = ["agent:main", platform, source.chat_type]
 
     if source.chat_id:
@@ -1232,7 +1151,6 @@ class SessionStore:
                     reasoning_content=message.get("reasoning_content") if message.get("role") == "assistant" else None,
                     reasoning_details=message.get("reasoning_details") if message.get("role") == "assistant" else None,
                     codex_reasoning_items=message.get("codex_reasoning_items") if message.get("role") == "assistant" else None,
-                    codex_message_items=message.get("codex_message_items") if message.get("role") == "assistant" else None,
                 )
             except Exception as e:
                 logger.debug("Session DB operation failed: %s", e)
@@ -1265,7 +1183,6 @@ class SessionStore:
                         reasoning_content=msg.get("reasoning_content") if role == "assistant" else None,
                         reasoning_details=msg.get("reasoning_details") if role == "assistant" else None,
                         codex_reasoning_items=msg.get("codex_reasoning_items") if role == "assistant" else None,
-                        codex_message_items=msg.get("codex_message_items") if role == "assistant" else None,
                     )
             except Exception as e:
                 logger.debug("Failed to rewrite transcript in DB: %s", e)

gateway/whatsapp_identity.py

@@ -1,135 +0,0 @@
-"""Shared helpers for canonicalising WhatsApp sender identity.
-
-WhatsApp's bridge can surface the same human under two different JID shapes
-within a single conversation:
-
-- LID form: ``999999999999999@lid``
-- Phone form: ``15551234567@s.whatsapp.net``
-
-Both the authorisation path (:mod:`gateway.run`) and the session-key path
-(:mod:`gateway.session`) need to collapse these aliases to a single stable
-identity. This module is the single source of truth for that resolution so
-the two paths can never drift apart.
-
-Public helpers:
-
-- :func:`normalize_whatsapp_identifier` — strip JID/LID/device/plus syntax
-  down to the bare numeric identifier.
-- :func:`canonical_whatsapp_identifier` — walk the bridge's
-  ``lid-mapping-*.json`` files and return a stable canonical identity
-  across phone/LID variants.
-- :func:`expand_whatsapp_aliases` — return the full alias set for an
-  identifier. Used by authorisation code that needs to match any known
-  form of a sender against an allow-list.
-
-Plugins that need per-sender behaviour on WhatsApp (role-based routing,
-per-contact authorisation, policy gating in a gateway hook) should use
-``canonical_whatsapp_identifier`` so their bookkeeping lines up with
-Hermes' own session keys.
-"""
-
-from __future__ import annotations
-
-import json
-from typing import Set
-
-from hermes_constants import get_hermes_home
-
-
-def normalize_whatsapp_identifier(value: str) -> str:
-    """Strip WhatsApp JID/LID syntax down to its stable numeric identifier.
-
-    Accepts any of the identifier shapes the WhatsApp bridge may emit:
-    ``"60123456789@s.whatsapp.net"``, ``"60123456789:47@s.whatsapp.net"``,
-    ``"60123456789@lid"``, or a bare ``"+601****6789"`` / ``"60123456789"``.
-    Returns just the numeric identifier (``"60123456789"``) suitable for
-    equality comparisons.
-
-    Useful for plugins that want to match sender IDs against
-    user-supplied config (phone numbers in ``config.yaml``) without
-    worrying about which variant the bridge happens to deliver.
-    """
-    return (
-        str(value or "")
-        .strip()
-        .replace("+", "", 1)
-        .split(":", 1)[0]
-        .split("@", 1)[0]
-    )
-
-
-def expand_whatsapp_aliases(identifier: str) -> Set[str]:
-    """Resolve WhatsApp phone/LID aliases via bridge session mapping files.
-
-    Returns the set of all identifiers transitively reachable through the
-    bridge's ``$HERMES_HOME/whatsapp/session/lid-mapping-*.json`` files,
-    starting from ``identifier``. The result always includes the
-    normalized input itself, so callers can safely ``in`` check against
-    the return value without a separate fallback branch.
-
-    Returns an empty set if ``identifier`` normalizes to empty.
-    """
-    normalized = normalize_whatsapp_identifier(identifier)
-    if not normalized:
-        return set()
-
-    session_dir = get_hermes_home() / "whatsapp" / "session"
-    resolved: Set[str] = set()
-    queue = [normalized]
-
-    while queue:
-        current = queue.pop(0)
-        if not current or current in resolved:
-            continue
-
-        resolved.add(current)
-        for suffix in ("", "_reverse"):
-            mapping_path = session_dir / f"lid-mapping-{current}{suffix}.json"
-            if not mapping_path.exists():
-                continue
-            try:
-                mapped = normalize_whatsapp_identifier(
-                    json.loads(mapping_path.read_text(encoding="utf-8"))
-                )
-            except Exception:
-                continue
-            if mapped and mapped not in resolved:
-                queue.append(mapped)
-
-    return resolved
-
-
-def canonical_whatsapp_identifier(identifier: str) -> str:
-    """Return a stable WhatsApp sender identity across phone-JID/LID variants.
-
-    WhatsApp may surface the same person under either a phone-format JID
-    (``60123456789@s.whatsapp.net``) or a LID (``1234567890@lid``). This
-    applies to a DM ``chat_id`` *and* to the ``participant_id`` of a
-    member inside a group chat — both represent a user identity, and the
-    bridge may flip between the two for the same human.
-
-    This helper reads the bridge's ``whatsapp/session/lid-mapping-*.json``
-    files, walks the mapping transitively, and picks the shortest
-    (numeric-preferred) alias as the canonical identity.
-    :func:`gateway.session.build_session_key` uses this for both WhatsApp
-    DM chat_ids and WhatsApp group participant_ids, so callers get the
-    same session-key identity Hermes itself uses.
-
-    Plugins that need per-sender behaviour (role-based routing,
-    authorisation, per-contact policy) should use this so their
-    bookkeeping lines up with Hermes' session bookkeeping even when
-    the bridge reshuffles aliases.
-
-    Returns an empty string if ``identifier`` normalizes to empty. If no
-    mapping files exist yet (fresh bridge install), returns the
-    normalized input unchanged.
-    """
-    normalized = normalize_whatsapp_identifier(identifier)
-    if not normalized:
-        return ""
-
-    # expand_whatsapp_aliases always includes `normalized` itself in the
-    # returned set, so the min() below degrades gracefully to `normalized`
-    # when no lid-mapping files are present.
-    aliases = expand_whatsapp_aliases(normalized)
-    return min(aliases, key=lambda candidate: (len(candidate), candidate))

hermes_cli/auth.py

@@ -356,14 +356,6 @@ PROVIDER_REGISTRY: Dict[str, ProviderConfig] = {
         api_key_env_vars=(),
         base_url_env_var="BEDROCK_BASE_URL",
     ),
-    "azure-foundry": ProviderConfig(
-        id="azure-foundry",
-        name="Azure Foundry",
-        auth_type="api_key",
-        inference_base_url="",  # User-provided endpoint
-        api_key_env_vars=("AZURE_FOUNDRY_API_KEY",),
-        base_url_env_var="AZURE_FOUNDRY_BASE_URL",
-    ),
 }
 
 
@@ -751,18 +743,7 @@ def _load_auth_store(auth_file: Optional[Path] = None) -> Dict[str, Any]:
 
     try:
         raw = json.loads(auth_file.read_text())
-    except Exception as exc:
-        corrupt_path = auth_file.with_suffix(".json.corrupt")
-        try:
-            import shutil
-            shutil.copy2(auth_file, corrupt_path)
-        except Exception:
-            pass
-        logger.warning(
-            "auth: failed to parse %s (%s) — starting with empty store. "
-            "Corrupt file preserved at %s",
-            auth_file, exc, corrupt_path,
-        )
+    except Exception:
         return {"version": AUTH_STORE_VERSION, "providers": {}}
 
     if isinstance(raw, dict) and (
@@ -4244,10 +4225,10 @@ def _login_nous(args, pconfig: ProviderConfig) -> None:
                 )
 
             from hermes_cli.models import (
-                get_curated_nous_model_ids, get_pricing_for_provider,
+                _PROVIDER_MODELS, get_pricing_for_provider,
                 check_nous_free_tier, partition_nous_models_by_tier,
             )
-            model_ids = get_curated_nous_model_ids()
+            model_ids = _PROVIDER_MODELS.get("nous", [])
 
             print()
             unavailable_models: list = []

hermes_cli/azure_detect.py

@@ -1,300 +0,0 @@
-"""Azure Foundry endpoint auto-detection.
-
-Inspect an Azure AI Foundry / Azure OpenAI endpoint to determine:
-  - API transport (OpenAI-style ``chat_completions`` vs
-    Anthropic-style ``anthropic_messages``)
-  - Available models (best effort — Azure does not expose a deployment
-    listing via the inference API key, but Azure OpenAI v1 endpoints
-    return the resource's model catalog via ``GET /models``)
-  - Context length for each discovered/entered model, via the existing
-    :func:`agent.model_metadata.get_model_context_length` resolver.
-
-Rationale:
-
-Azure has no pure-API-key deployment-listing endpoint — per Microsoft,
-deployment enumeration requires ARM management-plane auth.  Azure
-OpenAI v1 endpoints ``{resource}.openai.azure.com/openai/v1`` do return
-a ``/models`` list, but it reflects the resource's *available* models
-rather than the user's *deployed* deployment names.  In practice it is
-still a useful hint — the user picks a familiar model name and we look
-up its context length from the catalog.
-
-The detector never crashes on errors (every HTTP call is wrapped in a
-broad try/except).  Callers get a :class:`DetectionResult` with whatever
-information could be gathered, and fall back to manual entry for the
-rest.
-"""
-
-from __future__ import annotations
-
-import json
-import logging
-import re
-from dataclasses import dataclass, field
-from typing import Optional
-from urllib import request as urllib_request
-from urllib.error import HTTPError, URLError
-from urllib.parse import urlparse, urlunparse
-
-logger = logging.getLogger(__name__)
-
-
-# Default Azure OpenAI ``api-version`` to probe with.  The v1 GA endpoint
-# accepts requests without ``api-version`` entirely, so this is only used
-# as a fallback for pre-v1 resources that still require it.
-_AZURE_OPENAI_PROBE_API_VERSIONS = (
-    "2025-04-01-preview",
-    "2024-10-21",  # oldest GA that supports /models
-)
-
-# Default Azure Anthropic ``api-version``.  Matches the value used by
-# ``agent/anthropic_adapter.py`` when building the Anthropic client.
-_AZURE_ANTHROPIC_API_VERSION = "2025-04-15"
-
-
-@dataclass
-class DetectionResult:
-    """Everything auto-detection could gather from a base URL + API key."""
-
-    #: Detected API transport: ``"chat_completions"``,
-    #: ``"anthropic_messages"``, or ``None`` when detection failed.
-    api_mode: Optional[str] = None
-
-    #: Deployment / model IDs returned by ``/models`` (best effort).
-    #: Empty when the endpoint doesn't expose the list with an API key.
-    models: list[str] = field(default_factory=list)
-
-    #: Lowercased host from the base URL (used for display messages).
-    hostname: str = ""
-
-    #: Human-readable reason the detector chose ``api_mode``.  Useful
-    #: for explaining auto-detection to the user in the wizard.
-    reason: str = ""
-
-    #: ``True`` when ``/models`` returned a valid OpenAI-shaped payload.
-    models_probe_ok: bool = False
-
-    #: ``True`` when the URL was determined to be an Anthropic-style
-    #: endpoint (from path suffix or live probe).
-    is_anthropic: bool = False
-
-
-def _http_get_json(url: str, api_key: str, timeout: float = 6.0) -> tuple[int, Optional[dict]]:
-    """GET a URL with ``api-key`` + ``Authorization`` headers.  Return
-    ``(status_code, parsed_json_or_None)``.  Never raises."""
-    req = urllib_request.Request(url, method="GET")
-    # Azure OpenAI uses ``api-key``.  Some Azure deployments (and
-    # Anthropic-style routes) use ``Authorization: Bearer``.  Send both
-    # so we probe once per URL rather than twice.
-    req.add_header("api-key", api_key)
-    req.add_header("Authorization", f"Bearer {api_key}")
-    req.add_header("User-Agent", "hermes-agent/azure-detect")
-    try:
-        with urllib_request.urlopen(req, timeout=timeout) as resp:
-            body = resp.read()
-            try:
-                return resp.status, json.loads(body.decode("utf-8", errors="replace"))
-            except Exception:
-                return resp.status, None
-    except HTTPError as exc:
-        return exc.code, None
-    except (URLError, TimeoutError, OSError) as exc:
-        logger.debug("azure_detect: GET %s failed: %s", url, exc)
-        return 0, None
-    except Exception as exc:  # pragma: no cover — defensive
-        logger.debug("azure_detect: GET %s unexpected error: %s", url, exc)
-        return 0, None
-
-
-def _strip_trailing_v1(url: str) -> str:
-    """Strip trailing ``/v1`` or ``/v1/`` so we can construct sub-paths."""
-    return re.sub(r"/v1/?$", "", url.rstrip("/"))
-
-
-def _looks_like_anthropic_path(url: str) -> bool:
-    """Return True when the URL's path ends in ``/anthropic`` or
-    contains a ``/anthropic/`` segment.  Used by Azure Foundry
-    resources that route Claude traffic through a dedicated path."""
-    try:
-        parsed = urlparse(url)
-        path = (parsed.path or "").lower().rstrip("/")
-        return path.endswith("/anthropic") or "/anthropic/" in path + "/"
-    except Exception:
-        return False
-
-
-def _extract_model_ids(payload: dict) -> list[str]:
-    """Extract a list of model IDs from an OpenAI-shaped ``/models``
-    response.  Returns ``[]`` on any shape mismatch."""
-    data = payload.get("data") if isinstance(payload, dict) else None
-    if not isinstance(data, list):
-        return []
-    ids: list[str] = []
-    for item in data:
-        if not isinstance(item, dict):
-            continue
-        # OpenAI shape: {"id": "gpt-5.4", "object": "model", ...}
-        mid = item.get("id") or item.get("model") or item.get("name")
-        if isinstance(mid, str) and mid:
-            ids.append(mid)
-    return ids
-
-
-def _probe_openai_models(base_url: str, api_key: str) -> tuple[bool, list[str]]:
-    """Probe ``<base>/models`` for an OpenAI-shaped response.
-
-    Returns ``(ok, models)``.  ``ok`` is True iff the endpoint accepted
-    us as an OpenAI-style caller (200 OK + OpenAI-shaped JSON body).
-    """
-    base_url = base_url.rstrip("/")
-
-    # Azure OpenAI v1: {resource}.openai.azure.com/openai/v1 — no
-    # api-version required for GA paths, so probe without first.
-    candidates = [f"{base_url}/models"]
-    # Fallback: explicit api-version for pre-v1 resources
-    for v in _AZURE_OPENAI_PROBE_API_VERSIONS:
-        candidates.append(f"{base_url}/models?api-version={v}")
-
-    for url in candidates:
-        status, body = _http_get_json(url, api_key)
-        if status == 200 and body is not None:
-            ids = _extract_model_ids(body)
-            if ids:
-                logger.info(
-                    "azure_detect: /models probe OK at %s (%d models)",
-                    url, len(ids),
-                )
-                return True, ids
-            # 200 + empty list still counts as "OpenAI shape, no models
-            # listed" — let the user proceed with manual entry.
-            if isinstance(body, dict) and "data" in body:
-                return True, []
-    return False, []
-
-
-def _probe_anthropic_messages(base_url: str, api_key: str) -> bool:
-    """Send a zero-token request to ``<base>/v1/messages`` and check
-    whether the endpoint at least *recognises* the Anthropic Messages
-    shape (any 4xx that mentions ``messages`` or ``model``, or a 400
-    ``invalid_request`` with an Anthropic error shape).  Never completes
-    a real chat.
-    """
-    base = _strip_trailing_v1(base_url)
-    url = f"{base}/v1/messages?api-version={_AZURE_ANTHROPIC_API_VERSION}"
-    payload = json.dumps({
-        "model": "probe",
-        "max_tokens": 1,
-        "messages": [{"role": "user", "content": "ping"}],
-    }).encode("utf-8")
-    req = urllib_request.Request(url, method="POST", data=payload)
-    req.add_header("api-key", api_key)
-    req.add_header("Authorization", f"Bearer {api_key}")
-    req.add_header("anthropic-version", "2023-06-01")
-    req.add_header("content-type", "application/json")
-    req.add_header("User-Agent", "hermes-agent/azure-detect")
-    try:
-        with urllib_request.urlopen(req, timeout=6.0) as resp:
-            # Should never 200 — "probe" isn't a real deployment.  But
-            # if it does, the endpoint definitely speaks Anthropic.
-            return resp.status < 500
-    except HTTPError as exc:
-        # 4xx with an Anthropic-shaped error body = Anthropic endpoint.
-        try:
-            body = exc.read().decode("utf-8", errors="replace")
-            lowered = body.lower()
-            if "anthropic" in lowered or '"type"' in lowered and '"error"' in lowered:
-                return True
-            # Pre-Azure-v1 Azure Foundry returns a plain 404 for
-            # Anthropic-style calls on non-Anthropic deployments.  A
-            # 400 "model not found" IS Anthropic though.
-            if exc.code == 400 and ("messages" in lowered or "model" in lowered):
-                return True
-            return False
-        except Exception:
-            return False
-    except (URLError, TimeoutError, OSError):
-        return False
-    except Exception:  # pragma: no cover
-        return False
-
-
-def detect(base_url: str, api_key: str) -> DetectionResult:
-    """Inspect an Azure endpoint and describe its transport + models.
-
-    Call this from the wizard before asking the user to pick an API
-    mode manually.  The caller should treat the returned
-    :class:`DetectionResult` as *advisory* — if ``api_mode`` is None,
-    fall back to asking the user.
-    """
-    result = DetectionResult()
-
-    try:
-        parsed = urlparse(base_url)
-        result.hostname = (parsed.hostname or "").lower()
-    except Exception:
-        result.hostname = ""
-
-    # 1. Path sniff.  Azure Foundry exposes Anthropic-style deployments
-    #    under a dedicated ``/anthropic`` path.
-    if _looks_like_anthropic_path(base_url):
-        result.is_anthropic = True
-        result.api_mode = "anthropic_messages"
-        result.reason = "URL path ends in /anthropic → Anthropic Messages API"
-        return result
-
-    # 2. Try the OpenAI-style /models probe.  If this works, the
-    #    endpoint definitely speaks OpenAI wire.
-    ok, models = _probe_openai_models(base_url, api_key)
-    if ok:
-        result.models_probe_ok = True
-        result.models = models
-        result.api_mode = "chat_completions"
-        result.reason = (
-            f"GET /models returned {len(models)} model(s) — OpenAI-style endpoint"
-            if models
-            else "GET /models returned an OpenAI-shaped empty list — OpenAI-style endpoint"
-        )
-        return result
-
-    # 3. Fallback: probe the Anthropic Messages shape.  Slower and more
-    #    intrusive than /models, so only run it when the OpenAI probe
-    #    failed.
-    if _probe_anthropic_messages(base_url, api_key):
-        result.is_anthropic = True
-        result.api_mode = "anthropic_messages"
-        result.reason = "Endpoint accepts Anthropic Messages shape"
-        return result
-
-    # Nothing matched.  Caller falls back to manual selection.
-    result.reason = (
-        "Could not probe endpoint (private network, missing model list, or "
-        "non-standard path) — falling back to manual API-mode selection"
-    )
-    return result
-
-
-def lookup_context_length(model: str, base_url: str, api_key: str) -> Optional[int]:
-    """Thin wrapper around :func:`agent.model_metadata.get_model_context_length`
-    that returns ``None`` when only the fallback default (128k) would
-    fire, so the wizard can distinguish "we actually know this" from
-    "we guessed."""
-    try:
-        from agent.model_metadata import (
-            DEFAULT_FALLBACK_CONTEXT,
-            get_model_context_length,
-        )
-    except Exception:
-        return None
-
-    try:
-        n = get_model_context_length(model, base_url=base_url, api_key=api_key)
-    except Exception as exc:
-        logger.debug("azure_detect: context length lookup failed: %s", exc)
-        return None
-
-    if isinstance(n, int) and n > 0 and n != DEFAULT_FALLBACK_CONTEXT:
-        return n
-    return None
-
-
-__all__ = ["DetectionResult", "detect", "lookup_context_length"]

hermes_cli/commands.py

@@ -84,7 +84,9 @@ COMMAND_REGISTRY: list[CommandDef] = [
     CommandDef("deny", "Deny a pending dangerous command", "Session",
                gateway_only=True),
     CommandDef("background", "Run a prompt in the background", "Session",
-               aliases=("bg", "btw"), args_hint="<prompt>"),
+               aliases=("bg",), args_hint="<prompt>"),
+    CommandDef("btw", "Ephemeral side question using session context (no tools, not persisted)", "Session",
+               args_hint="<question>"),
     CommandDef("agents", "Show active agents and running tasks", "Session",
                aliases=("tasks",)),
     CommandDef("queue", "Queue a prompt for the next turn (doesn't interrupt)", "Session",
@@ -101,8 +103,7 @@ COMMAND_REGISTRY: list[CommandDef] = [
     # Configuration
     CommandDef("config", "Show current configuration", "Configuration",
                cli_only=True),
-    CommandDef("model", "Switch model for this session", "Configuration",
-               aliases=("provider",), args_hint="[model] [--provider name] [--global]"),
+    CommandDef("model", "Switch model for this session", "Configuration", args_hint="[model] [--provider name] [--global]"),
     CommandDef("gquota", "Show Google Gemini Code Assist quota usage", "Info",
                cli_only=True),
 
@@ -125,9 +126,6 @@ COMMAND_REGISTRY: list[CommandDef] = [
                cli_only=True, args_hint="[name]"),
     CommandDef("voice", "Toggle voice mode", "Configuration",
                args_hint="[on|off|tts|status]", subcommands=("on", "off", "tts", "status")),
-    CommandDef("busy", "Control what Enter does while Hermes is working", "Configuration",
-               cli_only=True, args_hint="[queue|interrupt|status]",
-               subcommands=("queue", "interrupt", "status")),
 
     # Tools & Skills
     CommandDef("tools", "Manage tools: /tools [list|disable|enable] [name...]", "Tools & Skills",
@@ -140,11 +138,6 @@ COMMAND_REGISTRY: list[CommandDef] = [
     CommandDef("cron", "Manage scheduled tasks", "Tools & Skills",
                cli_only=True, args_hint="[subcommand]",
                subcommands=("list", "add", "create", "edit", "pause", "resume", "run", "remove")),
-    CommandDef("kanban", "Multi-profile collaboration board (tasks, links, comments)",
-               "Tools & Skills", args_hint="[subcommand]",
-               subcommands=("list", "ls", "show", "create", "assign", "link", "unlink",
-                            "claim", "comment", "complete", "block", "unblock", "archive",
-                            "tail", "dispatch", "context", "init", "gc")),
     CommandDef("reload", "Reload .env variables into the running session", "Tools & Skills",
                cli_only=True),
     CommandDef("reload-mcp", "Reload MCP servers from config", "Tools & Skills",

hermes_cli/config.py

@@ -612,6 +612,14 @@ DEFAULT_CONFIG = {
             "timeout": 30,
             "extra_body": {},
         },
+        "flush_memories": {
+            "provider": "auto",
+            "model": "",
+            "base_url": "",
+            "api_key": "",
+            "timeout": 30,
+            "extra_body": {},
+        },
         "title_generation": {
             "provider": "auto",
             "model": "",
@@ -775,15 +783,6 @@ DEFAULT_CONFIG = {
         # warning log if out of range.
         "max_spawn_depth": 1,        # depth cap (1 = flat [default], 2 = orchestrator→leaf, 3 = three-level)
         "orchestrator_enabled": True,  # kill switch for role="orchestrator"
-        # When a subagent hits a dangerous-command approval prompt, the parent's
-        # prompt_toolkit TUI owns stdin — a thread-local input() call from the
-        # subagent worker would deadlock the parent UI. To avoid the deadlock,
-        # subagent threads ALWAYS resolve approvals non-interactively:
-        #   false (default) → auto-deny with a logger.warning audit line (safe)
-        #   true             → auto-approve "once" with a logger.warning audit line
-        # Flip to true only if you trust delegated work to run dangerous cmds
-        # without human review (cron pipelines, batch automation, etc.).
-        "subagent_auto_approve": False,
     },
 
     # Ephemeral prefill messages file — JSON list of {role, content} dicts
@@ -840,7 +839,7 @@ DEFAULT_CONFIG = {
         "auto_thread": True,           # Auto-create threads on @mention in channels (like Slack)
         "reactions": True,             # Add 👀/✅/❌ reactions to messages during processing
         "channel_prompts": {},         # Per-channel ephemeral system prompts (forum parents apply to child threads)
-        # discord / discord_admin tools: restrict which actions the agent may call.
+        # discord_server tool: restrict which actions the agent may call.
         # Default (empty) = all actions allowed (subject to bot privileged intents).
         # Accepts comma-separated string ("list_guilds,list_channels,fetch_messages")
         # or YAML list. Unknown names are dropped with a warning at load time.
@@ -959,27 +958,6 @@ DEFAULT_CONFIG = {
         "backup_count": 3,     # Number of rotated backup files to keep
     },
 
-    # Remotely-hosted model catalog manifest.  When enabled, the CLI fetches
-    # curated model lists for OpenRouter and Nous Portal from this URL,
-    # falling back to the in-repo snapshot on network failure.  Lets us
-    # update model picker lists without shipping a hermes-agent release.
-    # The default URL is served by the docs site GitHub Pages deploy.
-    "model_catalog": {
-        "enabled": True,
-        "url": "https://hermes-agent.nousresearch.com/docs/api/model-catalog.json",
-        # Disk cache TTL in hours.  Beyond this, the CLI refetches on the
-        # next /model or `hermes model` invocation; network failures
-        # silently fall back to the stale cache.
-        "ttl_hours": 24,
-        # Optional per-provider override URLs for third parties that want
-        # to self-host their own curation list using the same schema.
-        # Example:
-        #   providers:
-        #     openrouter:
-        #       url: https://example.com/my-curation.json
-        "providers": {},
-    },
-
     # Network settings — workarounds for connectivity issues.
     "network": {
         # Force IPv4 connections.  On servers with broken or unreachable IPv6,
@@ -1016,13 +994,6 @@ DEFAULT_CONFIG = {
         "min_interval_hours": 24,
     },
 
-    # Contextual first-touch onboarding hints (see agent/onboarding.py).
-    # Each hint is shown once per install and then latched here so it
-    # never fires again.  Users can wipe the section to re-see all hints.
-    "onboarding": {
-        "seen": {},
-    },
-
     # Config schema version - bump this when adding new required fields
     "_config_version": 22,
 }
@@ -1399,21 +1370,6 @@ OPTIONAL_ENV_VARS = {
         "category": "provider",
         "advanced": True,
     },
-    "AZURE_FOUNDRY_API_KEY": {
-        "description": "Azure Foundry API key for custom Azure endpoints",
-        "prompt": "Azure Foundry API Key",
-        "url": "https://ai.azure.com/",
-        "password": True,
-        "category": "provider",
-    },
-    "AZURE_FOUNDRY_BASE_URL": {
-        "description": "Azure Foundry base URL (set via 'hermes model' for endpoint-specific config)",
-        "prompt": "Azure Foundry base URL",
-        "url": None,
-        "password": False,
-        "category": "provider",
-        "advanced": True,
-    },
 
     # ── Tool API keys ──
     "EXA_API_KEY": {
@@ -2249,71 +2205,6 @@ def get_compatible_custom_providers(
     return compatible
 
 
-def get_custom_provider_context_length(
-    model: str,
-    base_url: str,
-    custom_providers: Optional[List[Dict[str, Any]]] = None,
-    config: Optional[Dict[str, Any]] = None,
-) -> Optional[int]:
-    """Look up a per-model ``context_length`` override from ``custom_providers``.
-
-    Matches any entry whose ``base_url`` equals ``base_url`` (trailing-slash
-    insensitive) and returns ``custom_providers[i].models.<model>.context_length``
-    if present and valid.  Returns ``None`` when no override applies.
-
-    This is the single source of truth for custom-provider context overrides,
-    used by:
-      * ``AIAgent.__init__`` (startup resolution)
-      * ``AIAgent.switch_model`` (mid-session ``/model`` switch)
-      * ``hermes_cli.model_switch.resolve_display_context_length`` (``/model`` confirmation display)
-      * ``gateway.run._format_session_info`` (``/info`` display)
-      * ``agent.model_metadata.get_model_context_length`` (when custom_providers is threaded through)
-
-    Before this helper existed, the lookup was duplicated in ``run_agent.py``'s
-    startup path only; every other path (notably ``/model`` switch) fell back
-    to the 128K default.  See #15779.
-    """
-    if not model or not base_url:
-        return None
-    if custom_providers is None:
-        try:
-            custom_providers = get_compatible_custom_providers(config)
-        except Exception:
-            if config is None:
-                return None
-            raw = config.get("custom_providers")
-            custom_providers = raw if isinstance(raw, list) else []
-    if not isinstance(custom_providers, list):
-        return None
-
-    target_url = (base_url or "").rstrip("/")
-    if not target_url:
-        return None
-
-    for entry in custom_providers:
-        if not isinstance(entry, dict):
-            continue
-        entry_url = (entry.get("base_url") or "").rstrip("/")
-        if not entry_url or entry_url != target_url:
-            continue
-        models = entry.get("models")
-        if not isinstance(models, dict):
-            continue
-        model_cfg = models.get(model)
-        if not isinstance(model_cfg, dict):
-            continue
-        raw_ctx = model_cfg.get("context_length")
-        if raw_ctx is None:
-            continue
-        try:
-            ctx = int(raw_ctx)
-        except (TypeError, ValueError):
-            continue
-        if ctx > 0:
-            return ctx
-    return None
-
-
 def check_config_version() -> Tuple[int, int]:
     """
     Check config version.

hermes_cli/doctor.py

@@ -320,11 +320,7 @@ def run_doctor(args):
                     known_providers.add("custom:" + name.lower().replace(" ", "-"))
 
             canonical_provider = provider
-            if (
-                provider
-                and _resolve_provider_full is not None
-                and provider not in ("auto", "custom")
-            ):
+            if provider and _resolve_provider_full is not None and provider != "auto":
                 provider_def = _resolve_provider_full(provider, user_providers, custom_providers)
                 canonical_provider = provider_def.id if provider_def is not None else None
 

hermes_cli/fallback_cmd.py

@@ -1,361 +0,0 @@
-"""
-hermes fallback — manage the fallback provider chain.
-
-Fallback providers are tried in order when the primary model fails with
-rate-limit, overload, or connection errors. See:
-https://hermes-agent.nousresearch.com/docs/user-guide/features/fallback-providers
-
-Subcommands:
-  hermes fallback [list]   Show the current fallback chain (default when no subcommand)
-  hermes fallback add      Pick provider + model via the same picker as `hermes model`,
-                           then append the selection to the chain
-  hermes fallback remove   Pick an entry to delete from the chain
-  hermes fallback clear    Remove all fallback entries
-
-Storage: ``fallback_providers`` in ``~/.hermes/config.yaml`` (top-level, list of
-``{provider, model, base_url?, api_mode?}`` dicts).  The legacy single-dict
-``fallback_model`` format is migrated to the new list format on first add.
-"""
-from __future__ import annotations
-
-import copy
-from typing import Any, Dict, List, Optional
-
-
-# ---------------------------------------------------------------------------
-# Helpers
-# ---------------------------------------------------------------------------
-
-def _read_chain(config: Dict[str, Any]) -> List[Dict[str, Any]]:
-    """Return the normalized fallback chain as a list of dicts.
-
-    Accepts both the new list format (``fallback_providers``) and the legacy
-    single-dict format (``fallback_model``).  The returned list is always a
-    fresh copy — callers can mutate without touching the config dict.
-    """
-    chain = config.get("fallback_providers") or []
-    if isinstance(chain, list):
-        result = [dict(e) for e in chain if isinstance(e, dict) and e.get("provider") and e.get("model")]
-        if result:
-            return result
-    legacy = config.get("fallback_model")
-    if isinstance(legacy, dict) and legacy.get("provider") and legacy.get("model"):
-        return [dict(legacy)]
-    if isinstance(legacy, list):
-        return [dict(e) for e in legacy if isinstance(e, dict) and e.get("provider") and e.get("model")]
-    return []
-
-
-def _write_chain(config: Dict[str, Any], chain: List[Dict[str, Any]]) -> None:
-    """Persist the chain to ``fallback_providers`` and clear legacy key."""
-    config["fallback_providers"] = chain
-    # Drop the legacy single-dict key on write so there's only one source of truth.
-    if "fallback_model" in config:
-        config.pop("fallback_model", None)
-
-
-def _format_entry(entry: Dict[str, Any]) -> str:
-    """One-line human-readable rendering of a fallback entry."""
-    provider = entry.get("provider", "?")
-    model = entry.get("model", "?")
-    base = entry.get("base_url")
-    suffix = f"  [{base}]" if base else ""
-    return f"{model}  (via {provider}){suffix}"
-
-
-def _extract_fallback_from_model_cfg(model_cfg: Any) -> Optional[Dict[str, Any]]:
-    """Pull the ``{provider, model, base_url?, api_mode?}`` dict from a ``config["model"]`` snapshot."""
-    if not isinstance(model_cfg, dict):
-        return None
-    provider = (model_cfg.get("provider") or "").strip()
-    # The picker writes the selected model to ``model.default``.
-    model = (model_cfg.get("default") or model_cfg.get("model") or "").strip()
-    if not provider or not model:
-        return None
-    entry: Dict[str, Any] = {"provider": provider, "model": model}
-    base_url = (model_cfg.get("base_url") or "").strip()
-    if base_url:
-        entry["base_url"] = base_url
-    api_mode = (model_cfg.get("api_mode") or "").strip()
-    if api_mode:
-        entry["api_mode"] = api_mode
-    return entry
-
-
-def _snapshot_auth_active_provider() -> Any:
-    """Return the current ``active_provider`` in auth.json, or a sentinel if unavailable."""
-    try:
-        from hermes_cli.auth import _load_auth_store
-        store = _load_auth_store()
-        return store.get("active_provider")
-    except Exception:
-        return None
-
-
-def _restore_auth_active_provider(value: Any) -> None:
-    """Write back a previously snapshotted ``active_provider`` value."""
-    try:
-        from hermes_cli.auth import _auth_store_lock, _load_auth_store, _save_auth_store
-        with _auth_store_lock():
-            store = _load_auth_store()
-            store["active_provider"] = value
-            _save_auth_store(store)
-    except Exception:
-        # Best-effort — if auth.json can't be restored, the user's primary
-        # provider may have been deactivated by the picker.  They can re-run
-        # `hermes model` to fix it.  Don't fail the fallback add.
-        pass
-
-
-# ---------------------------------------------------------------------------
-# Subcommand handlers
-# ---------------------------------------------------------------------------
-
-def cmd_fallback_list(args) -> None:  # noqa: ARG001
-    """Print the current fallback chain."""
-    from hermes_cli.config import load_config
-
-    config = load_config()
-    chain = _read_chain(config)
-
-    print()
-    if not chain:
-        print("  No fallback providers configured.")
-        print()
-        print("  Add one with:  hermes fallback add")
-        print()
-        return
-
-    primary = _describe_primary(config)
-    if primary:
-        print(f"  Primary:   {primary}")
-        print()
-    print(f"  Fallback chain ({len(chain)} {'entry' if len(chain) == 1 else 'entries'}):")
-    for i, entry in enumerate(chain, 1):
-        print(f"    {i}. {_format_entry(entry)}")
-    print()
-    print("  Tried in order when the primary fails (rate-limit, 5xx, connection errors).")
-    print("  Docs: https://hermes-agent.nousresearch.com/docs/user-guide/features/fallback-providers")
-    print()
-
-
-def _describe_primary(config: Dict[str, Any]) -> Optional[str]:
-    """One-line description of the primary model for display purposes."""
-    model_cfg = config.get("model")
-    if isinstance(model_cfg, dict):
-        provider = (model_cfg.get("provider") or "?").strip() or "?"
-        model = (model_cfg.get("default") or model_cfg.get("model") or "?").strip() or "?"
-        return f"{model}  (via {provider})"
-    if isinstance(model_cfg, str) and model_cfg.strip():
-        return model_cfg.strip()
-    return None
-
-
-def cmd_fallback_add(args) -> None:
-    """Launch the same picker as `hermes model`, then append the selection to the chain."""
-    from hermes_cli.main import _require_tty, select_provider_and_model
-    from hermes_cli.config import load_config, save_config
-
-    _require_tty("fallback add")
-
-    # Snapshot BEFORE the picker runs so we can distinguish "user actually
-    # picked something" from "user cancelled" by comparing before/after.
-    before_cfg = load_config()
-    model_before = copy.deepcopy(before_cfg.get("model"))
-    active_provider_before = _snapshot_auth_active_provider()
-
-    print()
-    print("  Adding a fallback provider.  The picker below is the same one used by")
-    print("  `hermes model` — select the provider + model you want as a fallback.")
-    print()
-
-    try:
-        select_provider_and_model(args=args)
-    except SystemExit:
-        # Some provider flows exit on auth failure — restore state and re-raise.
-        _restore_model_cfg(model_before)
-        _restore_auth_active_provider(active_provider_before)
-        raise
-
-    # Read the post-picker state to see what the user selected.
-    after_cfg = load_config()
-    model_after = after_cfg.get("model")
-
-    new_entry = _extract_fallback_from_model_cfg(model_after)
-    if not new_entry:
-        # Picker didn't complete (user cancelled or flow bailed).  Nothing to do.
-        _restore_model_cfg(model_before)
-        _restore_auth_active_provider(active_provider_before)
-        print()
-        print("  No fallback added.")
-        return
-
-    # Picker picked the same thing that's already the primary → nothing changed,
-    # and there's nothing useful to add as a fallback to itself.
-    primary_entry = _extract_fallback_from_model_cfg(model_before)
-    if primary_entry and primary_entry["provider"] == new_entry["provider"] \
-            and primary_entry["model"] == new_entry["model"]:
-        _restore_model_cfg(model_before)
-        _restore_auth_active_provider(active_provider_before)
-        print()
-        print(f"  Selected model matches the current primary ({_format_entry(new_entry)}).")
-        print("  A provider cannot be a fallback for itself — no change.")
-        return
-
-    # Reload the config with the primary restored, then append the new entry
-    # to ``fallback_providers``.  We deliberately re-load (rather than mutating
-    # ``after_cfg``) because the picker may have touched other top-level keys
-    # (custom_providers, providers credentials) that we want to keep.
-    _restore_model_cfg(model_before)
-    _restore_auth_active_provider(active_provider_before)
-
-    final_cfg = load_config()
-    chain = _read_chain(final_cfg)
-
-    # Reject exact-duplicate fallback entries.
-    for existing in chain:
-        if existing.get("provider") == new_entry["provider"] \
-                and existing.get("model") == new_entry["model"]:
-            print()
-            print(f"  {_format_entry(new_entry)} is already in the fallback chain — skipped.")
-            return
-
-    chain.append(new_entry)
-    _write_chain(final_cfg, chain)
-    save_config(final_cfg)
-
-    print()
-    print(f"  Added fallback: {_format_entry(new_entry)}")
-    print(f"  Chain is now {len(chain)} {'entry' if len(chain) == 1 else 'entries'} long.")
-    print()
-    print("  Run `hermes fallback list` to view, or `hermes fallback remove` to delete.")
-
-
-def _restore_model_cfg(model_before: Any) -> None:
-    """Restore ``config["model"]`` to a previously-captured snapshot."""
-    from hermes_cli.config import load_config, save_config
-
-    cfg = load_config()
-    if model_before is None:
-        cfg.pop("model", None)
-    else:
-        cfg["model"] = copy.deepcopy(model_before)
-    save_config(cfg)
-
-
-def cmd_fallback_remove(args) -> None:  # noqa: ARG001
-    """Pick an entry from the chain and remove it."""
-    from hermes_cli.config import load_config, save_config
-
-    config = load_config()
-    chain = _read_chain(config)
-
-    if not chain:
-        print()
-        print("  No fallback providers configured — nothing to remove.")
-        print()
-        return
-
-    choices = [_format_entry(e) for e in chain]
-    choices.append("Cancel")
-
-    try:
-        from hermes_cli.setup import _curses_prompt_choice
-        idx = _curses_prompt_choice("Select a fallback to remove:", choices, 0)
-    except Exception:
-        idx = _numbered_pick("Select a fallback to remove:", choices)
-
-    if idx is None or idx < 0 or idx >= len(chain):
-        print()
-        print("  Cancelled — no change.")
-        return
-
-    removed = chain.pop(idx)
-    _write_chain(config, chain)
-    save_config(config)
-
-    print()
-    print(f"  Removed fallback: {_format_entry(removed)}")
-    if chain:
-        print(f"  Chain is now {len(chain)} {'entry' if len(chain) == 1 else 'entries'} long.")
-    else:
-        print("  Fallback chain is now empty.")
-    print()
-
-
-def cmd_fallback_clear(args) -> None:  # noqa: ARG001
-    """Remove all fallback entries (with confirmation)."""
-    from hermes_cli.config import load_config, save_config
-
-    config = load_config()
-    chain = _read_chain(config)
-
-    if not chain:
-        print()
-        print("  No fallback providers configured — nothing to clear.")
-        print()
-        return
-
-    print()
-    print(f"  Current fallback chain ({len(chain)} {'entry' if len(chain) == 1 else 'entries'}):")
-    for i, entry in enumerate(chain, 1):
-        print(f"    {i}. {_format_entry(entry)}")
-    print()
-    try:
-        resp = input("  Clear all entries? [y/N]: ").strip().lower()
-    except (KeyboardInterrupt, EOFError):
-        print()
-        print("  Cancelled.")
-        return
-    if resp not in ("y", "yes"):
-        print("  Cancelled — no change.")
-        return
-
-    _write_chain(config, [])
-    save_config(config)
-    print()
-    print("  Fallback chain cleared.")
-    print()
-
-
-def _numbered_pick(question: str, choices: List[str]) -> Optional[int]:
-    """Fallback numbered-list picker when curses is unavailable."""
-    print(question)
-    for i, c in enumerate(choices, 1):
-        print(f"  {i}. {c}")
-    print()
-    while True:
-        try:
-            val = input(f"Choice [1-{len(choices)}]: ").strip()
-            if not val:
-                return None
-            idx = int(val) - 1
-            if 0 <= idx < len(choices):
-                return idx
-            print(f"Please enter 1-{len(choices)}")
-        except ValueError:
-            print("Please enter a number")
-        except (KeyboardInterrupt, EOFError):
-            print()
-            return None
-
-
-# ---------------------------------------------------------------------------
-# Dispatch
-# ---------------------------------------------------------------------------
-
-def cmd_fallback(args) -> None:
-    """Top-level dispatcher for ``hermes fallback [subcommand]``."""
-    sub = getattr(args, "fallback_command", None)
-    if sub in (None, "", "list", "ls"):
-        cmd_fallback_list(args)
-    elif sub == "add":
-        cmd_fallback_add(args)
-    elif sub in ("remove", "rm"):
-        cmd_fallback_remove(args)
-    elif sub == "clear":
-        cmd_fallback_clear(args)
-    else:
-        print(f"Unknown fallback subcommand: {sub}")
-        print("Use one of: list, add, remove, clear")
-        raise SystemExit(2)

hermes_cli/hooks.py

@@ -125,7 +125,6 @@ _DEFAULT_PAYLOADS = {
         "task_id": "test-task",
         "tool_call_id": "test-call",
         "result": '{"output": "hello"}',
-        "duration_ms": 42,
     },
     "pre_llm_call": {
         "session_id": "test-session",

hermes_cli/main.py

@@ -839,8 +839,6 @@ def _find_bundled_tui(tui_dir: Path) -> Optional[Path]:
 
 
 def _tui_build_needed(tui_dir: Path) -> bool:
-    if _hermes_ink_bundle_stale(tui_dir):
-        return True
     entry = tui_dir / "dist" / "entry.js"
     if not entry.exists():
         return True
@@ -1028,12 +1026,7 @@ def _make_tui_argv(tui_dir: Path, tui_dev: bool) -> tuple[list[str], Path]:
     return [node, str(root / "dist" / "entry.js")], root
 
 
-def _launch_tui(
-    resume_session_id: Optional[str] = None,
-    tui_dev: bool = False,
-    model: Optional[str] = None,
-    provider: Optional[str] = None,
-):
+def _launch_tui(resume_session_id: Optional[str] = None, tui_dev: bool = False):
     """Replace current process with the TUI."""
     tui_dir = PROJECT_ROOT / "ui-tui"
 
@@ -1043,12 +1036,6 @@ def _launch_tui(
     )
     env.setdefault("HERMES_PYTHON", sys.executable)
     env.setdefault("HERMES_CWD", os.getcwd())
-    if model:
-        env["HERMES_MODEL"] = model
-        env["HERMES_INFERENCE_MODEL"] = model
-    if provider:
-        env["HERMES_TUI_PROVIDER"] = provider
-        env["HERMES_INFERENCE_PROVIDER"] = provider
     # Guarantee an 8GB V8 heap + exposed GC for the TUI. Default node cap is
     # ~1.5–4GB depending on version and can fatal-OOM on long sessions with
     # large transcripts / reasoning blobs. Token-level merge: respect any
@@ -1187,8 +1174,6 @@ def cmd_chat(args):
         _launch_tui(
             getattr(args, "resume", None),
             tui_dev=getattr(args, "tui_dev", False),
-            model=getattr(args, "model", None),
-            provider=getattr(args, "provider", None),
         )
 
     # Import and run the CLI
@@ -1527,83 +1512,6 @@ def select_provider_and_model(args=None):
     all_providers = [(p.slug, p.tui_desc) for p in CANONICAL_PROVIDERS]
 
     def _named_custom_provider_map(cfg) -> dict[str, dict[str, str]]:
-        from hermes_cli.config import read_raw_config
-
-        # Build a lookup of raw (un-expanded) api_key templates keyed by a
-        # stable identity. We intentionally bypass
-        # ``get_compatible_custom_providers(read_raw_config())`` here because
-        # its ``_normalize_custom_provider_entry`` step calls ``urlparse()``
-        # on ``base_url`` and drops any entry whose ``base_url`` is itself an
-        # env-ref template (e.g. ``${NEURALWATT_API_BASE}``). Dropping those
-        # entries is exactly how env-ref preservation fails for the user
-        # config that motivated this fix.
-        raw_api_key_refs: dict[tuple, str] = {}
-        raw_cfg = read_raw_config()
-
-        def _record_raw(
-            name: str,
-            provider_key: str,
-            model: str,
-            api_key: str,
-        ) -> None:
-            template = str(api_key or "").strip()
-            if "${" not in template:
-                return
-            name = str(name or "").strip()
-            provider_key = str(provider_key or "").strip()
-            model = str(model or "").strip()
-            # Index by every plausible identity the loaded (expanded) config
-            # might present: (name), (name, model), (provider_key), and
-            # (provider_key, model). Case-insensitive on name/provider_key so
-            # the loaded entry matches regardless of display casing.
-            if name:
-                raw_api_key_refs.setdefault((name.lower(),), template)
-                raw_api_key_refs.setdefault((name.lower(), model), template)
-            if provider_key:
-                raw_api_key_refs.setdefault((provider_key.lower(),), template)
-                raw_api_key_refs.setdefault(
-                    (provider_key.lower(), model), template
-                )
-
-        raw_list = raw_cfg.get("custom_providers")
-        if isinstance(raw_list, list):
-            for raw_entry in raw_list:
-                if not isinstance(raw_entry, dict):
-                    continue
-                _record_raw(
-                    raw_entry.get("name", ""),
-                    "",
-                    raw_entry.get("model", "")
-                    or raw_entry.get("default_model", ""),
-                    raw_entry.get("api_key", ""),
-                )
-        raw_providers = raw_cfg.get("providers")
-        if isinstance(raw_providers, dict):
-            for raw_key, raw_entry in raw_providers.items():
-                if not isinstance(raw_entry, dict):
-                    continue
-                _record_raw(
-                    raw_entry.get("name", "") or raw_key,
-                    raw_key,
-                    raw_entry.get("model", "")
-                    or raw_entry.get("default_model", ""),
-                    raw_entry.get("api_key", ""),
-                )
-
-        def _lookup_ref(name: str, provider_key: str, model: str) -> str:
-            name_lc = str(name or "").strip().lower()
-            pkey_lc = str(provider_key or "").strip().lower()
-            model = str(model or "").strip()
-            for identity in (
-                (pkey_lc, model),
-                (pkey_lc,),
-                (name_lc, model),
-                (name_lc,),
-            ):
-                if identity[0] and identity in raw_api_key_refs:
-                    return raw_api_key_refs[identity]
-            return ""
-
         custom_provider_map = {}
         for entry in get_compatible_custom_providers(cfg):
             if not isinstance(entry, dict):
@@ -1627,9 +1535,6 @@ def select_provider_and_model(args=None):
                 "model": entry.get("model", ""),
                 "api_mode": entry.get("api_mode", ""),
                 "provider_key": provider_key,
-                "api_key_ref": _lookup_ref(
-                    name, provider_key, entry.get("model", "")
-                ),
             }
         return custom_provider_map
 
@@ -1719,8 +1624,6 @@ def select_provider_and_model(args=None):
         _model_flow_stepfun(config, current_model)
     elif selected_provider == "bedrock":
         _model_flow_bedrock(config, current_model)
-    elif selected_provider == "azure-foundry":
-        _model_flow_azure_foundry(config, current_model)
     elif selected_provider in (
         "gemini",
         "deepseek",
@@ -1804,6 +1707,7 @@ _AUX_TASKS: list[tuple[str, str, str]] = [
     ("session_search",   "Session search",   "past-conversation recall"),
     ("approval",         "Approval",         "smart command approval"),
     ("mcp",              "MCP",              "MCP tool reasoning"),
+    ("flush_memories",   "Flush memories",   "memory consolidation"),
     ("title_generation", "Title generation", "session titles"),
     ("skills_hub",       "Skills hub",       "skills search/install"),
 ]
@@ -2315,13 +2219,13 @@ def _model_flow_nous(config, current_model="", args=None):
     # The live /models endpoint returns hundreds of models; the curated list
     # shows only agentic models users recognize from OpenRouter.
     from hermes_cli.models import (
-        get_curated_nous_model_ids,
+        _PROVIDER_MODELS,
         get_pricing_for_provider,
         check_nous_free_tier,
         partition_nous_models_by_tier,
     )
 
-    model_ids = get_curated_nous_model_ids()
+    model_ids = _PROVIDER_MODELS.get("nous", [])
     if not model_ids:
         print("No curated models available for Nous Portal.")
         return
@@ -2864,19 +2768,6 @@ def _auto_provider_name(base_url: str) -> str:
     return name
 
 
-def _custom_provider_api_key_config_value(provider_info, resolved_api_key=""):
-    """Return the value that should be persisted for a custom provider key."""
-    api_key_ref = str(provider_info.get("api_key_ref", "") or "").strip()
-    if api_key_ref:
-        return api_key_ref
-
-    key_env = str(provider_info.get("key_env", "") or "").strip()
-    if key_env and not str(provider_info.get("api_key", "") or "").strip():
-        return f"${{{key_env}}}"
-
-    return str(resolved_api_key or "").strip()
-
-
 def _save_custom_provider(
     base_url, api_key="", model="", context_length=None, name=None
 ):
@@ -2932,203 +2823,6 @@ def _save_custom_provider(
     print(f'  💾 Saved to custom providers as "{name}" (edit in config.yaml)')
 
 
-def _model_flow_azure_foundry(config, current_model=""):
-    """Azure Foundry provider: configure endpoint, API mode, API key, and model.
-
-    Azure Foundry supports both OpenAI-style (``/v1/chat/completions``) and
-    Anthropic-style (``/v1/messages``) endpoints.  The wizard auto-detects
-    the transport and available models when possible:
-
-    * URLs ending in ``/anthropic`` → Anthropic Messages API.
-    * Successful ``GET <base>/models`` probe → OpenAI-style + populates
-      a picker with the returned deployment / model IDs.
-    * Anthropic Messages probe fallback when ``/models`` fails.
-    * Manual entry when every probe fails (private endpoints, etc.).
-
-    Context lengths for the chosen model are resolved via the standard
-    :func:`agent.model_metadata.get_model_context_length` chain
-    (models.dev, provider metadata, hardcoded family fallbacks).
-    """
-    from hermes_cli.auth import _save_model_choice, deactivate_provider  # noqa: F401
-    from hermes_cli.config import get_env_value, save_env_value, load_config, save_config
-    from hermes_cli import azure_detect
-    import getpass
-
-    # ── Load current Azure Foundry configuration ─────────────────────
-    model_cfg = config.get("model", {})
-    if isinstance(model_cfg, dict) and model_cfg.get("provider") == "azure-foundry":
-        current_base_url = str(model_cfg.get("base_url", "") or "")
-        current_api_mode = str(model_cfg.get("api_mode", "") or "")
-    else:
-        current_base_url = ""
-        current_api_mode = ""
-
-    current_api_key = get_env_value("AZURE_FOUNDRY_API_KEY") or ""
-
-    print()
-    print("Azure Foundry Configuration")
-    print("=" * 50)
-    print()
-    print("Azure Foundry can host models with either OpenAI-style or")
-    print("Anthropic-style API endpoints.  Hermes will probe your")
-    print("endpoint to auto-detect the transport and the deployed")
-    print("models when possible.")
-    print()
-
-    if current_base_url:
-        print(f"  Current endpoint: {current_base_url}")
-    if current_api_mode:
-        _lbl = "OpenAI-style" if current_api_mode == "chat_completions" else "Anthropic-style"
-        print(f"  Current API mode: {_lbl}")
-    if current_api_key:
-        print(f"  Current API key:  {current_api_key[:8]}...")
-    print()
-
-    # ── Step 1: endpoint URL ─────────────────────────────────────────
-    try:
-        base_url = input(
-            f"API endpoint URL [{current_base_url or 'e.g. https://your-resource.openai.azure.com/openai/v1'}]: "
-        ).strip()
-    except (KeyboardInterrupt, EOFError):
-        print("\nCancelled.")
-        return
-
-    effective_url = (base_url or current_base_url).rstrip("/")
-    if not effective_url:
-        print("No endpoint URL provided. Cancelled.")
-        return
-    if not effective_url.startswith(("http://", "https://")):
-        print(f"Invalid URL: {effective_url} (must start with http:// or https://)")
-        return
-
-    # ── Step 2: API key ──────────────────────────────────────────────
-    print()
-    try:
-        api_key = getpass.getpass(
-            f"API key [{current_api_key[:8] + '...' if current_api_key else 'required'}]: "
-        ).strip()
-    except (KeyboardInterrupt, EOFError):
-        print("\nCancelled.")
-        return
-
-    effective_key = api_key or current_api_key
-    if not effective_key:
-        print("No API key provided. Cancelled.")
-        return
-
-    # ── Step 3: auto-detect transport + models ───────────────────────
-    print()
-    print("◐ Probing endpoint to auto-detect transport and models...")
-    detection = azure_detect.detect(effective_url, effective_key)
-
-    discovered_models: list[str] = list(detection.models)
-    api_mode: str = detection.api_mode or ""
-
-    if api_mode:
-        mode_label = "OpenAI-style" if api_mode == "chat_completions" else "Anthropic-style"
-        print(f"✓ Detected API transport: {mode_label}")
-        if detection.reason:
-            print(f"    ({detection.reason})")
-        if discovered_models:
-            print(f"✓ Found {len(discovered_models)} deployed model(s) on this endpoint")
-    else:
-        print(f"⚠ Auto-detection incomplete: {detection.reason}")
-        print()
-        print("Select the API format your Azure Foundry endpoint uses:")
-        print("  1. OpenAI-style  (POST /v1/chat/completions)")
-        print("     For: GPT models, Llama, Mistral, and most open models")
-        print("  2. Anthropic-style  (POST /v1/messages)")
-        print("     For: Claude models deployed via Anthropic API format")
-        try:
-            default_choice = "2" if current_api_mode == "anthropic_messages" else "1"
-            mode_choice = input(f"API format [1/2] ({default_choice}): ").strip() or default_choice
-        except (KeyboardInterrupt, EOFError):
-            print("\nCancelled.")
-            return
-        api_mode = "anthropic_messages" if mode_choice == "2" else "chat_completions"
-
-    # ── Step 4: model name ───────────────────────────────────────────
-    print()
-    effective_model = ""
-    if discovered_models:
-        print("Available models on this endpoint:")
-        for i, mid in enumerate(discovered_models[:30], start=1):
-            print(f"  {i:>2}. {mid}")
-        if len(discovered_models) > 30:
-            print(f"  ... and {len(discovered_models) - 30} more (type name manually if not shown)")
-        print()
-        try:
-            pick = input(
-                f"Pick by number, or type a deployment name [{current_model or discovered_models[0]}]: "
-            ).strip()
-        except (KeyboardInterrupt, EOFError):
-            print("\nCancelled.")
-            return
-        if not pick:
-            effective_model = current_model or discovered_models[0]
-        elif pick.isdigit() and 1 <= int(pick) <= min(len(discovered_models), 30):
-            effective_model = discovered_models[int(pick) - 1]
-        else:
-            effective_model = pick
-    else:
-        try:
-            model_name = input(
-                f"Model / deployment name [{current_model or 'e.g. gpt-5.4, claude-sonnet-4-6'}]: "
-            ).strip()
-        except (KeyboardInterrupt, EOFError):
-            print("\nCancelled.")
-            return
-        effective_model = model_name or current_model
-
-    if not effective_model:
-        print("No model name provided. Cancelled.")
-        return
-
-    # ── Step 5: context-length lookup ────────────────────────────────
-    ctx_len = azure_detect.lookup_context_length(
-        effective_model, effective_url, effective_key,
-    )
-
-    # ── Step 6: persist ──────────────────────────────────────────────
-    save_env_value("AZURE_FOUNDRY_API_KEY", effective_key)
-
-    cfg = load_config()
-    model = cfg.get("model")
-    if not isinstance(model, dict):
-        model = {"default": model} if model else {}
-        cfg["model"] = model
-
-    model["provider"] = "azure-foundry"
-    model["base_url"] = effective_url
-    model["api_mode"] = api_mode
-    model["default"] = effective_model
-    if ctx_len:
-        model["context_length"] = ctx_len
-
-    save_config(cfg)
-    deactivate_provider()
-    config["model"] = dict(model)
-
-    # Clear any conflicting env vars so auxiliary clients don't poison
-    # themselves with a stale OpenAI base URL / key.
-    if get_env_value("OPENAI_BASE_URL"):
-        save_env_value("OPENAI_BASE_URL", "")
-    if get_env_value("OPENAI_API_KEY"):
-        save_env_value("OPENAI_API_KEY", "")
-
-    mode_label = "OpenAI-style" if api_mode == "chat_completions" else "Anthropic-style"
-    print()
-    print("✓ Azure Foundry configured:")
-    print(f"    Endpoint:       {effective_url}")
-    print(f"    API mode:       {mode_label}")
-    print(f"    Model:          {effective_model}")
-    if ctx_len:
-        print(f"    Context length: {ctx_len:,} tokens")
-    else:
-        print("    Context length: not auto-detected (will fall back at runtime)")
-    print()
-
-
 def _remove_custom_provider(config):
     """Let the user remove a saved custom provider from config.yaml."""
     from hermes_cli.config import load_config, save_config
@@ -3215,7 +2909,6 @@ def _model_flow_named_custom(config, provider_info):
     # Resolve key from env var if api_key not set directly
     if not api_key and key_env:
         api_key = os.environ.get(key_env, "")
-    config_api_key = _custom_provider_api_key_config_value(provider_info, api_key)
 
     print(f"  Provider: {name}")
     print(f"  URL:      {base_url}")
@@ -3312,8 +3005,8 @@ def _model_flow_named_custom(config, provider_info):
     else:
         model["provider"] = "custom"
         model["base_url"] = base_url
-        if config_api_key:
-            model["api_key"] = config_api_key
+        if api_key:
+            model["api_key"] = api_key
     # Apply api_mode from custom_providers entry, or clear stale value
     custom_api_mode = provider_info.get("api_mode", "")
     if custom_api_mode:
@@ -3331,15 +3024,15 @@ def _model_flow_named_custom(config, provider_info):
             provider_entry = providers_cfg.get(provider_key)
             if isinstance(provider_entry, dict):
                 provider_entry["default_model"] = model_name
-                if config_api_key and not str(provider_entry.get("api_key", "") or "").strip():
-                    provider_entry["api_key"] = config_api_key
+                if api_key and not str(provider_entry.get("api_key", "") or "").strip():
+                    provider_entry["api_key"] = api_key
                 if key_env and not str(provider_entry.get("key_env", "") or "").strip():
                     provider_entry["key_env"] = key_env
                 cfg["providers"] = providers_cfg
                 save_config(cfg)
     else:
         # Save model name to the custom_providers entry for next time
-        _save_custom_provider(base_url, config_api_key, model_name)
+        _save_custom_provider(base_url, api_key, model_name)
 
     print(f"\n✅ Model set to: {model_name}")
     print(f"   Provider: {name} ({base_url})")
@@ -4780,13 +4473,6 @@ def cmd_webhook(args):
     webhook_command(args)
 
 
-def cmd_kanban(args):
-    """Multi-profile collaboration board."""
-    from hermes_cli.kanban import kanban_command
-
-    return kanban_command(args)
-
-
 def cmd_hooks(args):
     """Shell-hook inspection and management."""
     from hermes_cli.hooks import hooks_command
@@ -5884,54 +5570,6 @@ def _finalize_update_output(state):
             pass
 
 
-def _cmd_update_check():
-    """Implement ``hermes update --check``: fetch and report without installing."""
-    git_dir = PROJECT_ROOT / ".git"
-    if not git_dir.exists():
-        print("✗ Not a git repository — cannot check for updates.")
-        sys.exit(1)
-
-    git_cmd = ["git"]
-    if sys.platform == "win32":
-        git_cmd = ["git", "-c", "windows.appendAtomically=false"]
-
-    print("→ Fetching from origin...")
-    fetch_result = subprocess.run(
-        git_cmd + ["fetch", "origin"],
-        cwd=PROJECT_ROOT,
-        capture_output=True,
-        text=True,
-    )
-    if fetch_result.returncode != 0:
-        stderr = fetch_result.stderr.strip()
-        if "Could not resolve host" in stderr or "unable to access" in stderr:
-            print("✗ Network error — cannot reach the remote repository.")
-        elif "Authentication failed" in stderr or "could not read Username" in stderr:
-            print("✗ Authentication failed — check your git credentials or SSH key.")
-        else:
-            print("✗ Failed to fetch from origin.")
-            if stderr:
-                print(f"  {stderr.splitlines()[0]}")
-        sys.exit(1)
-
-    rev_result = subprocess.run(
-        git_cmd + ["rev-list", "HEAD..origin/main", "--count"],
-        cwd=PROJECT_ROOT,
-        capture_output=True,
-        text=True,
-        check=True,
-    )
-    behind = int(rev_result.stdout.strip())
-
-    if behind == 0:
-        print("✓ Already up to date.")
-    else:
-        commits_word = "commit" if behind == 1 else "commits"
-        print(f"⚕ Update available: {behind} {commits_word} behind origin/main.")
-        from hermes_cli.config import recommended_update_command
-        print(f"  Run '{recommended_update_command()}' to install.")
-
-
 def cmd_update(args):
     """Update Hermes Agent to the latest version.
 
@@ -5945,10 +5583,6 @@ def cmd_update(args):
         managed_error("update Hermes Agent")
         return
 
-    if getattr(args, "check", False):
-        _cmd_update_check()
-        return
-
     gateway_mode = getattr(args, "gateway", False)
 
     # Protect against mid-update terminal disconnects (SIGHUP) and tolerate
@@ -6412,75 +6046,6 @@ def _cmd_update_impl(args, gateway_mode: bool):
             )
             import signal as _signal
 
-            def _wait_for_service_active(
-                scope_cmd_: list, svc_name_: str, timeout: float = 10.0,
-            ) -> bool:
-                """Poll ``systemctl is-active`` until the unit reports active.
-
-                systemd's Stopped -> Started transition after a graceful exit
-                (or a hard restart) is not instantaneous; a one-shot check
-                races that window and falsely reports the unit as down.
-                Poll every 0.5s up to ``timeout`` seconds before giving up.
-                """
-                deadline = _time.monotonic() + max(timeout, 0.5)
-                while True:
-                    try:
-                        _verify = subprocess.run(
-                            scope_cmd_ + ["is-active", svc_name_],
-                            capture_output=True, text=True, timeout=5,
-                        )
-                        if _verify.stdout.strip() == "active":
-                            return True
-                    except (FileNotFoundError, subprocess.TimeoutExpired):
-                        pass
-                    if _time.monotonic() >= deadline:
-                        return False
-                    _time.sleep(0.5)
-
-            def _service_restart_sec(
-                scope_cmd_: list, svc_name_: str, default: float = 0.0,
-            ) -> float:
-                """Read the unit's ``RestartUSec`` (RestartSec) in seconds.
-
-                After a graceful exit-75, systemd waits ``RestartSec`` before
-                respawning the unit.  Callers that poll for ``is-active``
-                must use a timeout >= ``RestartSec`` + transition slack, or
-                they'll give up *during* the cooldown window and wrongly
-                conclude the unit didn't relaunch.
-                """
-                try:
-                    _show = subprocess.run(
-                        scope_cmd_ + [
-                            "show", svc_name_,
-                            "--property=RestartUSec", "--value",
-                        ],
-                        capture_output=True, text=True, timeout=5,
-                    )
-                except (FileNotFoundError, subprocess.TimeoutExpired):
-                    return default
-                raw = (_show.stdout or "").strip()
-                # systemd emits values like "30s", "100ms", "1min 30s", or
-                # "infinity".  Parse conservatively; on any miss return default.
-                if not raw or raw == "infinity":
-                    return default
-                total = 0.0
-                matched = False
-                for part in raw.split():
-                    for _suf, _mult in (
-                        ("ms", 0.001),
-                        ("us", 0.000001),
-                        ("min", 60.0),
-                        ("s", 1.0),
-                    ):
-                        if part.endswith(_suf):
-                            try:
-                                total += float(part[: -len(_suf)]) * _mult
-                                matched = True
-                            except ValueError:
-                                pass
-                            break
-                return total if matched else default
-
             # Drain budget for graceful SIGUSR1 restarts.  The gateway drains
             # for up to ``agent.restart_drain_timeout`` (default 60s) before
             # exiting with code 75; we wait slightly longer so the drain
@@ -6587,23 +6152,14 @@ def _cmd_update_impl(args, gateway_mode: bool):
 
                             if _graceful_ok:
                                 # Gateway exited 75; systemd should relaunch
-                                # via Restart=on-failure.  The unit's
-                                # RestartSec (default 30s on ours) gates the
-                                # respawn — poll past that + slack so we
-                                # don't give up mid-cooldown and falsely
-                                # print "drained but didn't relaunch".  For
-                                # units without RestartSec set we fall back
-                                # to the original 10s budget.
-                                _restart_sec = _service_restart_sec(
-                                    scope_cmd, svc_name, default=0.0,
+                                # via Restart=on-failure.  Verify the new
+                                # process came up.
+                                _time.sleep(3)
+                                verify = subprocess.run(
+                                    scope_cmd + ["is-active", svc_name],
+                                    capture_output=True, text=True, timeout=5,
                                 )
-                                _post_drain_timeout = max(
-                                    10.0, _restart_sec + 10.0,
-                                )
-                                if _wait_for_service_active(
-                                    scope_cmd, svc_name,
-                                    timeout=_post_drain_timeout,
-                                ):
+                                if verify.stdout.strip() == "active":
                                     restarted_services.append(svc_name)
                                     continue
                                 # Process exited but wasn't respawned (older
@@ -6629,9 +6185,14 @@ def _cmd_update_impl(args, gateway_mode: bool):
                                 # Verify the service actually survived the
                                 # restart.  systemctl restart returns 0 even
                                 # if the new process crashes immediately.
-                                if _wait_for_service_active(
-                                    scope_cmd, svc_name, timeout=10.0,
-                                ):
+                                _time.sleep(3)
+                                verify = subprocess.run(
+                                    scope_cmd + ["is-active", svc_name],
+                                    capture_output=True,
+                                    text=True,
+                                    timeout=5,
+                                )
+                                if verify.stdout.strip() == "active":
                                     restarted_services.append(svc_name)
                                 else:
                                     # Retry once — transient startup failures
@@ -6646,9 +6207,14 @@ def _cmd_update_impl(args, gateway_mode: bool):
                                         text=True,
                                         timeout=15,
                                     )
-                                    if _wait_for_service_active(
-                                        scope_cmd, svc_name, timeout=10.0,
-                                    ):
+                                    _time.sleep(3)
+                                    verify2 = subprocess.run(
+                                        scope_cmd + ["is-active", svc_name],
+                                        capture_output=True,
+                                        text=True,
+                                        timeout=5,
+                                    )
+                                    if verify2.stdout.strip() == "active":
                                         restarted_services.append(svc_name)
                                         print(f"  ✓ {svc_name} recovered on retry")
                                     else:
@@ -7149,15 +6715,9 @@ def cmd_dashboard(args):
     try:
         import fastapi  # noqa: F401
         import uvicorn  # noqa: F401
-    except ImportError as e:
-        print("Web UI dependencies not installed (need fastapi + uvicorn).")
-        print(
-            f"Re-install the package into this interpreter so metadata updates apply:\n"
-            f"  cd {PROJECT_ROOT}\n"
-            f"  {sys.executable} -m pip install -e .\n"
-            "If `pip` is missing in this venv, use:  uv pip install -e ."
-        )
-        print(f"Import error: {e}")
+    except ImportError:
+        print("Web UI dependencies not installed.")
+        print(f"Install them with:  {sys.executable} -m pip install 'fastapi' 'uvicorn[standard]'")
         sys.exit(1)
 
     if "HERMES_WEB_DIST" not in os.environ:
@@ -7166,13 +6726,11 @@ def cmd_dashboard(args):
 
     from hermes_cli.web_server import start_server
 
-    embedded_chat = args.tui or os.environ.get("HERMES_DASHBOARD_TUI") == "1"
     start_server(
         host=args.host,
         port=args.port,
         open_browser=not args.no_open,
         allow_public=getattr(args, "insecure", False),
-        embedded_chat=embedded_chat,
     )
 
 
@@ -7230,9 +6788,6 @@ Examples:
     hermes auth remove <p> <t>    Remove pooled credential by index, id, or label
     hermes auth reset <provider>  Clear exhaustion status for a provider
     hermes model                  Select default model
-    hermes fallback [list]        Show fallback provider chain
-    hermes fallback add           Add a fallback provider (same picker as `hermes model`)
-    hermes fallback remove        Remove a fallback provider from the chain
     hermes config                 View configuration
     hermes config edit            Edit config in $EDITOR
     hermes config set model gpt-4 Set a config value
@@ -7258,40 +6813,6 @@ For more help on a command:
     parser.add_argument(
         "--version", "-V", action="store_true", help="Show version and exit"
     )
-    parser.add_argument(
-        "-z",
-        "--oneshot",
-        metavar="PROMPT",
-        default=None,
-        help=(
-            "One-shot mode: send a single prompt and print ONLY the final "
-            "response text to stdout. No banner, no spinner, no tool "
-            "previews, no session_id line. Tools, memory, rules, and "
-            "AGENTS.md in the CWD are loaded as normal; approvals are "
-            "auto-bypassed. Intended for scripts / pipes."
-        ),
-    )
-    # --model / --provider are accepted at the top level so they can pair
-    # with -z without needing the `chat` subcommand.  If neither -z nor a
-    # subcommand consumes them, they fall through harmlessly as None.
-    # Mirrors `hermes chat --model ... --provider ...` semantics.
-    parser.add_argument(
-        "-m",
-        "--model",
-        default=None,
-        help=(
-            "Model override for this invocation (e.g. anthropic/claude-sonnet-4.6). "
-            "Applies to -z/--oneshot and --tui. Also settable via HERMES_INFERENCE_MODEL env var."
-        ),
-    )
-    parser.add_argument(
-        "--provider",
-        default=None,
-        help=(
-            "Provider override for this invocation (e.g. openrouter, anthropic). "
-            "Applies to -z/--oneshot and --tui. Also settable via HERMES_INFERENCE_PROVIDER env var."
-        ),
-    )
     parser.add_argument(
         "--resume",
         "-r",
@@ -7574,42 +7095,6 @@ For more help on a command:
     )
     model_parser.set_defaults(func=cmd_model)
 
-    # =========================================================================
-    # fallback command — manage the fallback provider chain
-    # =========================================================================
-    from hermes_cli.fallback_cmd import cmd_fallback
-
-    fallback_parser = subparsers.add_parser(
-        "fallback",
-        help="Manage fallback providers (tried when the primary model fails)",
-        description=(
-            "Manage the fallback provider chain.  Fallback providers are tried "
-            "in order when the primary model fails with rate-limit, overload, or "
-            "connection errors.  See: "
-            "https://hermes-agent.nousresearch.com/docs/user-guide/features/fallback-providers"
-        ),
-    )
-    fallback_subparsers = fallback_parser.add_subparsers(dest="fallback_command")
-    fallback_subparsers.add_parser(
-        "list",
-        aliases=["ls"],
-        help="Show the current fallback chain (default when no subcommand)",
-    )
-    fallback_subparsers.add_parser(
-        "add",
-        help="Pick a provider + model (same picker as `hermes model`) and append to the chain",
-    )
-    fallback_subparsers.add_parser(
-        "remove",
-        aliases=["rm"],
-        help="Pick an entry to delete from the chain",
-    )
-    fallback_subparsers.add_parser(
-        "clear",
-        help="Remove all fallback entries",
-    )
-    fallback_parser.set_defaults(func=cmd_fallback)
-
     # =========================================================================
     # gateway command
     # =========================================================================
@@ -7780,19 +7265,6 @@ For more help on a command:
     setup_parser.add_argument(
         "--reset", action="store_true", help="Reset configuration to defaults"
     )
-    setup_parser.add_argument(
-        "--reconfigure",
-        action="store_true",
-        help="(Default on existing installs.) Re-run the full wizard, "
-             "showing current values as defaults. Kept for backwards "
-             "compatibility — a bare 'hermes setup' now does this.",
-    )
-    setup_parser.add_argument(
-        "--quick",
-        action="store_true",
-        help="On existing installs: only prompt for items that are missing "
-             "or unset, instead of running the full reconfigure wizard.",
-    )
     setup_parser.set_defaults(func=cmd_setup)
 
     # =========================================================================
@@ -8123,13 +7595,6 @@ For more help on a command:
 
     webhook_parser.set_defaults(func=cmd_webhook)
 
-    # =========================================================================
-    # kanban command — multi-profile collaboration board
-    # =========================================================================
-    from hermes_cli.kanban import build_parser as _build_kanban_parser
-    kanban_parser = _build_kanban_parser(subparsers)
-    kanban_parser.set_defaults(func=cmd_kanban)
-
     # =========================================================================
     # hooks command — shell-hook inspection and management
     # =========================================================================
@@ -9282,12 +8747,6 @@ Examples:
         default=False,
         help="Gateway mode: use file-based IPC for prompts instead of stdin (used internally by /update)",
     )
-    update_parser.add_argument(
-        "--check",
-        action="store_true",
-        default=False,
-        help="Check whether an update is available without installing anything",
-    )
     update_parser.set_defaults(func=cmd_update)
 
     # =========================================================================
@@ -9457,14 +8916,6 @@ Examples:
         action="store_true",
         help="Allow binding to non-localhost (DANGEROUS: exposes API keys on the network)",
     )
-    dashboard_parser.add_argument(
-        "--tui",
-        action="store_true",
-        help=(
-            "Expose the in-browser Chat tab (embedded `hermes --tui` via PTY/WebSocket). "
-            "Alternatively set HERMES_DASHBOARD_TUI=1."
-        ),
-    )
     dashboard_parser.set_defaults(func=cmd_dashboard)
 
     # =========================================================================
@@ -9634,17 +9085,6 @@ Examples:
                 exc_info=True,
             )
 
-    # Handle top-level --oneshot / -z: single-shot mode, stdout = final
-    # response only, nothing else. Bypasses cli.py entirely.
-    if getattr(args, "oneshot", None):
-        from hermes_cli.oneshot import run_oneshot
-
-        sys.exit(run_oneshot(
-            args.oneshot,
-            model=getattr(args, "model", None),
-            provider=getattr(args, "provider", None),
-        ))
-
     # Handle top-level --resume / --continue as shortcut to chat
     if (args.resume or args.continue_last) and args.command is None:
         args.command = "chat"

hermes_cli/model_catalog.py

@@ -1,329 +0,0 @@
-"""Remote model catalog fetcher.
-
-The Hermes docs site hosts a JSON manifest of curated models for providers
-we want to update without shipping a release (currently OpenRouter and
-Nous Portal). This module fetches, validates, and caches that manifest,
-falling back to the in-repo hardcoded lists when the network is unavailable.
-
-Pipeline
---------
-1. ``get_catalog()`` — returns a parsed manifest dict.
-   - Checks in-process cache (invalidated by TTL).
-   - Reads disk cache at ``~/.hermes/cache/model_catalog.json``.
-   - Fetches the master URL if disk cache is stale or missing.
-   - On any fetch failure, keeps using the stale cache (or empty dict).
-
-2. ``get_curated_openrouter_models()`` / ``get_curated_nous_models()`` —
-   thin accessors returning the shapes existing callers expect. Each
-   falls back to the in-repo hardcoded list on any lookup failure.
-
-Schema (version 1)
-------------------
-::
-
-    {
-      "version": 1,
-      "updated_at": "2026-04-25T22:00:00Z",
-      "metadata": {...},                # free-form
-      "providers": {
-        "openrouter": {
-          "metadata": {...},            # free-form
-          "models": [
-            {"id": "vendor/model", "description": "recommended",
-             "metadata": {...}}          # free-form, model-level
-          ]
-        },
-        "nous": {...}
-      }
-    }
-
-Unknown fields are ignored — extra metadata can be added at either level
-without bumping ``version``. ``version`` bumps are reserved for
-breaking changes (renaming ``providers``, changing ``models`` shape).
-"""
-
-from __future__ import annotations
-
-import json
-import logging
-import os
-import time
-import urllib.error
-import urllib.request
-from pathlib import Path
-from typing import Any
-
-from hermes_cli import __version__ as _HERMES_VERSION
-
-logger = logging.getLogger(__name__)
-
-# ---------------------------------------------------------------------------
-# Constants
-# ---------------------------------------------------------------------------
-
-DEFAULT_CATALOG_URL = (
-    "https://hermes-agent.nousresearch.com/docs/api/model-catalog.json"
-)
-DEFAULT_TTL_HOURS = 24
-DEFAULT_FETCH_TIMEOUT = 8.0
-SUPPORTED_SCHEMA_VERSION = 1
-
-_HERMES_USER_AGENT = f"hermes-cli/{_HERMES_VERSION}"
-
-# In-process cache to avoid repeated disk + parse work across multiple
-# calls within the same session. Invalidated by TTL against the disk file's
-# mtime, so calling code never has to think about this.
-_catalog_cache: dict[str, Any] | None = None
-_catalog_cache_source_mtime: float = 0.0
-
-
-# ---------------------------------------------------------------------------
-# Config
-# ---------------------------------------------------------------------------
-
-
-def _load_catalog_config() -> dict[str, Any]:
-    """Load the ``model_catalog`` config block with defaults filled in."""
-    try:
-        from hermes_cli.config import load_config
-        cfg = load_config() or {}
-    except Exception:
-        cfg = {}
-
-    raw = cfg.get("model_catalog")
-    if not isinstance(raw, dict):
-        raw = {}
-
-    return {
-        "enabled": bool(raw.get("enabled", True)),
-        "url": str(raw.get("url") or DEFAULT_CATALOG_URL),
-        "ttl_hours": float(raw.get("ttl_hours") or DEFAULT_TTL_HOURS),
-        "providers": raw.get("providers") if isinstance(raw.get("providers"), dict) else {},
-    }
-
-
-def _cache_path() -> Path:
-    """Return the disk cache path. Import lazily so tests can monkeypatch home."""
-    from hermes_constants import get_hermes_home
-    return get_hermes_home() / "cache" / "model_catalog.json"
-
-
-# ---------------------------------------------------------------------------
-# Fetch + validate + cache
-# ---------------------------------------------------------------------------
-
-
-def _fetch_manifest(url: str, timeout: float) -> dict[str, Any] | None:
-    """HTTP GET the manifest URL and return a parsed dict, or None on failure."""
-    try:
-        req = urllib.request.Request(
-            url,
-            headers={
-                "Accept": "application/json",
-                "User-Agent": _HERMES_USER_AGENT,
-            },
-        )
-        with urllib.request.urlopen(req, timeout=timeout) as resp:
-            data = json.loads(resp.read().decode())
-    except (urllib.error.URLError, TimeoutError, json.JSONDecodeError, OSError) as exc:
-        logger.info("model catalog fetch failed (%s): %s", url, exc)
-        return None
-    except Exception as exc:  # pragma: no cover — defensive
-        logger.info("model catalog fetch errored (%s): %s", url, exc)
-        return None
-
-    if not _validate_manifest(data):
-        logger.info("model catalog at %s failed schema validation", url)
-        return None
-
-    return data
-
-
-def _validate_manifest(data: Any) -> bool:
-    """Return True when ``data`` matches the minimum manifest shape."""
-    if not isinstance(data, dict):
-        return False
-    version = data.get("version")
-    if not isinstance(version, int) or version > SUPPORTED_SCHEMA_VERSION:
-        # Future schema version we don't understand — refuse rather than
-        # guess. Older schemas (version < 1) aren't supported either.
-        return False
-    providers = data.get("providers")
-    if not isinstance(providers, dict):
-        return False
-    for pname, pblock in providers.items():
-        if not isinstance(pname, str) or not isinstance(pblock, dict):
-            return False
-        models = pblock.get("models")
-        if not isinstance(models, list):
-            return False
-        for m in models:
-            if not isinstance(m, dict):
-                return False
-            if not isinstance(m.get("id"), str) or not m["id"].strip():
-                return False
-    return True
-
-
-def _read_disk_cache() -> tuple[dict[str, Any] | None, float]:
-    """Return ``(data_or_none, mtime)``. mtime is 0 if file is missing."""
-    path = _cache_path()
-    try:
-        mtime = path.stat().st_mtime
-    except (OSError, FileNotFoundError):
-        return (None, 0.0)
-    try:
-        with open(path) as fh:
-            data = json.load(fh)
-    except (OSError, json.JSONDecodeError):
-        return (None, 0.0)
-    if not _validate_manifest(data):
-        return (None, 0.0)
-    return (data, mtime)
-
-
-def _write_disk_cache(data: dict[str, Any]) -> None:
-    path = _cache_path()
-    try:
-        path.parent.mkdir(parents=True, exist_ok=True)
-        tmp = path.with_suffix(path.suffix + ".tmp")
-        with open(tmp, "w") as fh:
-            json.dump(data, fh, indent=2)
-            fh.write("\n")
-        os.replace(tmp, path)
-    except OSError as exc:
-        logger.info("model catalog cache write failed: %s", exc)
-
-
-# ---------------------------------------------------------------------------
-# Public API
-# ---------------------------------------------------------------------------
-
-
-def get_catalog(*, force_refresh: bool = False) -> dict[str, Any]:
-    """Return the parsed model catalog manifest, or an empty dict on failure.
-
-    Callers should treat a missing provider/model as "use the in-repo fallback"
-    — never raise from this function so the CLI keeps working offline.
-    """
-    global _catalog_cache, _catalog_cache_source_mtime
-
-    cfg = _load_catalog_config()
-    if not cfg["enabled"]:
-        return {}
-
-    ttl_seconds = max(0.0, cfg["ttl_hours"] * 3600.0)
-
-    disk_data, disk_mtime = _read_disk_cache()
-    now = time.time()
-    disk_fresh = disk_data is not None and (now - disk_mtime) < ttl_seconds
-
-    # In-process cache hit: disk hasn't changed since we loaded it and still fresh.
-    if (
-        not force_refresh
-        and _catalog_cache is not None
-        and disk_data is not None
-        and disk_mtime == _catalog_cache_source_mtime
-        and disk_fresh
-    ):
-        return _catalog_cache
-
-    # Disk is fresh enough — use it without a network hit.
-    if not force_refresh and disk_fresh and disk_data is not None:
-        _catalog_cache = disk_data
-        _catalog_cache_source_mtime = disk_mtime
-        return disk_data
-
-    # Need to (re)fetch. If it fails, fall back to any stale disk copy.
-    fetched = _fetch_manifest(cfg["url"], DEFAULT_FETCH_TIMEOUT)
-    if fetched is not None:
-        _write_disk_cache(fetched)
-        new_disk_data, new_mtime = _read_disk_cache()
-        if new_disk_data is not None:
-            _catalog_cache = new_disk_data
-            _catalog_cache_source_mtime = new_mtime
-            return new_disk_data
-        _catalog_cache = fetched
-        _catalog_cache_source_mtime = now
-        return fetched
-
-    if disk_data is not None:
-        _catalog_cache = disk_data
-        _catalog_cache_source_mtime = disk_mtime
-        return disk_data
-
-    return {}
-
-
-def _fetch_provider_override(provider: str) -> dict[str, Any] | None:
-    """If ``model_catalog.providers.<name>.url`` is set, fetch that instead."""
-    cfg = _load_catalog_config()
-    if not cfg["enabled"]:
-        return None
-    provider_cfg = cfg["providers"].get(provider)
-    if not isinstance(provider_cfg, dict):
-        return None
-    override_url = provider_cfg.get("url")
-    if not isinstance(override_url, str) or not override_url.strip():
-        return None
-    # Override fetches skip the disk cache because they're usually
-    # third-party self-hosted. Re-request on every call but with a short
-    # timeout so they don't block the picker.
-    return _fetch_manifest(override_url.strip(), DEFAULT_FETCH_TIMEOUT)
-
-
-def _get_provider_block(provider: str) -> dict[str, Any] | None:
-    """Return the provider's manifest block, respecting per-provider overrides."""
-    override = _fetch_provider_override(provider)
-    if override is not None:
-        block = override.get("providers", {}).get(provider)
-        if isinstance(block, dict):
-            return block
-
-    catalog = get_catalog()
-    if not catalog:
-        return None
-    block = catalog.get("providers", {}).get(provider)
-    return block if isinstance(block, dict) else None
-
-
-def get_curated_openrouter_models() -> list[tuple[str, str]] | None:
-    """Return OpenRouter's curated ``[(id, description), ...]`` from the manifest.
-
-    Returns ``None`` when the manifest is unavailable, so callers can fall
-    back to their hardcoded list.
-    """
-    block = _get_provider_block("openrouter")
-    if not block:
-        return None
-    out: list[tuple[str, str]] = []
-    for m in block.get("models", []):
-        mid = str(m.get("id") or "").strip()
-        if not mid:
-            continue
-        desc = str(m.get("description") or "")
-        out.append((mid, desc))
-    return out or None
-
-
-def get_curated_nous_models() -> list[str] | None:
-    """Return Nous Portal's curated list of model ids from the manifest.
-
-    Returns ``None`` when the manifest is unavailable.
-    """
-    block = _get_provider_block("nous")
-    if not block:
-        return None
-    out: list[str] = []
-    for m in block.get("models", []):
-        mid = str(m.get("id") or "").strip()
-        if mid:
-            out.append(mid)
-    return out or None
-
-
-def reset_cache() -> None:
-    """Clear the in-process cache. Used by tests and ``hermes model --refresh``."""
-    global _catalog_cache, _catalog_cache_source_mtime
-    _catalog_cache = None
-    _catalog_cache_source_mtime = 0.0

hermes_cli/model_switch.py

@@ -527,49 +527,6 @@ def _resolve_alias_fallback(
     return None
 
 
-def resolve_display_context_length(
-    model: str,
-    provider: str,
-    base_url: str = "",
-    api_key: str = "",
-    model_info: Optional[ModelInfo] = None,
-    custom_providers: list | None = None,
-) -> Optional[int]:
-    """Resolve the context length to show in /model output.
-
-    models.dev reports per-vendor context (e.g. gpt-5.5 = 1.05M on openai)
-    but provider-enforced limits can be lower (e.g. Codex OAuth caps the
-    same slug at 272k). The authoritative source is
-    ``agent.model_metadata.get_model_context_length`` which already knows
-    about Codex OAuth, Copilot, Nous, and falls back to models.dev for the
-    rest.
-
-    When ``custom_providers`` is provided, per-model ``context_length``
-    overrides from ``custom_providers[].models.<id>.context_length`` are
-    honored — this closes #15779 where ``/model`` switch ignored user-set
-    overrides.
-
-    Prefer the provider-aware value; fall back to ``model_info.context_window``
-    only if the resolver returns nothing.
-    """
-    try:
-        from agent.model_metadata import get_model_context_length
-        ctx = get_model_context_length(
-            model,
-            base_url=base_url or "",
-            api_key=api_key or "",
-            provider=provider or None,
-            custom_providers=custom_providers,
-        )
-        if ctx:
-            return int(ctx)
-    except Exception:
-        pass
-    if model_info is not None and model_info.context_window:
-        return int(model_info.context_window)
-    return None
-
-
 # ---------------------------------------------------------------------------
 # Core model-switching pipeline
 # ---------------------------------------------------------------------------
@@ -838,14 +795,9 @@ def switch_model(
                 requested=current_provider,
                 target_model=new_model,
             )
-            # If resolution fell through to "custom" (e.g. named custom provider like
-            # "ollama-launch" that resolve_runtime_provider doesn't know), keep existing
-            # credentials. Otherwise use the resolved values (picks up credential rotation,
-            # base_url adjustments for OpenCode, etc.).
-            if runtime.get("provider") != "custom":
-                api_key = runtime.get("api_key", "")
-                base_url = runtime.get("base_url", "")
-                api_mode = runtime.get("api_mode", "")
+            api_key = runtime.get("api_key", "")
+            base_url = runtime.get("base_url", "")
+            api_mode = runtime.get("api_mode", "")
         except Exception:
             pass
 
@@ -879,31 +831,16 @@ def switch_model(
             "message": f"Could not validate `{new_model}`: {e}",
         }
 
-    # Override rejection if model is in the user's saved provider config.
-    # API /v1/models may not list cloud/aliased models even though the server supports them.
     if not validation.get("accepted"):
-        override = False
-        if user_providers:
-            for up in user_providers:
-                if isinstance(up, dict) and up.get("provider") == target_provider:
-                    cfg_models = up.get("models", [])
-                    if new_model in cfg_models or any(
-                        m.get("name") == new_model for m in cfg_models if isinstance(m, dict)
-                    ):
-                        override = True
-                        break
-        if override:
-            validation = {"accepted": True, "persist": True, "recognized": False, "message": validation.get("message", "")}
-        else:
-            msg = validation.get("message", "Invalid model")
-            return ModelSwitchResult(
-                success=False,
-                new_model=new_model,
-                target_provider=target_provider,
-                provider_label=provider_label,
-                is_global=is_global,
-                error_message=msg,
-            )
+        msg = validation.get("message", "Invalid model")
+        return ModelSwitchResult(
+            success=False,
+            new_model=new_model,
+            target_provider=target_provider,
+            provider_label=provider_label,
+            is_global=is_global,
+            error_message=msg,
+        )
 
     # Apply auto-correction if validation found a closer match
     if validation.get("corrected_model"):

hermes_cli/models.py

@@ -42,7 +42,7 @@ OPENROUTER_MODELS: list[tuple[str, str]] = [
     ("anthropic/claude-sonnet-4.5",     ""),
     ("anthropic/claude-haiku-4.5",      ""),
     ("openrouter/elephant-alpha",       "free"),
-    ("openai/gpt-5.5",                  ""),
+    ("openai/gpt-5.4",                  ""),
     ("openai/gpt-5.4-mini",             ""),
     ("xiaomi/mimo-v2.5-pro",             ""),
     ("xiaomi/mimo-v2.5",                 ""),
@@ -65,7 +65,7 @@ OPENROUTER_MODELS: list[tuple[str, str]] = [
     ("nvidia/nemotron-3-super-120b-a12b:free", "free"),
     ("arcee-ai/trinity-large-preview:free", "free"),
     ("arcee-ai/trinity-large-thinking",  ""),
-    ("openai/gpt-5.5-pro",              ""),
+    ("openai/gpt-5.4-pro",              ""),
     ("openai/gpt-5.4-nano",             ""),
 ]
 
@@ -120,7 +120,7 @@ _PROVIDER_MODELS: dict[str, list[str]] = {
         "anthropic/claude-sonnet-4.6",
         "anthropic/claude-sonnet-4.5",
         "anthropic/claude-haiku-4.5",
-        "openai/gpt-5.5",
+        "openai/gpt-5.4",
         "openai/gpt-5.4-mini",
         "openai/gpt-5.3-codex",
         "google/gemini-3-pro-preview",
@@ -139,7 +139,7 @@ _PROVIDER_MODELS: dict[str, list[str]] = {
         "x-ai/grok-4.20-beta",
         "nvidia/nemotron-3-super-120b-a12b",
         "arcee-ai/trinity-large-thinking",
-        "openai/gpt-5.5-pro",
+        "openai/gpt-5.4-pro",
         "openai/gpt-5.4-nano",
     ],
     # Native OpenAI Chat Completions (api.openai.com). Used by /model counts and
@@ -383,9 +383,6 @@ _PROVIDER_MODELS: dict[str, list[str]] = {
         "us.meta.llama4-maverick-17b-instruct-v1:0",
         "us.meta.llama4-scout-17b-instruct-v1:0",
     ],
-    # Azure Foundry: user-provided endpoint and model.
-    # Empty list because models depend on the endpoint configuration.
-    "azure-foundry": [],
 }
 
 # Vercel AI Gateway: derive the bare-model-id catalog from the curated
@@ -743,7 +740,6 @@ CANONICAL_PROVIDERS: list[ProviderEntry] = [
     ProviderEntry("opencode-zen",   "OpenCode Zen",             "OpenCode Zen (35+ curated models, pay-as-you-go)"),
     ProviderEntry("opencode-go",    "OpenCode Go",              "OpenCode Go (open models, $10/month subscription)"),
     ProviderEntry("bedrock",        "AWS Bedrock",              "AWS Bedrock (Claude, Nova, Llama, DeepSeek — IAM or API key)"),
-    ProviderEntry("azure-foundry",  "Azure Foundry",            "Azure Foundry (OpenAI-style or Anthropic-style endpoint — your Azure AI deployment)"),
 ]
 
 # Derived dicts — used throughout the codebase
@@ -876,16 +872,7 @@ def fetch_openrouter_models(
     if _openrouter_catalog_cache is not None and not force_refresh:
         return list(_openrouter_catalog_cache)
 
-    # Prefer the remotely-hosted catalog manifest; fall back to the in-repo
-    # snapshot when the manifest is unreachable. Both are curated lists that
-    # drive the picker; the OpenRouter live /v1/models filter (tool support,
-    # free pricing) is applied on top either way.
-    try:
-        from hermes_cli.model_catalog import get_curated_openrouter_models
-        remote = get_curated_openrouter_models()
-    except Exception:
-        remote = None
-    fallback = list(remote) if remote else list(OPENROUTER_MODELS)
+    fallback = list(OPENROUTER_MODELS)
     preferred_ids = [mid for mid, _ in fallback]
 
     try:
@@ -938,24 +925,6 @@ def model_ids(*, force_refresh: bool = False) -> list[str]:
     return [mid for mid, _ in fetch_openrouter_models(force_refresh=force_refresh)]
 
 
-def get_curated_nous_model_ids() -> list[str]:
-    """Return the curated Nous Portal model-id list.
-
-    Prefers the remotely-hosted catalog manifest (published under
-    ``website/static/api/model-catalog.json``); falls back to the in-repo
-    snapshot in ``_PROVIDER_MODELS["nous"]`` when the manifest is
-    unreachable. Always returns a list (never None).
-    """
-    try:
-        from hermes_cli.model_catalog import get_curated_nous_models
-        remote = get_curated_nous_models()
-    except Exception:
-        remote = None
-    if remote:
-        return list(remote)
-    return list(_PROVIDER_MODELS.get("nous", []))
-
-
 def _ai_gateway_model_is_free(pricing: Any) -> bool:
     """Return True if an AI Gateway model has $0 input AND output pricing."""
     if not isinstance(pricing, dict):
@@ -1410,124 +1379,6 @@ def curated_models_for_provider(
     return [(m, "") for m in models]
 
 
-def _provider_keys(provider: str) -> set[str]:
-    key = (provider or "").strip().lower()
-    normalized = normalize_provider(provider)
-    return {k for k in (key, normalized) if k}
-
-
-def _model_in_provider_catalog(name_lower: str, providers: set[str]) -> bool:
-    return any(
-        name_lower == model.lower()
-        for provider in providers
-        for model in _PROVIDER_MODELS.get(provider, [])
-    )
-
-
-_AGGREGATOR_PROVIDERS = frozenset(
-    {"nous", "openrouter", "ai-gateway", "copilot", "kilocode"}
-)
-
-
-def _resolve_static_model_alias(
-    name_lower: str,
-    current_keys: set[str],
-) -> Optional[tuple[str, str]]:
-    """Resolve short aliases (e.g. sonnet/opus) using static catalogs only."""
-    try:
-        from hermes_cli.model_switch import MODEL_ALIASES
-    except Exception:
-        return None
-
-    identity = MODEL_ALIASES.get(name_lower)
-    if identity is None:
-        return None
-
-    vendor = identity.vendor
-    family = identity.family
-
-    def _match(provider: str) -> Optional[str]:
-        models = _PROVIDER_MODELS.get(provider, [])
-        if not models:
-            return None
-        prefix = (
-            f"{vendor}/{family}"
-            if provider in _AGGREGATOR_PROVIDERS
-            else family
-        ).lower()
-        for model in models:
-            if model.lower().startswith(prefix):
-                return model
-        return None
-
-    for provider in current_keys:
-        if matched := _match(provider):
-            return provider, matched
-
-    for provider in _PROVIDER_MODELS:
-        if provider in current_keys or provider in _AGGREGATOR_PROVIDERS:
-            continue
-        if matched := _match(provider):
-            return provider, matched
-
-    for provider in _AGGREGATOR_PROVIDERS:
-        if provider in current_keys and (matched := _match(provider)):
-            return provider, matched
-
-    return None
-
-
-def detect_static_provider_for_model(
-    model_name: str,
-    current_provider: str,
-) -> Optional[tuple[str, str]]:
-    """Auto-detect a provider from static catalogs only.
-
-    Returns ``(provider_id, model_name)``. The model name may be remapped
-    when a static alias or bare provider name resolves to a catalog default.
-    Returns ``None`` when no confident match is found.
-    """
-    name = (model_name or "").strip()
-    if not name:
-        return None
-
-    name_lower = name.lower()
-    current_keys = _provider_keys(current_provider)
-
-    alias_match = _resolve_static_model_alias(name_lower, current_keys)
-    if alias_match:
-        return alias_match
-
-    # --- Step 0: bare provider name typed as model ---
-    # If someone types `/model nous` or `/model anthropic`, treat it as a
-    # provider switch and pick the first model from that provider's catalog.
-    # Skip "custom" and "openrouter" — custom has no model catalog, and
-    # openrouter requires an explicit model name to be useful.
-    resolved_provider = _PROVIDER_ALIASES.get(name_lower, name_lower)
-    if resolved_provider not in {"custom", "openrouter"}:
-        default_models = _PROVIDER_MODELS.get(resolved_provider, [])
-        if (
-            resolved_provider in _PROVIDER_LABELS
-            and default_models
-            and resolved_provider not in current_keys
-        ):
-            return (resolved_provider, default_models[0])
-
-    # Aggregators list other providers' models — never auto-switch TO them
-    # If the model belongs to the current provider's catalog, don't suggest switching
-    if _model_in_provider_catalog(name_lower, current_keys):
-        return None
-
-    # --- Step 1: check static provider catalogs for a direct match ---
-    for pid, models in _PROVIDER_MODELS.items():
-        if pid in current_keys or pid in _AGGREGATOR_PROVIDERS:
-            continue
-        if any(name_lower == m.lower() for m in models):
-            return (pid, name)
-
-    return None
-
-
 def detect_provider_for_model(
     model_name: str,
     current_provider: str,
@@ -1540,19 +1391,86 @@ def detect_provider_for_model(
 
     Priority:
     0. Bare provider name → switch to that provider's default model
-    1. Direct provider static catalog match
-    2. OpenRouter catalog match
+    1. Direct provider with credentials (highest)
+    2. Direct provider without credentials → remap to OpenRouter slug
+    3. OpenRouter catalog match
     """
     name = (model_name or "").strip()
     if not name:
         return None
 
-    static_match = detect_static_provider_for_model(name, current_provider)
-    if static_match:
-        return static_match
-    if _model_in_provider_catalog(name.lower(), _provider_keys(current_provider)):
+    name_lower = name.lower()
+
+    # --- Step 0: bare provider name typed as model ---
+    # If someone types `/model nous` or `/model anthropic`, treat it as a
+    # provider switch and pick the first model from that provider's catalog.
+    # Skip "custom" and "openrouter" — custom has no model catalog, and
+    # openrouter requires an explicit model name to be useful.
+    resolved_provider = _PROVIDER_ALIASES.get(name_lower, name_lower)
+    if resolved_provider not in {"custom", "openrouter"}:
+        default_models = _PROVIDER_MODELS.get(resolved_provider, [])
+        if (
+            resolved_provider in _PROVIDER_LABELS
+            and default_models
+            and resolved_provider != normalize_provider(current_provider)
+        ):
+            return (resolved_provider, default_models[0])
+
+    # Aggregators list other providers' models — never auto-switch TO them
+    _AGGREGATORS = {"nous", "openrouter", "ai-gateway", "copilot", "kilocode"}
+
+    # If the model belongs to the current provider's catalog, don't suggest switching
+    current_models = _PROVIDER_MODELS.get(current_provider, [])
+    if any(name_lower == m.lower() for m in current_models):
         return None
 
+    # --- Step 1: check static provider catalogs for a direct match ---
+    direct_match: Optional[str] = None
+    for pid, models in _PROVIDER_MODELS.items():
+        if pid == current_provider or pid in _AGGREGATORS:
+            continue
+        if any(name_lower == m.lower() for m in models):
+            direct_match = pid
+            break
+
+    if direct_match:
+        # Check if we have credentials for this provider — env vars,
+        # credential pool, or auth store entries.
+        has_creds = False
+        try:
+            from hermes_cli.auth import PROVIDER_REGISTRY
+            pconfig = PROVIDER_REGISTRY.get(direct_match)
+            if pconfig:
+                for env_var in pconfig.api_key_env_vars:
+                    if os.getenv(env_var, "").strip():
+                        has_creds = True
+                        break
+        except Exception:
+            pass
+        # Also check credential pool and auth store — covers OAuth,
+        # Claude Code tokens, and other non-env-var credentials (#10300).
+        if not has_creds:
+            try:
+                from agent.credential_pool import load_pool
+                pool = load_pool(direct_match)
+                if pool.has_credentials():
+                    has_creds = True
+            except Exception:
+                pass
+        if not has_creds:
+            try:
+                from hermes_cli.auth import _load_auth_store
+                store = _load_auth_store()
+                if direct_match in store.get("providers", {}) or direct_match in store.get("credential_pool", {}):
+                    has_creds = True
+            except Exception:
+                pass
+
+        # Always return the direct provider match.  If credentials are
+        # missing, the client init will give a clear error rather than
+        # silently routing through the wrong provider (#10300).
+        return (direct_match, name)
+
     # --- Step 2: check OpenRouter catalog ---
     # First try exact match (handles provider/model format)
     or_slug = _find_openrouter_slug(name)
@@ -2653,8 +2571,8 @@ def validate_requested_model(
                 )
 
             return {
-                "accepted": True,
-                "persist": True,
+                "accepted": False,
+                "persist": False,
                 "recognized": False,
                 "message": message,
             }

hermes_cli/oneshot.py

@@ -1,202 +0,0 @@
-"""Oneshot (-z) mode: send a prompt, get the final content block, exit.
-
-Bypasses cli.py entirely.  No banner, no spinner, no session_id line,
-no stderr chatter.  Just the agent's final text to stdout.
-
-Toolsets = whatever the user has configured for "cli" in `hermes tools`.
-Rules / memory / AGENTS.md / preloaded skills = same as a normal chat turn.
-Approvals = auto-bypassed (HERMES_YOLO_MODE=1 is set for the call).
-Working directory = the user's CWD (AGENTS.md etc. resolve from there as usual).
-
-Model / provider selection mirrors `hermes chat`:
-    - Both optional. If omitted, use the user's configured default.
-    - If both given, pair them exactly as given.
-    - If only --model given, auto-detect the provider that serves it.
-    - If only --provider given, error out (ambiguous — caller must pick a model).
-
-Env var fallbacks (used when the corresponding arg is not passed):
-    - HERMES_INFERENCE_MODEL
-    - HERMES_INFERENCE_PROVIDER  (already read by resolve_runtime_provider)
-"""
-
-from __future__ import annotations
-
-import logging
-import os
-import sys
-from contextlib import redirect_stderr, redirect_stdout
-from typing import Optional
-
-
-def run_oneshot(
-    prompt: str,
-    model: Optional[str] = None,
-    provider: Optional[str] = None,
-) -> int:
-    """Execute a single prompt and print only the final content block.
-
-    Args:
-        prompt: The user message to send.
-        model: Optional model override. Falls back to HERMES_INFERENCE_MODEL
-            env var, then config.yaml's model.default / model.model.
-        provider: Optional provider override. Falls back to
-            HERMES_INFERENCE_PROVIDER env var, then config.yaml's model.provider,
-            then "auto".
-
-    Returns the exit code.  Caller should sys.exit() with the return.
-    """
-    # Silence every stdlib logger for the duration.  AIAgent, tools, and
-    # provider adapters all log to stderr through the root logger; file
-    # handlers added by setup_logging() keep working (they're attached to
-    # the root logger's handler list, not affected by level), but no
-    # bytes reach the terminal.
-    logging.disable(logging.CRITICAL)
-
-    # --provider without --model is ambiguous: carrying the user's configured
-    # model across to a different provider is usually wrong (that provider may
-    # not host it), and silently picking the provider's catalog default hides
-    # the mismatch.  Require the caller to be explicit.  Validate BEFORE the
-    # stderr redirect so the message actually reaches the terminal.
-    env_model_early = os.getenv("HERMES_INFERENCE_MODEL", "").strip()
-    if provider and not ((model or "").strip() or env_model_early):
-        sys.stderr.write(
-            "hermes -z: --provider requires --model (or HERMES_INFERENCE_MODEL). "
-            "Pass both explicitly, or neither to use your configured defaults.\n"
-        )
-        return 2
-
-    # Auto-approve any shell / tool approvals.  Non-interactive by
-    # definition — a prompt would hang forever.
-    os.environ["HERMES_YOLO_MODE"] = "1"
-    os.environ["HERMES_ACCEPT_HOOKS"] = "1"
-
-    # Redirect stderr AND stdout to devnull for the entire call tree.
-    # We'll print the final response to the real stdout at the end.
-    real_stdout = sys.stdout
-    devnull = open(os.devnull, "w")
-
-    try:
-        with redirect_stdout(devnull), redirect_stderr(devnull):
-            response = _run_agent(prompt, model=model, provider=provider)
-    finally:
-        try:
-            devnull.close()
-        except Exception:
-            pass
-
-    if response:
-        real_stdout.write(response)
-        if not response.endswith("\n"):
-            real_stdout.write("\n")
-        real_stdout.flush()
-    return 0
-
-
-def _run_agent(
-    prompt: str,
-    model: Optional[str] = None,
-    provider: Optional[str] = None,
-) -> str:
-    """Build an AIAgent exactly like a normal CLI chat turn would, then
-    run a single conversation.  Returns the final response string."""
-    # Imports are local so they don't run when hermes is invoked for
-    # other commands (keeps top-level CLI startup cheap).
-    from hermes_cli.config import load_config
-    from hermes_cli.models import detect_provider_for_model
-    from hermes_cli.runtime_provider import resolve_runtime_provider
-    from hermes_cli.tools_config import _get_platform_tools
-    from run_agent import AIAgent
-
-    cfg = load_config()
-
-    # Resolve effective model: explicit arg → env var → config.
-    model_cfg = cfg.get("model") or {}
-    if isinstance(model_cfg, str):
-        cfg_model = model_cfg
-    else:
-        cfg_model = model_cfg.get("default") or model_cfg.get("model") or ""
-
-    env_model = os.getenv("HERMES_INFERENCE_MODEL", "").strip()
-    effective_model = (model or "").strip() or env_model or cfg_model
-
-    # Resolve effective provider: explicit arg → (auto-detect from model if
-    # model was explicit) → env / config (handled inside resolve_runtime_provider).
-    #
-    # When --model is given without --provider, auto-detect the provider that
-    # serves that model — same semantic as `/model <name>` in an interactive
-    # session.  Without this, resolve_runtime_provider() would fall back to
-    # the user's configured default provider, which may not host the model
-    # the caller just asked for.
-    effective_provider = (provider or "").strip() or None
-    if effective_provider is None and (model or env_model):
-        # Only auto-detect when the model was explicitly requested via arg or
-        # env var (not when it came from config — that's the "use my defaults"
-        # path and the configured provider is already correct).
-        explicit_model = (model or "").strip() or env_model
-        if explicit_model:
-            cfg_provider = ""
-            if isinstance(model_cfg, dict):
-                cfg_provider = str(model_cfg.get("provider") or "").strip().lower()
-            current_provider = (
-                cfg_provider
-                or os.getenv("HERMES_INFERENCE_PROVIDER", "").strip().lower()
-                or "auto"
-            )
-            detected = detect_provider_for_model(explicit_model, current_provider)
-            if detected:
-                effective_provider, effective_model = detected
-
-    runtime = resolve_runtime_provider(
-        requested=effective_provider,
-        target_model=effective_model or None,
-    )
-
-    # Pull in whatever toolsets the user has enabled for "cli".
-    # sorted() gives stable ordering; set→list for AIAgent's signature.
-    toolsets_list = sorted(_get_platform_tools(cfg, "cli"))
-
-    agent = AIAgent(
-        api_key=runtime.get("api_key"),
-        base_url=runtime.get("base_url"),
-        provider=runtime.get("provider"),
-        api_mode=runtime.get("api_mode"),
-        model=effective_model,
-        enabled_toolsets=toolsets_list,
-        quiet_mode=True,
-        platform="cli",
-        credential_pool=runtime.get("credential_pool"),
-        # Interactive callbacks are intentionally NOT wired beyond this
-        # one.  In oneshot mode there's no user sitting at a terminal:
-        #   - clarify  → returns a synthetic "pick a default" instruction
-        #                so the agent continues instead of stalling on
-        #                the tool's built-in "not available" error
-        #   - sudo password prompt → terminal_tool gates on
-        #                HERMES_INTERACTIVE which we never set
-        #   - shell-hook approval → auto-approved via HERMES_ACCEPT_HOOKS=1
-        #                (set above); also falls back to deny on non-tty
-        #   - dangerous-command approval → bypassed via HERMES_YOLO_MODE=1
-        #   - skill secret capture → returns gracefully when no callback set
-        clarify_callback=_oneshot_clarify_callback,
-    )
-
-    # Belt-and-braces: make sure AIAgent doesn't invoke any streaming
-    # display callbacks that would bypass our stdout capture.
-    agent.suppress_status_output = True
-    agent.stream_delta_callback = None
-    agent.tool_gen_callback = None
-
-    return agent.chat(prompt) or ""
-
-
-def _oneshot_clarify_callback(question: str, choices=None) -> str:
-    """Clarify is disabled in oneshot mode — tell the agent to pick a
-    default and proceed instead of stalling or erroring."""
-    if choices:
-        return (
-            f"[oneshot mode: no user available. Pick the best option from "
-            f"{choices} using your own judgment and continue.]"
-        )
-    return (
-        "[oneshot mode: no user available. Make the most reasonable "
-        "assumption you can and continue.]"
-    )

hermes_cli/providers.py

@@ -167,12 +167,6 @@ HERMES_OVERLAYS: Dict[str, HermesOverlay] = {
         transport="openai_chat",
         base_url_env_var="OLLAMA_BASE_URL",
     ),
-    # Azure Foundry: supports both OpenAI-style and Anthropic-style endpoints.
-    # The transport is determined at runtime from config.yaml model.api_mode.
-    "azure-foundry": HermesOverlay(
-        transport="openai_chat",  # default; overridden by api_mode in config
-        base_url_env_var="AZURE_FOUNDRY_BASE_URL",
-    ),
 }
 
 

hermes_cli/pty_bridge.py

@@ -1,229 +0,0 @@
-"""PTY bridge for `hermes dashboard` chat tab.
-
-Wraps a child process behind a pseudo-terminal so its ANSI output can be
-streamed to a browser-side terminal emulator (xterm.js) and typed
-keystrokes can be fed back in.  The only caller today is the
-``/api/pty`` WebSocket endpoint in ``hermes_cli.web_server``.
-
-Design constraints:
-
-* **POSIX-only.**  Hermes Agent supports Windows exclusively via WSL, which
-  exposes a native POSIX PTY via ``openpty(3)``.  Native Windows Python
-  has no PTY; :class:`PtyUnavailableError` is raised with a user-readable
-  install/platform message so the dashboard can render a banner instead of
-  crashing.
-* **Zero Node dependency on the server side.**  We use :mod:`ptyprocess`,
-  which is a pure-Python wrapper around the OS calls.  The browser talks
-  to the same ``hermes --tui`` binary it would launch from the CLI, so
-  every TUI feature (slash popover, model picker, tool rows, markdown,
-  skin engine, clarify/sudo/approval prompts) ships automatically.
-* **Byte-safe I/O.**  Reads and writes go through the PTY master fd
-  directly — we avoid :class:`ptyprocess.PtyProcessUnicode` because
-  streaming ANSI is inherently byte-oriented and UTF-8 boundaries may land
-  mid-read.
-"""
-
-from __future__ import annotations
-
-import errno
-import fcntl
-import os
-import select
-import signal
-import struct
-import sys
-import termios
-import time
-from typing import Optional, Sequence
-
-try:
-    import ptyprocess  # type: ignore
-    _PTY_AVAILABLE = not sys.platform.startswith("win")
-except ImportError:  # pragma: no cover - dev env without ptyprocess
-    ptyprocess = None  # type: ignore
-    _PTY_AVAILABLE = False
-
-
-__all__ = ["PtyBridge", "PtyUnavailableError"]
-
-
-class PtyUnavailableError(RuntimeError):
-    """Raised when a PTY cannot be created on this platform.
-
-    Today this means native Windows (no ConPTY bindings) or a dev
-    environment missing the ``ptyprocess`` dependency.  The dashboard
-    surfaces the message to the user as a chat-tab banner.
-    """
-
-
-class PtyBridge:
-    """Thin wrapper around ``ptyprocess.PtyProcess`` for byte streaming.
-
-    Not thread-safe.  A single bridge is owned by the WebSocket handler
-    that spawned it; the reader runs in an executor thread while writes
-    happen on the event-loop thread.  Both sides are OK because the
-    kernel PTY is the actual synchronization point — we never call
-    :mod:`ptyprocess` methods concurrently, we only call ``os.read`` and
-    ``os.write`` on the master fd, which is safe.
-    """
-
-    def __init__(self, proc: "ptyprocess.PtyProcess"):  # type: ignore[name-defined]
-        self._proc = proc
-        self._fd: int = proc.fd
-        self._closed = False
-
-    # -- lifecycle --------------------------------------------------------
-
-    @classmethod
-    def is_available(cls) -> bool:
-        """True if a PTY can be spawned on this platform."""
-        return bool(_PTY_AVAILABLE)
-
-    @classmethod
-    def spawn(
-        cls,
-        argv: Sequence[str],
-        *,
-        cwd: Optional[str] = None,
-        env: Optional[dict] = None,
-        cols: int = 80,
-        rows: int = 24,
-    ) -> "PtyBridge":
-        """Spawn ``argv`` behind a new PTY and return a bridge.
-
-        Raises :class:`PtyUnavailableError` if the platform can't host a
-        PTY.  Raises :class:`FileNotFoundError` or :class:`OSError` for
-        ordinary exec failures (missing binary, bad cwd, etc.).
-        """
-        if not _PTY_AVAILABLE:
-            if sys.platform.startswith("win"):
-                raise PtyUnavailableError(
-                    "Pseudo-terminals are unavailable on this platform. "
-                    "Hermes Agent supports Windows only via WSL."
-                )
-            if ptyprocess is None:
-                raise PtyUnavailableError(
-                    "The `ptyprocess` package is missing. "
-                    "Install with: pip install ptyprocess "
-                    "(or pip install -e '.[pty]')."
-                )
-            raise PtyUnavailableError("Pseudo-terminals are unavailable.")
-        # Let caller-supplied env fully override inheritance; if they pass
-        # None we inherit the server's env (same semantics as subprocess).
-        spawn_env = os.environ.copy() if env is None else env
-        proc = ptyprocess.PtyProcess.spawn(  # type: ignore[union-attr]
-            list(argv),
-            cwd=cwd,
-            env=spawn_env,
-            dimensions=(rows, cols),
-        )
-        return cls(proc)
-
-    @property
-    def pid(self) -> int:
-        return int(self._proc.pid)
-
-    def is_alive(self) -> bool:
-        if self._closed:
-            return False
-        try:
-            return bool(self._proc.isalive())
-        except Exception:
-            return False
-
-    # -- I/O --------------------------------------------------------------
-
-    def read(self, timeout: float = 0.2) -> Optional[bytes]:
-        """Read up to 64 KiB of raw bytes from the PTY master.
-
-        Returns:
-            * bytes — zero or more bytes of child output
-            * empty bytes (``b""``) — no data available within ``timeout``
-            * None — child has exited and the master fd is at EOF
-
-        Never blocks longer than ``timeout`` seconds.  Safe to call after
-        :meth:`close`; returns ``None`` in that case.
-        """
-        if self._closed:
-            return None
-        try:
-            readable, _, _ = select.select([self._fd], [], [], timeout)
-        except (OSError, ValueError):
-            return None
-        if not readable:
-            return b""
-        try:
-            data = os.read(self._fd, 65536)
-        except OSError as exc:
-            # EIO on Linux = slave side closed.  EBADF = already closed.
-            if exc.errno in (errno.EIO, errno.EBADF):
-                return None
-            raise
-        if not data:
-            return None
-        return data
-
-    def write(self, data: bytes) -> None:
-        """Write raw bytes to the PTY master (i.e. the child's stdin)."""
-        if self._closed or not data:
-            return
-        # os.write can return a short write under load; loop until drained.
-        view = memoryview(data)
-        while view:
-            try:
-                n = os.write(self._fd, view)
-            except OSError as exc:
-                if exc.errno in (errno.EIO, errno.EBADF, errno.EPIPE):
-                    return
-                raise
-            if n <= 0:
-                return
-            view = view[n:]
-
-    def resize(self, cols: int, rows: int) -> None:
-        """Forward a terminal resize to the child via ``TIOCSWINSZ``."""
-        if self._closed:
-            return
-        # struct winsize: rows, cols, xpixel, ypixel (all unsigned short)
-        winsize = struct.pack("HHHH", max(1, rows), max(1, cols), 0, 0)
-        try:
-            fcntl.ioctl(self._fd, termios.TIOCSWINSZ, winsize)
-        except OSError:
-            pass
-
-    # -- teardown ---------------------------------------------------------
-
-    def close(self) -> None:
-        """Terminate the child (SIGTERM → 0.5s grace → SIGKILL) and close fds.
-
-        Idempotent.  Reaping the child is important so we don't leak
-        zombies across the lifetime of the dashboard process.
-        """
-        if self._closed:
-            return
-        self._closed = True
-
-        # SIGHUP is the conventional "your terminal went away" signal.
-        # We escalate if the child ignores it.
-        for sig in (signal.SIGHUP, signal.SIGTERM, signal.SIGKILL):
-            if not self._proc.isalive():
-                break
-            try:
-                self._proc.kill(sig)
-            except Exception:
-                pass
-            deadline = time.monotonic() + 0.5
-            while self._proc.isalive() and time.monotonic() < deadline:
-                time.sleep(0.02)
-
-        try:
-            self._proc.close(force=True)
-        except Exception:
-            pass
-
-    # Context-manager sugar — handy in tests and ad-hoc scripts.
-    def __enter__(self) -> "PtyBridge":
-        return self
-
-    def __exit__(self, *_exc) -> None:
-        self.close()

hermes_cli/runtime_provider.py

@@ -221,19 +221,6 @@ def _resolve_runtime_from_pool_entry(
     elif provider == "copilot":
         api_mode = _copilot_runtime_api_mode(model_cfg, getattr(entry, "runtime_api_key", ""))
         base_url = base_url or PROVIDER_REGISTRY["copilot"].inference_base_url
-    elif provider == "azure-foundry":
-        # Azure Foundry: read api_mode and base_url from config
-        cfg_provider = str(model_cfg.get("provider") or "").strip().lower()
-        if cfg_provider == "azure-foundry":
-            cfg_base_url = str(model_cfg.get("base_url") or "").strip().rstrip("/")
-            if cfg_base_url:
-                base_url = cfg_base_url
-            configured_mode = _parse_api_mode(model_cfg.get("api_mode"))
-            if configured_mode:
-                api_mode = configured_mode
-        # For Anthropic-style endpoints, strip /v1 suffix
-        if api_mode == "anthropic_messages":
-            base_url = re.sub(r"/v1/?$", "", base_url)
     else:
         configured_provider = str(model_cfg.get("provider") or "").strip().lower()
         # Honour model.base_url from config.yaml when the configured provider
@@ -602,71 +589,6 @@ def _resolve_openrouter_runtime(
     }
 
 
-def _resolve_azure_foundry_runtime(
-    *,
-    requested_provider: str,
-    model_cfg: Dict[str, Any],
-    explicit_api_key: Optional[str] = None,
-    explicit_base_url: Optional[str] = None,
-) -> Dict[str, Any]:
-    """Resolve an Azure Foundry runtime entry.
-
-    Reads ``model.base_url`` + ``model.api_mode`` from config.yaml (or
-    explicit overrides), pulls the API key from ``.env`` / env var, and
-    strips a trailing ``/v1`` for Anthropic-style endpoints because the
-    Anthropic SDK appends ``/v1/messages`` internally.
-
-    Raises :class:`AuthError` when required values are missing.
-    """
-    explicit_api_key = str(explicit_api_key or "").strip()
-    explicit_base_url_clean = str(explicit_base_url or "").strip().rstrip("/")
-
-    cfg_provider = str(model_cfg.get("provider") or "").strip().lower()
-    cfg_base_url = ""
-    cfg_api_mode = "chat_completions"
-    if cfg_provider == "azure-foundry":
-        cfg_base_url = str(model_cfg.get("base_url") or "").strip().rstrip("/")
-        cfg_api_mode = _parse_api_mode(model_cfg.get("api_mode")) or "chat_completions"
-
-    env_base_url = os.getenv("AZURE_FOUNDRY_BASE_URL", "").strip().rstrip("/")
-    base_url = explicit_base_url_clean or cfg_base_url or env_base_url
-    if not base_url:
-        raise AuthError(
-            "Azure Foundry requires a base URL. Set it via 'hermes model' or "
-            "the AZURE_FOUNDRY_BASE_URL environment variable."
-        )
-
-    api_key = explicit_api_key
-    if not api_key:
-        try:
-            from hermes_cli.config import get_env_value
-            api_key = get_env_value("AZURE_FOUNDRY_API_KEY") or ""
-        except Exception:
-            api_key = ""
-    if not api_key:
-        api_key = os.getenv("AZURE_FOUNDRY_API_KEY", "").strip()
-    if not api_key:
-        raise AuthError(
-            "Azure Foundry requires an API key. Set AZURE_FOUNDRY_API_KEY in "
-            "~/.hermes/.env or run 'hermes model' to configure."
-        )
-
-    # Anthropic SDK appends /v1/messages itself, so strip any trailing /v1
-    # we inherited from the configured base_url to avoid double-/v1 paths.
-    if cfg_api_mode == "anthropic_messages":
-        base_url = re.sub(r"/v1/?$", "", base_url)
-
-    source = "explicit" if (explicit_api_key or explicit_base_url) else "config"
-    return {
-        "provider": "azure-foundry",
-        "api_mode": cfg_api_mode,
-        "base_url": base_url,
-        "api_key": api_key,
-        "source": source,
-        "requested_provider": requested_provider,
-    }
-
-
 def _resolve_explicit_runtime(
     *,
     provider: str,
@@ -756,15 +678,6 @@ def _resolve_explicit_runtime(
             "requested_provider": requested_provider,
         }
 
-    # Azure Foundry: user-configured endpoint with selectable API mode
-    if provider == "azure-foundry":
-        return _resolve_azure_foundry_runtime(
-            requested_provider=requested_provider,
-            model_cfg=model_cfg,
-            explicit_api_key=explicit_api_key,
-            explicit_base_url=explicit_base_url,
-        )
-
     pconfig = PROVIDER_REGISTRY.get(provider)
     if pconfig and pconfig.auth_type == "api_key":
         env_url = ""
@@ -833,40 +746,6 @@ def resolve_runtime_provider(
     """
     requested_provider = resolve_requested_provider(requested)
 
-    # Azure Anthropic short-circuit: when explicitly targeting an Azure endpoint
-    # with provider="anthropic", bypass _resolve_named_custom_runtime (which would
-    # return provider="custom" with chat_completions api_mode and no valid key).
-    # Instead, use the Azure key directly with anthropic_messages api_mode.
-    _eff_base = (explicit_base_url or "").strip()
-    if requested_provider == "anthropic" and "azure.com" in _eff_base:
-        _azure_key = (
-            (explicit_api_key or "").strip()
-            or os.getenv("AZURE_ANTHROPIC_KEY", "").strip()
-            or os.getenv("ANTHROPIC_API_KEY", "").strip()
-        )
-        return {
-            "provider": "anthropic",
-            "api_mode": "anthropic_messages",
-            "base_url": _eff_base.rstrip("/"),
-            "api_key": _azure_key,
-            "source": "azure-explicit",
-            "requested_provider": requested_provider,
-        }
-
-    # Azure Foundry: user-configured endpoint with selectable API mode
-    # (OpenAI-style chat_completions or Anthropic-style anthropic_messages).
-    # Resolve before the custom-runtime / pool / generic paths so Azure
-    # config is always picked up from model.base_url + model.api_mode,
-    # regardless of whether the caller passed explicit_* args.
-    if requested_provider == "azure-foundry":
-        azure_runtime = _resolve_azure_foundry_runtime(
-            requested_provider=requested_provider,
-            model_cfg=_get_model_config(),
-            explicit_api_key=explicit_api_key,
-            explicit_base_url=explicit_base_url,
-        )
-        return azure_runtime
-
     custom_runtime = _resolve_named_custom_runtime(
         requested_provider=requested_provider,
         explicit_api_key=explicit_api_key,
@@ -1045,6 +924,13 @@ def resolve_runtime_provider(
 
     # Anthropic (native Messages API)
     if provider == "anthropic":
+        from agent.anthropic_adapter import resolve_anthropic_token
+        token = resolve_anthropic_token()
+        if not token:
+            raise AuthError(
+                "No Anthropic credentials found. Set ANTHROPIC_TOKEN or ANTHROPIC_API_KEY, "
+                "run 'claude setup-token', or authenticate with 'claude /login'."
+            )
         # Allow base URL override from config.yaml model.base_url, but only
         # when the configured provider is anthropic — otherwise a non-Anthropic
         # base_url (e.g. Codex endpoint) would leak into Anthropic requests.
@@ -1053,33 +939,6 @@ def resolve_runtime_provider(
         if cfg_provider == "anthropic":
             cfg_base_url = (model_cfg.get("base_url") or "").strip().rstrip("/")
         base_url = cfg_base_url or "https://api.anthropic.com"
-
-        # For Azure AI Foundry endpoints, use ANTHROPIC_API_KEY directly —
-        # Claude Code OAuth tokens (sk-ant-oat01) are not accepted by Azure.
-        # Azure keys don't start with "sk-ant-" so resolve_anthropic_token()
-        # would find the Claude Code OAuth token first (priority 3) and return
-        # that instead, causing 401s. Detect Azure endpoints and use the env
-        # key directly to bypass the OAuth priority chain.
-        _is_azure_endpoint = "azure.com" in base_url.lower() or (
-            cfg_base_url and "azure.com" in cfg_base_url.lower()
-        )
-        if _is_azure_endpoint:
-            token = (
-                os.getenv("AZURE_ANTHROPIC_KEY", "").strip()
-                or os.getenv("ANTHROPIC_API_KEY", "").strip()
-            )
-            if not token:
-                raise AuthError(
-                    "No Azure Anthropic API key found. Set AZURE_ANTHROPIC_KEY or ANTHROPIC_API_KEY."
-                )
-        else:
-            from agent.anthropic_adapter import resolve_anthropic_token
-            token = resolve_anthropic_token()
-            if not token:
-                raise AuthError(
-                    "No Anthropic credentials found. Set ANTHROPIC_TOKEN or ANTHROPIC_API_KEY, "
-                    "run 'claude setup-token', or authenticate with 'claude /login'."
-                )
         return {
             "provider": "anthropic",
             "api_mode": "anthropic_messages",

hermes_cli/setup.py

@@ -2863,6 +2863,17 @@ SETUP_SECTIONS = [
     ("agent", "Agent Settings", setup_agent_settings),
 ]
 
+# The returning-user menu intentionally omits standalone TTS because model setup
+# already includes TTS selection and tools setup covers the rest of the provider
+# configuration. Keep this list in the same order as the visible menu entries.
+RETURNING_USER_MENU_SECTION_KEYS = [
+    "model",
+    "terminal",
+    "gateway",
+    "tools",
+    "agent",
+]
+
 
 def run_setup_wizard(args):
     """Run the interactive setup wizard.
@@ -2887,9 +2898,6 @@ def run_setup_wizard(args):
         save_config(copy.deepcopy(DEFAULT_CONFIG))
         print_success("Configuration reset to defaults.")
 
-    reconfigure_requested = bool(getattr(args, "reconfigure", False))
-    quick_requested = bool(getattr(args, "quick", False))
-
     config = load_config()
     hermes_home = get_hermes_home()
 
@@ -2981,36 +2989,50 @@ def run_setup_wizard(args):
     migration_ran = False
 
     if is_existing:
-        # Existing install — default is the full-wizard reconfigure flow.
-        # Every prompt shows the current value as its default, so pressing
-        # Enter keeps it.  Opt into `--quick` for the narrow "just fill in
-        # missing items" flow (useful after a partial OpenClaw migration
-        # or when a required API key got cleared).
-        if quick_requested:
+        # ── Returning User Menu ──
+        print()
+        print_header("Welcome Back!")
+        print_success("You already have Hermes configured.")
+        print()
+
+        menu_choices = [
+            "Quick Setup - configure missing items only",
+            "Full Setup - reconfigure everything",
+            "Model & Provider",
+            "Terminal Backend",
+            "Messaging Platforms (Gateway)",
+            "Tools",
+            "Agent Settings",
+            "Exit",
+        ]
+        choice = prompt_choice("What would you like to do?", menu_choices, 0)
+
+        if choice == 0:
+            # Quick setup
             _run_quick_setup(config, hermes_home)
             return
-
-        print()
-        print_header("Reconfigure")
-        print_success("You already have Hermes configured.")
-        print_info("Running the full wizard — each prompt shows your current value.")
-        print_info("Press Enter to keep it, or type a new value to change it.")
-        print_info("")
-        print_info("Tip: jump straight to a section with 'hermes setup model|terminal|")
-        print_info("     gateway|tools|agent', or fill only missing items with --quick.")
-        # Fall through to the "Full Setup — run all sections" block below.
-        # --reconfigure is now the default on existing installs; the flag
-        # is preserved for backwards compatibility but is a no-op here.
+        elif choice == 1:
+            # Full setup — fall through to run all sections
+            pass
+        elif choice == 7:
+            print_info("Exiting. Run 'hermes setup' again when ready.")
+            return
+        elif 2 <= choice <= 6:
+            # Individual section — map by key, not by position.
+            # SETUP_SECTIONS includes TTS but the returning-user menu skips it,
+            # so positional indexing (choice - 2) would dispatch the wrong section.
+            section_key = RETURNING_USER_MENU_SECTION_KEYS[choice - 2]
+            section = next((s for s in SETUP_SECTIONS if s[0] == section_key), None)
+            if section:
+                _, label, func = section
+                func(config)
+                save_config(config)
+                _print_setup_summary(config, hermes_home)
+            return
     else:
         # ── First-Time Setup ──
         print()
 
-        # --reconfigure / --quick on a fresh install are meaningless — fall
-        # through to the normal first-time flow.
-        if reconfigure_requested or quick_requested:
-            print_info("No existing configuration found — running first-time setup.")
-            print()
-
         # Offer OpenClaw migration before configuration begins
         migration_ran = _offer_openclaw_migration(hermes_home)
         if migration_ran:

hermes_cli/tips.py

@@ -10,7 +10,8 @@ import random
 
 TIPS = [
     # --- Slash Commands ---
-    "/background <prompt> (alias /bg or /btw) runs a task in a separate session while your current one stays free.",
+    "/btw <question> asks a quick side question without tools or history — great for clarifications.",
+    "/background <prompt> runs a task in a separate session while your current one stays free.",
     "/branch forks the current session so you can explore a different direction without losing progress.",
     "/compress manually compresses conversation context when things get long.",
     "/rollback lists filesystem checkpoints — restore files the agent modified to any prior state.",

hermes_cli/tools_config.py

@@ -68,58 +68,25 @@ CONFIGURABLE_TOOLSETS = [
     ("rl",              "🧪 RL Training",               "Tinker-Atropos training tools"),
     ("homeassistant",    "🏠 Home Assistant",           "smart home device control"),
     ("spotify",          "🎵 Spotify",                  "playback, search, playlists, library"),
-    ("discord",         "💬 Discord (read/participate)", "fetch messages, search members, create thread"),
-    ("discord_admin",   "🛡️  Discord Server Admin",    "list channels/roles, pin, assign roles"),
 ]
 
 # Toolsets that are OFF by default for new installs.
 # They're still in _HERMES_CORE_TOOLS (available at runtime if enabled),
 # but the setup checklist won't pre-select them for first-time users.
-_DEFAULT_OFF_TOOLSETS = {"moa", "homeassistant", "rl", "spotify", "discord", "discord_admin"}
-
-# Platform-scoped toolsets: only appear in the `hermes tools` checklist for
-# these platforms, and only resolve/save for these platforms.  A toolset
-# absent from this map is available on every platform (current behaviour).
-#
-# Use this for tools whose APIs only make sense on one platform (Discord
-# server admin, Slack workspace admin, etc.).  Keeps every other platform's
-# checklist from filling up with irrelevant toggles.
-_TOOLSET_PLATFORM_RESTRICTIONS: Dict[str, Set[str]] = {
-    "discord": {"discord"},
-    "discord_admin": {"discord"},
-}
-
-
-def _toolset_allowed_for_platform(ts_key: str, platform: str) -> bool:
-    """Return True if ``ts_key`` is configurable on ``platform``.
-
-    Toolsets without a restriction entry are allowed everywhere (the default).
-    """
-    allowed = _TOOLSET_PLATFORM_RESTRICTIONS.get(ts_key)
-    return allowed is None or platform in allowed
+_DEFAULT_OFF_TOOLSETS = {"moa", "homeassistant", "rl", "spotify"}
 
 
 def _get_effective_configurable_toolsets():
     """Return CONFIGURABLE_TOOLSETS + any plugin-provided toolsets.
 
     Plugin toolsets are appended at the end so they appear after the
-    built-in toolsets in the TUI checklist. A plugin whose toolset key
-    already appears in ``CONFIGURABLE_TOOLSETS`` is skipped — bundled
-    plugins (e.g. ``plugins/spotify``) share their toolset key with the
-    built-in entry, and we want the built-in label/description to win.
-    Without the dedupe, ``hermes tools`` → "reconfigure existing" would
-    list the same toolset twice.
+    built-in toolsets in the TUI checklist.
     """
     result = list(CONFIGURABLE_TOOLSETS)
-    seen = {ts_key for ts_key, _, _ in result}
     try:
         from hermes_cli.plugins import discover_plugins, get_plugin_toolsets
         discover_plugins()  # idempotent — ensures plugins are loaded
-        for entry in get_plugin_toolsets():
-            if entry[0] in seen:
-                continue
-            seen.add(entry[0])
-            result.append(entry)
+        result.extend(get_plugin_toolsets())
     except Exception:
         pass
     return result
@@ -401,9 +368,13 @@ TOOL_CATEGORIES = {
         "providers": [
             {
                 "name": "Spotify Web API",
-                "tag": "PKCE OAuth — opens the setup wizard",
-                "env_vars": [],
-                "post_setup": "spotify",
+                "tag": "PKCE OAuth — run `hermes auth spotify` after this",
+                "env_vars": [
+                    {"key": "HERMES_SPOTIFY_CLIENT_ID", "prompt": "Spotify app client_id",
+                     "url": "https://developer.spotify.com/dashboard"},
+                    {"key": "HERMES_SPOTIFY_REDIRECT_URI", "prompt": "Redirect URI (must be allow-listed in your Spotify app)",
+                     "default": "http://127.0.0.1:43827/spotify/callback"},
+                ],
             },
         ],
     },
@@ -507,35 +478,6 @@ def _run_post_setup(post_setup_key: str):
             _print_warning("    kittentts install timed out (>5min)")
             _print_info(f"    Run manually: python -m pip install -U '{wheel_url}' soundfile")
 
-    elif post_setup_key == "spotify":
-        # Run the full `hermes auth spotify` flow — if the user has no
-        # client_id yet, this drops them into the interactive wizard
-        # (opens the Spotify dashboard, prompts for client_id, persists
-        # to ~/.hermes/.env), then continues straight into PKCE. If they
-        # already have an app, it skips the wizard and just does OAuth.
-        from types import SimpleNamespace
-        try:
-            from hermes_cli.auth import login_spotify_command
-        except Exception as exc:
-            _print_warning(f"    Could not load Spotify auth: {exc}")
-            _print_info("    Run manually: hermes auth spotify")
-            return
-        _print_info("    Starting Spotify login...")
-        try:
-            login_spotify_command(SimpleNamespace(
-                client_id=None, redirect_uri=None, scope=None,
-                no_browser=False, timeout=None,
-            ))
-            _print_success("    Spotify authenticated")
-        except SystemExit as exc:
-            # User aborted the wizard, or OAuth failed — don't fail the
-            # toolset enable; they can retry with `hermes auth spotify`.
-            _print_warning(f"    Spotify login did not complete: {exc}")
-            _print_info("    Run later: hermes auth spotify")
-        except Exception as exc:
-            _print_warning(f"    Spotify login failed: {exc}")
-            _print_info("    Run manually: hermes auth spotify")
-
     elif post_setup_key == "rl_training":
         try:
             __import__("tinker_atropos")
@@ -624,7 +566,7 @@ def _get_platform_tools(
     include_default_mcp_servers: bool = True,
 ) -> Set[str]:
     """Resolve which individual toolset names are enabled for a platform."""
-    from toolsets import resolve_toolset, TOOLSETS
+    from toolsets import resolve_toolset
 
     platform_toolsets = config.get("platform_toolsets") or {}
     toolset_names = platform_toolsets.get(platform)
@@ -638,8 +580,6 @@ def _get_platform_tools(
     toolset_names = [str(ts) for ts in toolset_names]
 
     configurable_keys = {ts_key for ts_key, _, _ in CONFIGURABLE_TOOLSETS}
-    plugin_ts_keys = _get_plugin_toolset_keys()
-    platform_default_keys = {p["default_toolset"] for p in PLATFORMS.values()}
 
     # If the saved list contains any configurable keys directly, the user
     # has explicitly configured this platform — use direct membership.
@@ -649,10 +589,7 @@ def _get_platform_tools(
     has_explicit_config = any(ts in configurable_keys for ts in toolset_names)
 
     if has_explicit_config:
-        enabled_toolsets = {
-            ts for ts in toolset_names
-            if ts in configurable_keys and _toolset_allowed_for_platform(ts, platform)
-        }
+        enabled_toolsets = {ts for ts in toolset_names if ts in configurable_keys}
     else:
         # No explicit config — fall back to resolving composite toolset names
         # (e.g. "hermes-cli") to individual tool names and reverse-mapping.
@@ -662,52 +599,14 @@ def _get_platform_tools(
 
         enabled_toolsets = set()
         for ts_key, _, _ in CONFIGURABLE_TOOLSETS:
-            if not _toolset_allowed_for_platform(ts_key, platform):
-                continue
             ts_tools = set(resolve_toolset(ts_key))
             if ts_tools and ts_tools.issubset(all_tool_names):
                 enabled_toolsets.add(ts_key)
-
         default_off = set(_DEFAULT_OFF_TOOLSETS)
-        # Legacy safety: if the platform's own name matches a default-off
-        # toolset (e.g. `homeassistant` platform + `homeassistant` toolset),
-        # keep that toolset enabled on first install.  Skip this dodge for
-        # platform-restricted toolsets — those are always opt-in even on
-        # their own platform (e.g. `discord` + `discord` should stay OFF).
-        if platform in default_off and platform not in _TOOLSET_PLATFORM_RESTRICTIONS:
+        if platform in default_off:
             default_off.remove(platform)
         enabled_toolsets -= default_off
 
-    # Recover non-configurable platform toolsets (e.g. discord, feishu_doc,
-    # feishu_drive).  These are part of the platform's default composite but
-    # absent from CONFIGURABLE_TOOLSETS, so they can't appear in the TUI
-    # checklist or in a user-saved config.  Must run in BOTH branches —
-    # otherwise saving via `hermes tools` (which flips has_explicit_config
-    # to True) silently drops them.
-    platform_tool_universe = set(resolve_toolset(PLATFORMS[platform]["default_toolset"]))
-    configurable_tool_universe = set()
-    for ck in configurable_keys:
-        configurable_tool_universe.update(resolve_toolset(ck))
-    claimed = set()
-    for ts_key in enabled_toolsets:
-        claimed.update(resolve_toolset(ts_key))
-    skip = configurable_keys | plugin_ts_keys | platform_default_keys
-    skip |= {k for k in TOOLSETS if k.startswith("hermes-")}
-    skip |= set(_DEFAULT_OFF_TOOLSETS) - {platform}
-    for ts_key, ts_def in TOOLSETS.items():
-        if ts_key in skip:
-            continue
-        if ts_def.get("includes"):
-            continue
-        ts_tools = set(resolve_toolset(ts_key))
-        if not ts_tools or not ts_tools.issubset(platform_tool_universe):
-            continue
-        if ts_tools.issubset(configurable_tool_universe):
-            continue
-        if not ts_tools.issubset(claimed):
-            enabled_toolsets.add(ts_key)
-            claimed.update(ts_tools)
-
     # Plugin toolsets: enabled by default unless explicitly disabled, or
     # unless the toolset is in _DEFAULT_OFF_TOOLSETS (e.g. spotify —
     # shipped as a bundled plugin but user must opt in via `hermes tools`
@@ -715,6 +614,7 @@ def _get_platform_tools(
     # A plugin toolset is "known" for a platform once `hermes tools`
     # has been saved for that platform (tracked via known_plugin_toolsets).
     # Unknown plugins default to enabled; known-but-absent = disabled.
+    plugin_ts_keys = _get_plugin_toolset_keys()
     if plugin_ts_keys:
         known_map = config.get("known_plugin_toolsets", {})
         known_for_platform = set(known_map.get(platform, []))
@@ -732,6 +632,7 @@ def _get_platform_tools(
 
     # Preserve any explicit non-configurable toolset entries (for example,
     # custom toolsets or MCP server names saved in platform_toolsets).
+    platform_default_keys = {p["default_toolset"] for p in PLATFORMS.values()}
     explicit_passthrough = {
         ts
         for ts in toolset_names
@@ -777,14 +678,6 @@ def _save_platform_tools(config: dict, platform: str, enabled_toolset_keys: Set[
     """
     config.setdefault("platform_toolsets", {})
 
-    # Drop platform-scoped toolsets that don't apply here.  Prevents the
-    # "Configure all platforms" checklist (or a hand-edited config.yaml)
-    # from turning on, say, the `discord` toolset for Telegram.
-    enabled_toolset_keys = {
-        ts for ts in enabled_toolset_keys
-        if _toolset_allowed_for_platform(ts, platform)
-    }
-
     # Get the set of all configurable toolset keys (built-in + plugin)
     configurable_keys = {ts_key for ts_key, _, _ in CONFIGURABLE_TOOLSETS}
     plugin_keys = _get_plugin_toolset_keys()
@@ -799,7 +692,6 @@ def _save_platform_tools(config: dict, platform: str, enabled_toolset_keys: Set[
     existing_toolsets = config.get("platform_toolsets", {}).get(platform, [])
     if not isinstance(existing_toolsets, list):
         existing_toolsets = []
-    existing_toolsets = [str(ts) for ts in existing_toolsets]
 
     # Preserve any entries that are NOT configurable toolsets and NOT platform
     # defaults (i.e. only MCP server names should be preserved)
@@ -807,11 +699,6 @@ def _save_platform_tools(config: dict, platform: str, enabled_toolset_keys: Set[
         entry for entry in existing_toolsets
         if entry not in configurable_keys and entry not in platform_default_keys
     }
-    # Opening `hermes tools` is the user's opt-in to reconfigure tools, so treat
-    # saving from the picker as consent to clear the "no_mcp" sentinel. The
-    # picker has no checkbox for no_mcp, so without this users who once set it
-    # by hand could never re-enable MCP servers through the UI.
-    preserved_entries.discard("no_mcp")
 
     # Merge preserved entries with new enabled toolsets
     config["platform_toolsets"][platform] = sorted(enabled_toolset_keys | preserved_entries)
@@ -919,7 +806,7 @@ def _estimate_tool_tokens() -> Dict[str, int]:
     return _tool_token_cache
 
 
-def _prompt_toolset_checklist(platform_label: str, enabled: Set[str], platform: str = "cli") -> Set[str]:
+def _prompt_toolset_checklist(platform_label: str, enabled: Set[str]) -> Set[str]:
     """Multi-select checklist of toolsets. Returns set of selected toolset keys."""
     from hermes_cli.curses_ui import curses_checklist
     from toolsets import resolve_toolset
@@ -927,12 +814,7 @@ def _prompt_toolset_checklist(platform_label: str, enabled: Set[str], platform:
     # Pre-compute per-tool token counts (cached after first call).
     tool_tokens = _estimate_tool_tokens()
 
-    effective_all = _get_effective_configurable_toolsets()
-    # Drop platform-scoped toolsets that don't apply to this platform.
-    effective = [
-        (k, l, d) for (k, l, d) in effective_all
-        if _toolset_allowed_for_platform(k, platform)
-    ]
+    effective = _get_effective_configurable_toolsets()
 
     labels = []
     for ts_key, ts_label, ts_desc in effective:
@@ -1846,7 +1728,7 @@ def tools_command(args=None, first_install: bool = False, config: dict = None):
             checklist_preselected = current_enabled - _DEFAULT_OFF_TOOLSETS
 
             # Show checklist
-            new_enabled = _prompt_toolset_checklist(pinfo["label"], checklist_preselected, pkey)
+            new_enabled = _prompt_toolset_checklist(pinfo["label"], checklist_preselected)
 
             added = new_enabled - current_enabled
             removed = current_enabled - new_enabled
@@ -2202,11 +2084,7 @@ def _apply_mcp_change(config: dict, targets: List[str], action: str) -> Set[str]
 
 def _print_tools_list(enabled_toolsets: set, mcp_servers: dict, platform: str = "cli"):
     """Print a summary of enabled/disabled toolsets and MCP tool filters."""
-    effective_all = _get_effective_configurable_toolsets()
-    effective = [
-        (k, l, d) for (k, l, d) in effective_all
-        if _toolset_allowed_for_platform(k, platform)
-    ]
+    effective = _get_effective_configurable_toolsets()
     builtin_keys = {ts_key for ts_key, _, _ in CONFIGURABLE_TOOLSETS}
 
     print(f"Built-in toolsets ({platform}):")
@@ -2272,20 +2150,6 @@ def tools_disable_enable_command(args):
             _print_error(f"Unknown toolset '{name}'")
         toolset_targets = [t for t in toolset_targets if t in valid_toolsets]
 
-    # Reject platform-scoped toolsets on platforms that don't allow them.
-    restricted_targets = [
-        t for t in toolset_targets
-        if not _toolset_allowed_for_platform(t, platform)
-    ]
-    if restricted_targets:
-        for name in restricted_targets:
-            allowed = sorted(_TOOLSET_PLATFORM_RESTRICTIONS.get(name) or set())
-            _print_error(
-                f"Toolset '{name}' is not available on platform '{platform}' "
-                f"(only: {', '.join(allowed)})"
-            )
-        toolset_targets = [t for t in toolset_targets if t not in restricted_targets]
-
     if toolset_targets:
         _apply_toolset_change(config, platform, toolset_targets, action)
 

hermes_cli/web_server.py

@@ -49,7 +49,7 @@ from hermes_cli.config import (
 from gateway.status import get_running_pid, read_runtime_status
 
 try:
-    from fastapi import FastAPI, HTTPException, Request, WebSocket, WebSocketDisconnect
+    from fastapi import FastAPI, HTTPException, Request
     from fastapi.middleware.cors import CORSMiddleware
     from fastapi.responses import FileResponse, HTMLResponse, JSONResponse
     from fastapi.staticfiles import StaticFiles
@@ -73,10 +73,6 @@ app = FastAPI(title="Hermes Agent", version=__version__)
 _SESSION_TOKEN = secrets.token_urlsafe(32)
 _SESSION_HEADER_NAME = "X-Hermes-Session-Token"
 
-# In-browser Chat tab (/chat, /api/pty, …).  Off unless ``hermes dashboard --tui``
-# or HERMES_DASHBOARD_TUI=1.  Set from :func:`start_server`.
-_DASHBOARD_EMBEDDED_CHAT_ENABLED = False
-
 # Simple rate limiter for the reveal endpoint
 _reveal_timestamps: List[float] = []
 _REVEAL_MAX_PER_WINDOW = 5
@@ -287,7 +283,7 @@ _SCHEMA_OVERRIDES: Dict[str, Dict[str, Any]] = {
     "display.busy_input_mode": {
         "type": "select",
         "description": "Input behavior while agent is running",
-        "options": ["interrupt", "queue"],
+        "options": ["queue", "interrupt", "block"],
     },
     "memory.provider": {
         "type": "select",
@@ -1533,30 +1529,26 @@ def _submit_anthropic_pkce(session_id: str, code_input: str) -> Dict[str, Any]:
         with urllib.request.urlopen(req, timeout=20) as resp:
             result = json.loads(resp.read().decode())
     except Exception as e:
-        with _oauth_sessions_lock:
-            sess["status"] = "error"
-            sess["error_message"] = f"Token exchange failed: {e}"
+        sess["status"] = "error"
+        sess["error_message"] = f"Token exchange failed: {e}"
         return {"ok": False, "status": "error", "message": sess["error_message"]}
 
     access_token = result.get("access_token", "")
     refresh_token = result.get("refresh_token", "")
     expires_in = int(result.get("expires_in") or 3600)
     if not access_token:
-        with _oauth_sessions_lock:
-            sess["status"] = "error"
-            sess["error_message"] = "No access token returned"
+        sess["status"] = "error"
+        sess["error_message"] = "No access token returned"
         return {"ok": False, "status": "error", "message": sess["error_message"]}
 
     expires_at_ms = int(time.time() * 1000) + (expires_in * 1000)
     try:
         _save_anthropic_oauth_creds(access_token, refresh_token, expires_at_ms)
     except Exception as e:
-        with _oauth_sessions_lock:
-            sess["status"] = "error"
-            sess["error_message"] = f"Save failed: {e}"
+        sess["status"] = "error"
+        sess["error_message"] = f"Save failed: {e}"
         return {"ok": False, "status": "error", "message": sess["error_message"]}
-    with _oauth_sessions_lock:
-        sess["status"] = "approved"
+    sess["status"] = "approved"
     _log.info("oauth/pkce: anthropic login completed (session=%s)", session_id)
     return {"ok": True, "status": "approved"}
 
@@ -2271,329 +2263,6 @@ async def get_usage_analytics(days: int = 30):
         db.close()
 
 
-# ---------------------------------------------------------------------------
-# /api/pty — PTY-over-WebSocket bridge for the dashboard "Chat" tab.
-#
-# The endpoint spawns the same ``hermes --tui`` binary the CLI uses, behind
-# a POSIX pseudo-terminal, and forwards bytes + resize escapes across a
-# WebSocket.  The browser renders the ANSI through xterm.js (see
-# web/src/pages/ChatPage.tsx).
-#
-# Auth: ``?token=<session_token>`` query param (browsers can't set
-# Authorization on the WS upgrade).  Same ephemeral ``_SESSION_TOKEN`` as
-# REST.  Localhost-only — we defensively reject non-loopback clients even
-# though uvicorn binds to 127.0.0.1.
-# ---------------------------------------------------------------------------
-
-import re
-import asyncio
-
-from hermes_cli.pty_bridge import PtyBridge, PtyUnavailableError
-
-_RESIZE_RE = re.compile(rb"\x1b\[RESIZE:(\d+);(\d+)\]")
-_PTY_READ_CHUNK_TIMEOUT = 0.2
-_VALID_CHANNEL_RE = re.compile(r"^[A-Za-z0-9._-]{1,128}$")
-# Starlette's TestClient reports the peer as "testclient"; treat it as
-# loopback so tests don't need to rewrite request scope.
-_LOOPBACK_HOSTS = frozenset({"127.0.0.1", "::1", "localhost", "testclient"})
-
-# Per-channel subscriber registry used by /api/pub (PTY-side gateway → dashboard)
-# and /api/events (dashboard → browser sidebar).  Keyed by an opaque channel id
-# the chat tab generates on mount; entries auto-evict when the last subscriber
-# drops AND the publisher has disconnected.
-_event_channels: dict[str, set] = {}
-_event_lock = asyncio.Lock()
-
-
-def _resolve_chat_argv(
-    resume: Optional[str] = None,
-    sidecar_url: Optional[str] = None,
-) -> tuple[list[str], Optional[str], Optional[dict]]:
-    """Resolve the argv + cwd + env for the chat PTY.
-
-    Default: whatever ``hermes --tui`` would run.  Tests monkeypatch this
-    function to inject a tiny fake command (``cat``, ``sh -c 'printf …'``)
-    so nothing has to build Node or the TUI bundle.
-
-    Session resume is propagated via the ``HERMES_TUI_RESUME`` env var —
-    matching what ``hermes_cli.main._launch_tui`` does for the CLI path.
-    Appending ``--resume <id>`` to argv doesn't work because ``ui-tui`` does
-    not parse its argv.
-
-    `sidecar_url` (when set) is forwarded as ``HERMES_TUI_SIDECAR_URL`` so
-    the spawned ``tui_gateway.entry`` can mirror dispatcher emits to the
-    dashboard's ``/api/pub`` endpoint (see :func:`pub_ws`).
-    """
-    from hermes_cli.main import PROJECT_ROOT, _make_tui_argv
-
-    argv, cwd = _make_tui_argv(PROJECT_ROOT / "ui-tui", tui_dev=False)
-    env: Optional[dict] = None
-
-    if resume or sidecar_url:
-        env = os.environ.copy()
-
-        if resume:
-            env["HERMES_TUI_RESUME"] = resume
-
-        if sidecar_url:
-            env["HERMES_TUI_SIDECAR_URL"] = sidecar_url
-
-    return list(argv), str(cwd) if cwd else None, env
-
-
-def _build_sidecar_url(channel: str) -> Optional[str]:
-    """ws:// URL the PTY child should publish events to, or None when unbound."""
-    host = getattr(app.state, "bound_host", None)
-    port = getattr(app.state, "bound_port", None)
-
-    if not host or not port:
-        return None
-
-    netloc = f"[{host}]:{port}" if ":" in host and not host.startswith("[") else f"{host}:{port}"
-    qs = urllib.parse.urlencode({"token": _SESSION_TOKEN, "channel": channel})
-
-    return f"ws://{netloc}/api/pub?{qs}"
-
-
-async def _broadcast_event(channel: str, payload: str) -> None:
-    """Fan out one publisher frame to every subscriber on `channel`."""
-    async with _event_lock:
-        subs = list(_event_channels.get(channel, ()))
-
-    for sub in subs:
-        try:
-            await sub.send_text(payload)
-        except Exception:
-            # Subscriber went away mid-send; the /api/events finally clause
-            # will remove it from the registry on its next iteration.
-            pass
-
-
-def _channel_or_close_code(ws: WebSocket) -> Optional[str]:
-    """Return the channel id from the query string or None if invalid."""
-    channel = ws.query_params.get("channel", "")
-
-    return channel if _VALID_CHANNEL_RE.match(channel) else None
-
-
-@app.websocket("/api/pty")
-async def pty_ws(ws: WebSocket) -> None:
-    if not _DASHBOARD_EMBEDDED_CHAT_ENABLED:
-        await ws.close(code=4403)
-        return
-
-    # --- auth + loopback check (before accept so we can close cleanly) ---
-    token = ws.query_params.get("token", "")
-    expected = _SESSION_TOKEN
-    if not hmac.compare_digest(token.encode(), expected.encode()):
-        await ws.close(code=4401)
-        return
-
-    client_host = ws.client.host if ws.client else ""
-    if client_host and client_host not in _LOOPBACK_HOSTS:
-        await ws.close(code=4403)
-        return
-
-    await ws.accept()
-
-    # --- spawn PTY ------------------------------------------------------
-    resume = ws.query_params.get("resume") or None
-    channel = _channel_or_close_code(ws)
-    sidecar_url = _build_sidecar_url(channel) if channel else None
-
-    try:
-        argv, cwd, env = _resolve_chat_argv(resume=resume, sidecar_url=sidecar_url)
-    except SystemExit as exc:
-        # _make_tui_argv calls sys.exit(1) when node/npm is missing.
-        await ws.send_text(f"\r\n\x1b[31mChat unavailable: {exc}\x1b[0m\r\n")
-        await ws.close(code=1011)
-        return
-
-
-    try:
-        bridge = PtyBridge.spawn(argv, cwd=cwd, env=env)
-    except PtyUnavailableError as exc:
-        await ws.send_text(f"\r\n\x1b[31mChat unavailable: {exc}\x1b[0m\r\n")
-        await ws.close(code=1011)
-        return
-    except (FileNotFoundError, OSError) as exc:
-        await ws.send_text(f"\r\n\x1b[31mChat failed to start: {exc}\x1b[0m\r\n")
-        await ws.close(code=1011)
-        return
-
-    loop = asyncio.get_running_loop()
-
-    # --- reader task: PTY master → WebSocket ----------------------------
-    async def pump_pty_to_ws() -> None:
-        while True:
-            chunk = await loop.run_in_executor(
-                None, bridge.read, _PTY_READ_CHUNK_TIMEOUT
-            )
-            if chunk is None:  # EOF
-                return
-            if not chunk:  # no data this tick; yield control and retry
-                await asyncio.sleep(0)
-                continue
-            try:
-                await ws.send_bytes(chunk)
-            except Exception:
-                return
-
-    reader_task = asyncio.create_task(pump_pty_to_ws())
-
-    # --- writer loop: WebSocket → PTY master ----------------------------
-    try:
-        while True:
-            msg = await ws.receive()
-            msg_type = msg.get("type")
-            if msg_type == "websocket.disconnect":
-                break
-            raw = msg.get("bytes")
-            if raw is None:
-                text = msg.get("text")
-                raw = text.encode("utf-8") if isinstance(text, str) else b""
-            if not raw:
-                continue
-
-            # Resize escape is consumed locally, never written to the PTY.
-            match = _RESIZE_RE.match(raw)
-            if match and match.end() == len(raw):
-                cols = int(match.group(1))
-                rows = int(match.group(2))
-                bridge.resize(cols=cols, rows=rows)
-                continue
-
-            bridge.write(raw)
-    except WebSocketDisconnect:
-        pass
-    finally:
-        reader_task.cancel()
-        try:
-            await reader_task
-        except (asyncio.CancelledError, Exception):
-            pass
-        bridge.close()
-
-
-# ---------------------------------------------------------------------------
-# /api/ws — JSON-RPC WebSocket sidecar for the dashboard "Chat" tab.
-#
-# Drives the same `tui_gateway.dispatch` surface Ink uses over stdio, so the
-# dashboard can render structured metadata (model badge, tool-call sidebar,
-# slash launcher, session info) alongside the xterm.js terminal that PTY
-# already paints. Both transports bind to the same session id when one is
-# active, so a tool.start emitted by the agent fans out to both sinks.
-# ---------------------------------------------------------------------------
-
-
-@app.websocket("/api/ws")
-async def gateway_ws(ws: WebSocket) -> None:
-    if not _DASHBOARD_EMBEDDED_CHAT_ENABLED:
-        await ws.close(code=4403)
-        return
-
-    token = ws.query_params.get("token", "")
-    if not hmac.compare_digest(token.encode(), _SESSION_TOKEN.encode()):
-        await ws.close(code=4401)
-        return
-
-    client_host = ws.client.host if ws.client else ""
-    if client_host and client_host not in _LOOPBACK_HOSTS:
-        await ws.close(code=4403)
-        return
-
-    from tui_gateway.ws import handle_ws
-
-    await handle_ws(ws)
-
-
-# ---------------------------------------------------------------------------
-# /api/pub + /api/events — chat-tab event broadcast.
-#
-# The PTY-side ``tui_gateway.entry`` opens /api/pub at startup (driven by
-# HERMES_TUI_SIDECAR_URL set in /api/pty's PTY env) and writes every
-# dispatcher emit through it.  The dashboard fans those frames out to any
-# subscriber that opened /api/events on the same channel id.  This is what
-# gives the React sidebar its tool-call feed without breaking the PTY
-# child's stdio handshake with Ink.
-# ---------------------------------------------------------------------------
-
-
-@app.websocket("/api/pub")
-async def pub_ws(ws: WebSocket) -> None:
-    if not _DASHBOARD_EMBEDDED_CHAT_ENABLED:
-        await ws.close(code=4403)
-        return
-
-    token = ws.query_params.get("token", "")
-    if not hmac.compare_digest(token.encode(), _SESSION_TOKEN.encode()):
-        await ws.close(code=4401)
-        return
-
-    client_host = ws.client.host if ws.client else ""
-    if client_host and client_host not in _LOOPBACK_HOSTS:
-        await ws.close(code=4403)
-        return
-
-    channel = _channel_or_close_code(ws)
-    if not channel:
-        await ws.close(code=4400)
-        return
-
-    await ws.accept()
-
-    try:
-        while True:
-            await _broadcast_event(channel, await ws.receive_text())
-    except WebSocketDisconnect:
-        pass
-
-
-@app.websocket("/api/events")
-async def events_ws(ws: WebSocket) -> None:
-    if not _DASHBOARD_EMBEDDED_CHAT_ENABLED:
-        await ws.close(code=4403)
-        return
-
-    token = ws.query_params.get("token", "")
-    if not hmac.compare_digest(token.encode(), _SESSION_TOKEN.encode()):
-        await ws.close(code=4401)
-        return
-
-    client_host = ws.client.host if ws.client else ""
-    if client_host and client_host not in _LOOPBACK_HOSTS:
-        await ws.close(code=4403)
-        return
-
-    channel = _channel_or_close_code(ws)
-    if not channel:
-        await ws.close(code=4400)
-        return
-
-    await ws.accept()
-
-    async with _event_lock:
-        _event_channels.setdefault(channel, set()).add(ws)
-
-    try:
-        while True:
-            # Subscribers don't speak — the receive() just blocks until
-            # disconnect so the connection stays open as long as the
-            # browser holds it.
-            await ws.receive_text()
-    except WebSocketDisconnect:
-        pass
-    finally:
-        async with _event_lock:
-            subs = _event_channels.get(channel)
-
-            if subs is not None:
-                subs.discard(ws)
-
-                if not subs:
-                    _event_channels.pop(channel, None)
-
-
 def mount_spa(application: FastAPI):
     """Mount the built SPA. Falls back to index.html for client-side routing.
 
@@ -2615,10 +2284,8 @@ def mount_spa(application: FastAPI):
     def _serve_index():
         """Return index.html with the session token injected."""
         html = _index_path.read_text()
-        chat_js = "true" if _DASHBOARD_EMBEDDED_CHAT_ENABLED else "false"
         token_script = (
-            f'<script>window.__HERMES_SESSION_TOKEN__="{_SESSION_TOKEN}";'
-            f"window.__HERMES_DASHBOARD_EMBEDDED_CHAT__={chat_js};</script>"
+            f'<script>window.__HERMES_SESSION_TOKEN__="{_SESSION_TOKEN}";</script>'
         )
         html = html.replace("</head>", f"{token_script}</head>", 1)
         return HTMLResponse(
@@ -3103,23 +2770,13 @@ def _mount_plugin_api_routes():
             _log.warning("Plugin %s declares api=%s but file not found", plugin["name"], api_file_name)
             continue
         try:
-            module_name = f"hermes_dashboard_plugin_{plugin['name']}"
-            spec = importlib.util.spec_from_file_location(module_name, api_path)
+            spec = importlib.util.spec_from_file_location(
+                f"hermes_dashboard_plugin_{plugin['name']}", api_path,
+            )
             if spec is None or spec.loader is None:
                 continue
             mod = importlib.util.module_from_spec(spec)
-            # Register in sys.modules BEFORE exec_module so pydantic/FastAPI
-            # can resolve forward references (e.g. models defined in a file
-            # that uses `from __future__ import annotations`). Without this,
-            # TypeAdapter lazy-build fails at first request with
-            # "is not fully defined" because the module namespace isn't
-            # reachable by name for string-annotation resolution.
-            sys.modules[module_name] = mod
-            try:
-                spec.loader.exec_module(mod)
-            except Exception:
-                sys.modules.pop(module_name, None)
-                raise
+            spec.loader.exec_module(mod)
             router = getattr(mod, "router", None)
             if router is None:
                 _log.warning("Plugin %s api file has no 'router' attribute", plugin["name"])
@@ -3141,15 +2798,10 @@ def start_server(
     port: int = 9119,
     open_browser: bool = True,
     allow_public: bool = False,
-    *,
-    embedded_chat: bool = False,
 ):
     """Start the web UI server."""
     import uvicorn
 
-    global _DASHBOARD_EMBEDDED_CHAT_ENABLED
-    _DASHBOARD_EMBEDDED_CHAT_ENABLED = embedded_chat
-
     _LOCALHOST = ("127.0.0.1", "localhost", "::1")
     if host not in _LOCALHOST and not allow_public:
         raise SystemExit(
@@ -3165,10 +2817,7 @@ def start_server(
 
     # Record the bound host so host_header_middleware can validate incoming
     # Host headers against it. Defends against DNS rebinding (GHSA-ppp5-vxwm-4cf7).
-    # bound_port is also stashed so /api/pty can build the back-WS URL the
-    # PTY child uses to publish events to the dashboard sidebar.
     app.state.bound_host = host
-    app.state.bound_port = port
 
     if open_browser:
         import webbrowser

hermes_state.py

@@ -31,7 +31,7 @@ T = TypeVar("T")
 
 DEFAULT_DB_PATH = get_hermes_home() / "state.db"
 
-SCHEMA_VERSION = 9
+SCHEMA_VERSION = 8
 
 SCHEMA_SQL = """
 CREATE TABLE IF NOT EXISTS schema_version (
@@ -83,8 +83,7 @@ CREATE TABLE IF NOT EXISTS messages (
     reasoning TEXT,
     reasoning_content TEXT,
     reasoning_details TEXT,
-    codex_reasoning_items TEXT,
-    codex_message_items TEXT
+    codex_reasoning_items TEXT
 );
 
 CREATE TABLE IF NOT EXISTS state_meta (
@@ -357,15 +356,6 @@ class SessionDB:
                 except sqlite3.OperationalError:
                     pass  # Column already exists
                 cursor.execute("UPDATE schema_version SET version = 8")
-            if current_version < 9:
-                # v9: preserve replayable Codex assistant message ids/phases so
-                # follow-up turns can rebuild Responses API message items instead
-                # of flattening everything to plain assistant text.
-                try:
-                    cursor.execute('ALTER TABLE messages ADD COLUMN "codex_message_items" TEXT')
-                except sqlite3.OperationalError:
-                    pass  # Column already exists
-                cursor.execute("UPDATE schema_version SET version = 9")
 
         # Unique title index — always ensure it exists (safe to run after migrations
         # since the title column is guaranteed to exist at this point)
@@ -966,7 +956,6 @@ class SessionDB:
         reasoning_content: str = None,
         reasoning_details: Any = None,
         codex_reasoning_items: Any = None,
-        codex_message_items: Any = None,
     ) -> int:
         """
         Append a message to a session. Returns the message row ID.
@@ -983,10 +972,6 @@ class SessionDB:
             json.dumps(codex_reasoning_items)
             if codex_reasoning_items else None
         )
-        codex_message_items_json = (
-            json.dumps(codex_message_items)
-            if codex_message_items else None
-        )
         tool_calls_json = json.dumps(tool_calls) if tool_calls else None
 
         # Pre-compute tool call count
@@ -998,9 +983,8 @@ class SessionDB:
             cursor = conn.execute(
                 """INSERT INTO messages (session_id, role, content, tool_call_id,
                    tool_calls, tool_name, timestamp, token_count, finish_reason,
-                   reasoning, reasoning_content, reasoning_details, codex_reasoning_items,
-                   codex_message_items)
-                   VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)""",
+                   reasoning, reasoning_content, reasoning_details, codex_reasoning_items)
+                   VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)""",
                 (
                     session_id,
                     role,
@@ -1015,7 +999,6 @@ class SessionDB:
                     reasoning_content,
                     reasoning_details_json,
                     codex_items_json,
-                    codex_message_items_json,
                 ),
             )
             msg_id = cursor.lastrowid
@@ -1129,8 +1112,7 @@ class SessionDB:
         with self._lock:
             cursor = self._conn.execute(
                 "SELECT role, content, tool_call_id, tool_calls, tool_name, "
-                "reasoning, reasoning_content, reasoning_details, codex_reasoning_items, "
-                "codex_message_items "
+                "reasoning, reasoning_content, reasoning_details, codex_reasoning_items "
                 "FROM messages WHERE session_id = ? ORDER BY timestamp, id",
                 (session_id,),
             )
@@ -1168,12 +1150,6 @@ class SessionDB:
                     except (json.JSONDecodeError, TypeError):
                         logger.warning("Failed to deserialize codex_reasoning_items, falling back to None")
                         msg["codex_reasoning_items"] = None
-                if row["codex_message_items"]:
-                    try:
-                        msg["codex_message_items"] = json.loads(row["codex_message_items"])
-                    except (json.JSONDecodeError, TypeError):
-                        logger.warning("Failed to deserialize codex_message_items, falling back to None")
-                        msg["codex_message_items"] = None
             messages.append(msg)
         return messages
 

model_tools.py

@@ -24,7 +24,6 @@ import json
 import asyncio
 import logging
 import threading
-import time
 from typing import Dict, Any, List, Optional, Tuple
 
 from tools.registry import discover_builtin_tools, registry
@@ -289,34 +288,30 @@ def get_tool_definitions(
                 filtered_tools[i] = {"type": "function", "function": dynamic_schema}
                 break
 
-    # Rebuild discord / discord_admin schemas based on the bot's privileged
-    # intents (detected from GET /applications/@me) and the user's action
-    # allowlist in config.  Hides actions the bot's intents don't support so
-    # the model never attempts them, and annotates fetch_messages when the
+    # Rebuild discord_server schema based on the bot's privileged intents
+    # (detected from GET /applications/@me) and the user's action allowlist
+    # in config.  Hides actions the bot's intents don't support so the
+    # model never attempts them, and annotates fetch_messages when the
     # MESSAGE_CONTENT intent is missing.
-    _discord_schema_fns = {
-        "discord": "get_dynamic_schema_core",
-        "discord_admin": "get_dynamic_schema_admin",
-    }
-    for discord_tool_name in _discord_schema_fns:
-        if discord_tool_name in available_tool_names:
-            try:
-                from tools import discord_tool as _dt
-                schema_fn = getattr(_dt, _discord_schema_fns[discord_tool_name])
-                dynamic = schema_fn()
-            except Exception:
-                dynamic = None
-            if dynamic is None:
-                filtered_tools = [
-                    t for t in filtered_tools
-                    if t.get("function", {}).get("name") != discord_tool_name
-                ]
-                available_tool_names.discard(discord_tool_name)
-            else:
-                for i, td in enumerate(filtered_tools):
-                    if td.get("function", {}).get("name") == discord_tool_name:
-                        filtered_tools[i] = {"type": "function", "function": dynamic}
-                        break
+    if "discord_server" in available_tool_names:
+        try:
+            from tools.discord_tool import get_dynamic_schema
+            dynamic = get_dynamic_schema()
+        except Exception:  # pragma: no cover — defensive, fall back to static
+            dynamic = None
+        if dynamic is None:
+            # Tool filtered out entirely (empty allowlist or detection disabled
+            # the only remaining actions).  Drop it from the schema list.
+            filtered_tools = [
+                t for t in filtered_tools
+                if t.get("function", {}).get("name") != "discord_server"
+            ]
+            available_tool_names.discard("discord_server")
+        else:
+            for i, td in enumerate(filtered_tools):
+                if td.get("function", {}).get("name") == "discord_server":
+                    filtered_tools[i] = {"type": "function", "function": dynamic}
+                    break
 
     # Strip web tool cross-references from browser_navigate description when
     # web_search / web_extract are not available.  The static schema says
@@ -469,9 +464,9 @@ def _coerce_number(value: str, integer_only: bool = False):
         f = float(value)
     except (ValueError, OverflowError):
         return value
-    # Guard against inf/nan — not JSON-serializable, keep original string
+    # Guard against inf/nan before int() conversion
     if f != f or f == float("inf") or f == float("-inf"):
-        return value
+        return f
     # If it looks like an integer (no fractional part), return int
     if f == int(f):
         return int(f)
@@ -568,14 +563,6 @@ def handle_function_call(
             except Exception:
                 pass  # file_tools may not be loaded yet
 
-        # Measure tool dispatch latency so post_tool_call and
-        # transform_tool_result hooks can observe per-tool duration.
-        # Inspired by Claude Code 2.1.119, which added ``duration_ms`` to
-        # PostToolUse hook inputs so plugin authors can build latency
-        # dashboards, budget alerts, and regression canaries without having
-        # to wrap every tool manually.  We use monotonic() so the value is
-        # unaffected by wall-clock adjustments during the call.
-        _dispatch_start = time.monotonic()
         if function_name == "execute_code":
             # Prefer the caller-provided list so subagents can't overwrite
             # the parent's tool set via the process-global.
@@ -591,7 +578,6 @@ def handle_function_call(
                 task_id=task_id,
                 user_task=user_task,
             )
-        duration_ms = int((time.monotonic() - _dispatch_start) * 1000)
 
         try:
             from hermes_cli.plugins import invoke_hook
@@ -603,7 +589,6 @@ def handle_function_call(
                 task_id=task_id or "",
                 session_id=session_id or "",
                 tool_call_id=tool_call_id or "",
-                duration_ms=duration_ms,
             )
         except Exception:
             pass
@@ -624,7 +609,6 @@ def handle_function_call(
                 task_id=task_id or "",
                 session_id=session_id or "",
                 tool_call_id=tool_call_id or "",
-                duration_ms=duration_ms,
             )
             for hook_result in hook_results:
                 if isinstance(hook_result, str):

nix/lib.nix

@@ -156,7 +156,7 @@
       for entry in "''${ENTRIES[@]}"; do
         IFS=":" read -r ATTR FOLDER NIX_FILE <<< "$entry"
         echo "==> .#$ATTR ($FOLDER -> $NIX_FILE)"
-        OUTPUT=$(nix build ".#$ATTR.npmDeps" --no-link --rebuild --print-build-logs 2>&1)
+        OUTPUT=$(nix build ".#$ATTR.npmDeps" --no-link --print-build-logs 2>&1)
         STATUS=$?
         if [ "$STATUS" -eq 0 ]; then
           echo "    ok"

nix/web.nix

@@ -4,7 +4,7 @@ let
   src = ../web;
   npmDeps = pkgs.fetchNpmDeps {
     inherit src;
-    hash = "sha256-4Z8KQ69QhO83X6zff+5urWBv6MME686MhTTMdwSl65o=";
+    hash = "sha256-TS/vrCHbdvXkPcAPxImKzAd2pdDCrKlgYZkXBMQ+TEg=";
   };
 
   npm = hermesNpmLib.mkNpmPassthru { folder = "web"; attr = "web"; pname = "hermes-web"; };

plugins/example-dashboard/dashboard/dist/index.js

@@ -91,29 +91,4 @@
 
   // Register this plugin — the dashboard picks it up automatically.
   window.__HERMES_PLUGINS__.register("example", ExamplePage);
-
-  // ─────────────────────────────────────────────────────────────────────
-  // Page-scoped slot demo: inject a small banner at the top of /sessions.
-  //
-  // Built-in pages expose named slots (<page>:top, <page>:bottom) that
-  // plugins can populate without overriding the whole route. The
-  // manifest lists the slots we use in its `slots` array so the shell
-  // knows to render <PluginSlot name="sessions:top" /> there.
-  // ─────────────────────────────────────────────────────────────────────
-  function SessionsTopBanner() {
-    return React.createElement(Card, {
-      className: "border-dashed",
-    },
-      React.createElement(CardContent, { className: "flex items-center gap-3 py-2" },
-        React.createElement(Badge, { variant: "outline" }, "Example"),
-        React.createElement("span", {
-          className: "text-xs text-muted-foreground",
-        }, "This banner was injected into the Sessions page by the example plugin via the ",
-          React.createElement("code", { className: "font-courier" }, "sessions:top"),
-          " slot."),
-      ),
-    );
-  }
-
-  window.__HERMES_PLUGINS__.registerSlot("example", "sessions:top", SessionsTopBanner);
 })();

plugins/example-dashboard/dashboard/manifest.json

@@ -8,7 +8,6 @@
     "path": "/example",
     "position": "after:skills"
   },
-  "slots": ["sessions:top"],
   "entry": "dist/index.js",
   "api": "plugin_api.py"
 }

plugins/kanban/dashboard/dist/style.css

@@ -1,752 +0,0 @@
-/*
- * Hermes Kanban — dashboard plugin styles.
- *
- * All colors reference theme CSS vars so the board reskins with the
- * active dashboard theme. No hardcoded palette.
- */
-
-.hermes-kanban {
-  width: 100%;
-}
-
-/* ---- Columns layout -------------------------------------------------- */
-
-.hermes-kanban-columns {
-  display: grid;
-  grid-template-columns: repeat(auto-fit, minmax(260px, 1fr));
-  gap: 0.75rem;
-  align-items: start;
-}
-
-.hermes-kanban-column {
-  display: flex;
-  flex-direction: column;
-  background: color-mix(in srgb, var(--color-card) 85%, transparent);
-  border: 1px solid var(--color-border);
-  border-radius: var(--radius);
-  padding: 0.5rem;
-  min-height: 200px;
-  max-height: calc(100vh - 220px);
-  transition: border-color 120ms ease, background-color 120ms ease;
-}
-
-.hermes-kanban-column--drop {
-  border-color: var(--color-ring);
-  background: color-mix(in srgb, var(--color-ring) 8%, var(--color-card));
-}
-
-.hermes-kanban-column-header {
-  display: flex;
-  align-items: center;
-  gap: 0.5rem;
-  padding: 0.25rem 0.25rem 0.35rem;
-  font-weight: 600;
-  font-size: 0.85rem;
-  color: var(--color-foreground);
-}
-
-.hermes-kanban-column-label {
-  flex: 1;
-  letter-spacing: 0.01em;
-}
-
-.hermes-kanban-column-count {
-  font-variant-numeric: tabular-nums;
-  color: var(--color-muted-foreground);
-  font-size: 0.75rem;
-  font-weight: 500;
-}
-
-.hermes-kanban-column-add {
-  appearance: none;
-  background: transparent;
-  border: 1px solid var(--color-border);
-  color: var(--color-foreground);
-  border-radius: var(--radius-sm, 0.25rem);
-  width: 22px;
-  height: 22px;
-  line-height: 1;
-  font-size: 1rem;
-  cursor: pointer;
-}
-.hermes-kanban-column-add:hover {
-  background: color-mix(in srgb, var(--color-foreground) 8%, transparent);
-}
-
-.hermes-kanban-column-sub {
-  padding: 0 0.25rem 0.5rem;
-  font-size: 0.7rem;
-  color: var(--color-muted-foreground);
-  border-bottom: 1px solid color-mix(in srgb, var(--color-border) 60%, transparent);
-  margin-bottom: 0.5rem;
-}
-
-.hermes-kanban-column-body {
-  display: flex;
-  flex-direction: column;
-  gap: 0.45rem;
-  overflow-y: auto;
-  padding-right: 0.1rem;
-}
-
-.hermes-kanban-empty {
-  padding: 1.5rem 0.5rem;
-  text-align: center;
-  font-size: 0.75rem;
-  color: var(--color-muted-foreground);
-  border: 1px dashed color-mix(in srgb, var(--color-border) 70%, transparent);
-  border-radius: var(--radius-sm, 0.25rem);
-}
-
-/* ---- Status dots ----------------------------------------------------- */
-
-.hermes-kanban-dot {
-  display: inline-block;
-  width: 0.5rem;
-  height: 0.5rem;
-  border-radius: 999px;
-  background: var(--color-muted-foreground);
-}
-.hermes-kanban-dot-triage   { background: #b47dd6; }  /* lilac — fresh/unspecified */
-.hermes-kanban-dot-todo     { background: var(--color-muted-foreground); }
-.hermes-kanban-dot-ready    { background: #d4b348; }  /* amber */
-.hermes-kanban-dot-running  { background: #3fb97d; }  /* green */
-.hermes-kanban-dot-blocked  { background: var(--color-destructive, #d14a4a); }
-.hermes-kanban-dot-done     { background: #4a8cd1; }  /* blue */
-.hermes-kanban-dot-archived { background: var(--color-border); }
-
-/* ---- Progress pill (N/M child tasks done) --------------------------- */
-
-.hermes-kanban-progress {
-  font-family: var(--font-mono, ui-monospace, monospace);
-  font-size: 0.62rem;
-  padding: 0.05rem 0.35rem;
-  border-radius: 999px;
-  background: color-mix(in srgb, var(--color-foreground) 8%, transparent);
-  border: 1px solid color-mix(in srgb, var(--color-border) 80%, transparent);
-  color: var(--color-muted-foreground);
-  letter-spacing: 0.02em;
-}
-.hermes-kanban-progress--full {
-  background: color-mix(in srgb, #3fb97d 22%, transparent);
-  border-color: color-mix(in srgb, #3fb97d 45%, transparent);
-  color: var(--color-foreground);
-}
-
-/* ---- Lanes (per-profile sub-grouping inside Running) ---------------- */
-
-.hermes-kanban-lane {
-  display: flex;
-  flex-direction: column;
-  gap: 0.35rem;
-  padding: 0.25rem 0 0.35rem;
-  border-top: 1px dashed color-mix(in srgb, var(--color-border) 70%, transparent);
-}
-.hermes-kanban-lane:first-child {
-  border-top: 0;
-  padding-top: 0;
-}
-.hermes-kanban-lane-head {
-  display: flex;
-  align-items: center;
-  gap: 0.4rem;
-  font-size: 0.65rem;
-  text-transform: uppercase;
-  letter-spacing: 0.08em;
-  color: var(--color-muted-foreground);
-  padding: 0 0.1rem;
-}
-.hermes-kanban-lane-name {
-  font-weight: 600;
-  font-family: var(--font-mono, ui-monospace, monospace);
-}
-.hermes-kanban-lane-count {
-  margin-left: auto;
-  font-variant-numeric: tabular-nums;
-}
-
-/* ---- Card ------------------------------------------------------------ */
-
-.hermes-kanban-card {
-  cursor: grab;
-  transition: transform 100ms ease, box-shadow 100ms ease;
-}
-.hermes-kanban-card:hover {
-  box-shadow: 0 1px 0 0 var(--color-ring) inset, 0 0 0 1px var(--color-ring) inset;
-}
-.hermes-kanban-card:active {
-  cursor: grabbing;
-  transform: scale(0.995);
-}
-
-.hermes-kanban-card-content {
-  padding: 0.5rem 0.6rem !important;
-  display: flex;
-  flex-direction: column;
-  gap: 0.3rem;
-}
-
-.hermes-kanban-card-row {
-  display: flex;
-  align-items: center;
-  gap: 0.35rem;
-  flex-wrap: wrap;
-}
-
-.hermes-kanban-card-id {
-  font-family: var(--font-mono, ui-monospace, monospace);
-  font-size: 0.65rem;
-  color: var(--color-muted-foreground);
-  letter-spacing: 0.03em;
-}
-
-.hermes-kanban-card-title {
-  font-size: 0.85rem;
-  font-weight: 500;
-  line-height: 1.3;
-  color: var(--color-foreground);
-  word-break: break-word;
-}
-
-.hermes-kanban-card-meta {
-  font-size: 0.7rem;
-  color: var(--color-muted-foreground);
-  gap: 0.55rem;
-}
-
-.hermes-kanban-priority {
-  font-size: 0.6rem !important;
-  padding: 0.05rem 0.3rem !important;
-  background: color-mix(in srgb, var(--color-ring) 18%, transparent);
-  color: var(--color-foreground);
-  border: 1px solid color-mix(in srgb, var(--color-ring) 40%, transparent);
-}
-
-.hermes-kanban-tag {
-  font-size: 0.6rem !important;
-  padding: 0.05rem 0.3rem !important;
-}
-
-.hermes-kanban-assignee {
-  font-weight: 500;
-  color: color-mix(in srgb, var(--color-foreground) 80%, var(--color-muted-foreground));
-}
-.hermes-kanban-unassigned {
-  font-style: italic;
-}
-.hermes-kanban-ago {
-  margin-left: auto;
-}
-
-/* ---- Inline create --------------------------------------------------- */
-
-.hermes-kanban-inline-create {
-  display: flex;
-  flex-direction: column;
-  gap: 0.35rem;
-  padding: 0.5rem;
-  margin-bottom: 0.5rem;
-  background: color-mix(in srgb, var(--color-card) 70%, transparent);
-  border: 1px dashed var(--color-border);
-  border-radius: var(--radius-sm, 0.25rem);
-}
-
-/* ---- Drawer (task detail side panel) --------------------------------- */
-
-.hermes-kanban-drawer-shade {
-  position: fixed;
-  inset: 0;
-  background: rgba(0, 0, 0, 0.45);
-  z-index: 60;
-  display: flex;
-  justify-content: flex-end;
-}
-
-.hermes-kanban-drawer {
-  width: min(480px, 92vw);
-  height: 100vh;
-  background: var(--color-card);
-  border-left: 1px solid var(--color-border);
-  display: flex;
-  flex-direction: column;
-  box-shadow: -4px 0 18px rgba(0, 0, 0, 0.35);
-  animation: hermes-kanban-drawer-in 180ms ease-out;
-}
-
-@keyframes hermes-kanban-drawer-in {
-  from { transform: translateX(100%); opacity: 0.3; }
-  to   { transform: translateX(0);    opacity: 1; }
-}
-
-.hermes-kanban-drawer-head {
-  display: flex;
-  align-items: center;
-  justify-content: space-between;
-  padding: 0.6rem 0.8rem;
-  border-bottom: 1px solid var(--color-border);
-  font-family: var(--font-mono, ui-monospace, monospace);
-}
-
-.hermes-kanban-drawer-close {
-  appearance: none;
-  background: transparent;
-  border: 0;
-  color: var(--color-muted-foreground);
-  font-size: 1.25rem;
-  line-height: 1;
-  cursor: pointer;
-  padding: 0 0.25rem;
-}
-.hermes-kanban-drawer-close:hover { color: var(--color-foreground); }
-
-.hermes-kanban-drawer-body {
-  flex: 1;
-  overflow-y: auto;
-  padding: 0.9rem;
-  display: flex;
-  flex-direction: column;
-  gap: 0.85rem;
-}
-
-.hermes-kanban-drawer-title {
-  display: flex;
-  align-items: center;
-  gap: 0.5rem;
-  font-size: 1rem;
-  font-weight: 600;
-}
-
-.hermes-kanban-drawer-meta {
-  display: flex;
-  flex-direction: column;
-  gap: 0.15rem;
-  padding: 0.5rem 0.6rem;
-  background: color-mix(in srgb, var(--color-foreground) 4%, transparent);
-  border: 1px solid var(--color-border);
-  border-radius: var(--radius-sm, 0.25rem);
-}
-
-.hermes-kanban-meta-row {
-  display: flex;
-  gap: 0.5rem;
-  font-size: 0.72rem;
-}
-.hermes-kanban-meta-label {
-  width: 92px;
-  color: var(--color-muted-foreground);
-}
-.hermes-kanban-meta-value {
-  color: var(--color-foreground);
-  word-break: break-word;
-}
-
-.hermes-kanban-actions {
-  display: flex;
-  flex-wrap: wrap;
-  gap: 0.3rem;
-}
-
-.hermes-kanban-section {
-  display: flex;
-  flex-direction: column;
-  gap: 0.35rem;
-}
-
-.hermes-kanban-section-head {
-  font-size: 0.72rem;
-  font-weight: 600;
-  text-transform: uppercase;
-  letter-spacing: 0.07em;
-  color: var(--color-muted-foreground);
-}
-
-.hermes-kanban-pre {
-  margin: 0;
-  padding: 0.45rem 0.55rem;
-  white-space: pre-wrap;
-  word-break: break-word;
-  background: color-mix(in srgb, var(--color-foreground) 4%, transparent);
-  border: 1px solid var(--color-border);
-  border-radius: var(--radius-sm, 0.25rem);
-  font-family: var(--font-mono, ui-monospace, monospace);
-  font-size: 0.72rem;
-  color: var(--color-foreground);
-}
-
-.hermes-kanban-comment {
-  border-left: 2px solid color-mix(in srgb, var(--color-ring) 35%, transparent);
-  padding-left: 0.5rem;
-  display: flex;
-  flex-direction: column;
-  gap: 0.2rem;
-}
-
-.hermes-kanban-comment-head {
-  display: flex;
-  gap: 0.5rem;
-  font-size: 0.7rem;
-}
-.hermes-kanban-comment-author {
-  font-weight: 600;
-  color: var(--color-foreground);
-}
-.hermes-kanban-comment-ago {
-  color: var(--color-muted-foreground);
-}
-
-.hermes-kanban-event {
-  display: flex;
-  gap: 0.5rem;
-  font-size: 0.7rem;
-  color: var(--color-muted-foreground);
-  font-family: var(--font-mono, ui-monospace, monospace);
-}
-.hermes-kanban-event-kind {
-  color: var(--color-foreground);
-  min-width: 6rem;
-}
-.hermes-kanban-event-payload {
-  color: var(--color-muted-foreground);
-  overflow: hidden;
-  text-overflow: ellipsis;
-  white-space: nowrap;
-  max-width: 280px;
-}
-
-.hermes-kanban-drawer-comment-row {
-  display: flex;
-  gap: 0.4rem;
-  padding: 0.55rem 0.75rem;
-  border-top: 1px solid var(--color-border);
-  background: color-mix(in srgb, var(--color-card) 90%, transparent);
-}
-
-.hermes-kanban-count {
-  display: inline-flex;
-  gap: 0.2rem;
-  align-items: center;
-}
-
-/* ---- Selection chrome ----------------------------------------------- */
-
-.hermes-kanban-card--selected :where(.hermes-kanban-card-content) {
-  box-shadow: 0 0 0 2px var(--color-ring) inset,
-              0 0 0 1px var(--color-ring) inset;
-  background: color-mix(in srgb, var(--color-ring) 6%, var(--color-card));
-}
-
-.hermes-kanban-card-check {
-  width: 0.85rem;
-  height: 0.85rem;
-  margin: 0;
-  cursor: pointer;
-  accent-color: var(--color-ring);
-}
-
-/* ---- Bulk action bar ------------------------------------------------ */
-
-.hermes-kanban-bulk {
-  display: flex;
-  align-items: center;
-  gap: 0.5rem;
-  padding: 0.4rem 0.75rem;
-  background: color-mix(in srgb, var(--color-ring) 10%, var(--color-card));
-  border: 1px solid color-mix(in srgb, var(--color-ring) 40%, var(--color-border));
-  border-radius: var(--radius-sm, 0.25rem);
-  flex-wrap: wrap;
-}
-.hermes-kanban-bulk-count {
-  font-weight: 600;
-  font-size: 0.75rem;
-  padding-right: 0.25rem;
-}
-.hermes-kanban-bulk-btn {
-  height: 1.7rem !important;
-  padding: 0 0.5rem !important;
-  font-size: 0.7rem !important;
-  border: 1px solid var(--color-border);
-  cursor: pointer;
-}
-.hermes-kanban-bulk-btn:hover {
-  background: color-mix(in srgb, var(--color-foreground) 8%, transparent);
-}
-.hermes-kanban-bulk-reassign {
-  display: flex;
-  align-items: center;
-  gap: 0.25rem;
-  padding-left: 0.5rem;
-  border-left: 1px solid color-mix(in srgb, var(--color-border) 70%, transparent);
-}
-
-/* ---- Dependency editor chips --------------------------------------- */
-
-.hermes-kanban-deps-row {
-  display: flex;
-  align-items: center;
-  gap: 0.5rem;
-  margin-bottom: 0.4rem;
-}
-.hermes-kanban-deps-label {
-  font-size: 0.68rem;
-  text-transform: uppercase;
-  letter-spacing: 0.08em;
-  color: var(--color-muted-foreground);
-  min-width: 4rem;
-}
-.hermes-kanban-deps-chips {
-  display: flex;
-  gap: 0.3rem;
-  flex-wrap: wrap;
-  flex: 1;
-}
-.hermes-kanban-deps-empty {
-  font-size: 0.7rem;
-  color: var(--color-muted-foreground);
-  font-style: italic;
-}
-.hermes-kanban-dep-chip {
-  display: inline-flex;
-  align-items: center;
-  gap: 0.15rem;
-  padding: 0.1rem 0.35rem;
-  background: color-mix(in srgb, var(--color-foreground) 6%, transparent);
-  border: 1px solid var(--color-border);
-  border-radius: var(--radius-sm, 0.25rem);
-  font-family: var(--font-mono, ui-monospace, monospace);
-  font-size: 0.68rem;
-  color: var(--color-foreground);
-}
-.hermes-kanban-dep-chip-x {
-  appearance: none;
-  background: transparent;
-  border: 0;
-  color: var(--color-muted-foreground);
-  cursor: pointer;
-  font-size: 0.85rem;
-  line-height: 1;
-  padding: 0 0.15rem;
-}
-.hermes-kanban-dep-chip-x:hover { color: var(--color-destructive, #d14a4a); }
-
-/* ---- Inline edit affordances --------------------------------------- */
-
-.hermes-kanban-editable {
-  cursor: pointer;
-  border-bottom: 1px dotted color-mix(in srgb, var(--color-border) 80%, transparent);
-}
-.hermes-kanban-editable:hover {
-  color: var(--color-foreground);
-  border-bottom-color: var(--color-ring);
-}
-
-.hermes-kanban-drawer-title-text {
-  cursor: pointer;
-}
-.hermes-kanban-drawer-title-text:hover {
-  text-decoration: underline;
-  text-decoration-color: var(--color-ring);
-  text-decoration-style: dotted;
-  text-underline-offset: 3px;
-}
-
-.hermes-kanban-edit-row {
-  display: flex;
-  align-items: center;
-  gap: 0.35rem;
-  width: 100%;
-}
-
-.hermes-kanban-section-head-row {
-  display: flex;
-  align-items: center;
-  justify-content: space-between;
-  gap: 0.5rem;
-}
-.hermes-kanban-edit-link {
-  appearance: none;
-  background: transparent;
-  border: 0;
-  color: var(--color-muted-foreground);
-  font-size: 0.7rem;
-  text-transform: uppercase;
-  letter-spacing: 0.05em;
-  cursor: pointer;
-  padding: 0;
-}
-.hermes-kanban-edit-link:hover { color: var(--color-ring); }
-
-.hermes-kanban-textarea {
-  width: 100%;
-  min-height: 8rem;
-  background: var(--color-card);
-  color: var(--color-foreground);
-  border: 1px solid var(--color-border);
-  border-radius: var(--radius-sm, 0.25rem);
-  padding: 0.5rem 0.6rem;
-  font-family: var(--font-mono, ui-monospace, monospace);
-  font-size: 0.8rem;
-  line-height: 1.5;
-  resize: vertical;
-}
-.hermes-kanban-textarea:focus {
-  outline: none;
-  border-color: var(--color-ring);
-  box-shadow: 0 0 0 2px color-mix(in srgb, var(--color-ring) 30%, transparent);
-}
-
-/* ---- Markdown rendering -------------------------------------------- */
-
-.hermes-kanban-md {
-  font-size: 0.8rem;
-  line-height: 1.55;
-  color: var(--color-foreground);
-}
-.hermes-kanban-md p  { margin: 0.25rem 0; }
-.hermes-kanban-md h1,
-.hermes-kanban-md h2,
-.hermes-kanban-md h3,
-.hermes-kanban-md h4 {
-  margin: 0.6rem 0 0.2rem;
-  line-height: 1.25;
-}
-.hermes-kanban-md h1 { font-size: 1.05rem; }
-.hermes-kanban-md h2 { font-size: 0.95rem; }
-.hermes-kanban-md h3 { font-size: 0.88rem; }
-.hermes-kanban-md h4 { font-size: 0.82rem; }
-.hermes-kanban-md ul {
-  margin: 0.25rem 0 0.25rem 1.1rem;
-  padding: 0;
-}
-.hermes-kanban-md li { margin: 0.1rem 0; }
-.hermes-kanban-md a {
-  color: var(--color-ring);
-  text-decoration: underline;
-}
-.hermes-kanban-md code {
-  font-family: var(--font-mono, ui-monospace, monospace);
-  font-size: 0.75rem;
-  padding: 0.05rem 0.3rem;
-  background: color-mix(in srgb, var(--color-foreground) 8%, transparent);
-  border-radius: 3px;
-}
-.hermes-kanban-md-code {
-  margin: 0.35rem 0;
-  padding: 0.5rem 0.6rem;
-  background: color-mix(in srgb, var(--color-foreground) 5%, transparent);
-  border: 1px solid var(--color-border);
-  border-radius: var(--radius-sm, 0.25rem);
-  overflow-x: auto;
-}
-.hermes-kanban-md-code code {
-  background: transparent;
-  padding: 0;
-  font-size: 0.75rem;
-  white-space: pre;
-}
-.hermes-kanban-md strong { font-weight: 600; }
-
-/* ---- Touch-drag proxy ---------------------------------------------- */
-
-.hermes-kanban-touch-proxy {
-  pointer-events: none;
-  opacity: 0.85;
-  box-shadow: 0 8px 20px rgba(0, 0, 0, 0.35);
-  transform: scale(1.02);
-  transition: none;
-}
-
-
-/* ---- Staleness tiers ------------------------------------------------ */
-
-.hermes-kanban-card--stale-amber :where(.hermes-kanban-card-content) {
-  box-shadow: 0 0 0 1px #d4b34888 inset;
-}
-.hermes-kanban-card--stale-amber:hover :where(.hermes-kanban-card-content) {
-  box-shadow: 0 0 0 2px #d4b348 inset;
-}
-.hermes-kanban-card--stale-red :where(.hermes-kanban-card-content) {
-  box-shadow: 0 0 0 1px var(--color-destructive, #d14a4a) inset,
-              0 0 8px color-mix(in srgb, var(--color-destructive, #d14a4a) 30%, transparent);
-}
-.hermes-kanban-card--stale-red:hover :where(.hermes-kanban-card-content) {
-  box-shadow: 0 0 0 2px var(--color-destructive, #d14a4a) inset,
-              0 0 10px color-mix(in srgb, var(--color-destructive, #d14a4a) 45%, transparent);
-}
-
-/* ---- Worker log pane ------------------------------------------------ */
-
-.hermes-kanban-log {
-  max-height: 340px;
-  overflow: auto;
-  white-space: pre;
-  font-size: 0.7rem;
-  line-height: 1.45;
-}
-
-
-/* ---- Run history (per-attempt log in the drawer) ------------------- */
-
-.hermes-kanban-run {
-  border-left: 2px solid var(--color-border);
-  padding: 0.35rem 0.5rem;
-  margin-bottom: 0.4rem;
-  background: color-mix(in srgb, var(--color-foreground) 3%, transparent);
-  border-radius: var(--radius-sm, 0.25rem);
-}
-.hermes-kanban-run--active  { border-left-color: #3fb97d; }
-.hermes-kanban-run--completed { border-left-color: #4a8cd1; }
-.hermes-kanban-run--ended { border-left-color: #6b7280; }  /* generic fallback when outcome is unset */
-.hermes-kanban-run--blocked { border-left-color: var(--color-destructive, #d14a4a); }
-.hermes-kanban-run--crashed,
-.hermes-kanban-run--timed_out,
-.hermes-kanban-run--gave_up,
-.hermes-kanban-run--spawn_failed {
-  border-left-color: var(--color-destructive, #d14a4a);
-  background: color-mix(in srgb, var(--color-destructive, #d14a4a) 6%, transparent);
-}
-.hermes-kanban-run--reclaimed { border-left-color: #d4b348; }
-
-.hermes-kanban-run-head {
-  display: flex;
-  align-items: center;
-  gap: 0.6rem;
-  font-size: 0.7rem;
-}
-.hermes-kanban-run-outcome {
-  font-family: var(--font-mono, ui-monospace, monospace);
-  font-weight: 600;
-  text-transform: uppercase;
-  letter-spacing: 0.05em;
-  color: var(--color-foreground);
-}
-.hermes-kanban-run-profile {
-  color: var(--color-muted-foreground);
-}
-.hermes-kanban-run-elapsed {
-  font-variant-numeric: tabular-nums;
-  color: var(--color-muted-foreground);
-}
-.hermes-kanban-run-ago {
-  margin-left: auto;
-  color: var(--color-muted-foreground);
-}
-.hermes-kanban-run-summary {
-  font-size: 0.75rem;
-  padding: 0.2rem 0 0;
-  color: var(--color-foreground);
-}
-.hermes-kanban-run-error {
-  font-size: 0.7rem;
-  color: var(--color-destructive, #d14a4a);
-  padding: 0.15rem 0 0;
-  font-family: var(--font-mono, ui-monospace, monospace);
-}
-.hermes-kanban-run-meta {
-  display: block;
-  font-size: 0.65rem;
-  padding: 0.15rem 0 0;
-  color: var(--color-muted-foreground);
-  white-space: pre-wrap;
-  word-break: break-word;
-  font-family: var(--font-mono, ui-monospace, monospace);
-}

plugins/kanban/dashboard/manifest.json

@@ -1,14 +0,0 @@
-{
-  "name": "kanban",
-  "label": "Kanban",
-  "description": "Multi-agent collaboration board — drag-drop cards across columns, read comment threads, see which profile is running what",
-  "icon": "Package",
-  "version": "1.0.0",
-  "tab": {
-    "path": "/kanban",
-    "position": "after:skills"
-  },
-  "entry": "dist/index.js",
-  "css": "dist/style.css",
-  "api": "plugin_api.py"
-}

plugins/kanban/dashboard/plugin_api.py

@@ -1,830 +0,0 @@
-"""Kanban dashboard plugin — backend API routes.
-
-Mounted at /api/plugins/kanban/ by the dashboard plugin system.
-
-This layer is intentionally thin: every handler is a small wrapper around
-``hermes_cli.kanban_db`` or a direct SQL query. Writes use the same code
-paths the CLI and gateway ``/kanban`` command use, so the three surfaces
-cannot drift.
-
-Live updates arrive via the ``/events`` WebSocket, which tails the
-append-only ``task_events`` table on a short poll interval (WAL mode lets
-reads run alongside the dispatcher's IMMEDIATE write transactions).
-
-Security note
--------------
-The dashboard's HTTP auth middleware (``web_server.auth_middleware``)
-explicitly skips ``/api/plugins/`` — plugin routes are unauthenticated by
-design because the dashboard binds to localhost by default. For the
-WebSocket we still require the session token as a ``?token=`` query
-parameter (browsers cannot set the ``Authorization`` header on an upgrade
-request), matching the established pattern used by the in-browser PTY
-bridge in ``hermes_cli/web_server.py``. If you run the dashboard with
-``--host 0.0.0.0``, every plugin route — kanban included — becomes
-reachable from the network. Don't do that on a shared host.
-"""
-
-from __future__ import annotations
-
-import asyncio
-import hmac
-import json
-import logging
-import sqlite3
-import time
-from dataclasses import asdict
-from typing import Any, Optional
-
-from fastapi import APIRouter, HTTPException, Query, WebSocket, WebSocketDisconnect, status as http_status
-from pydantic import BaseModel, Field
-
-from hermes_cli import kanban_db
-
-log = logging.getLogger(__name__)
-
-router = APIRouter()
-
-
-# ---------------------------------------------------------------------------
-# Auth helper — WebSocket only (HTTP routes live behind the dashboard's
-# existing plugin-bypass; this is documented above).
-# ---------------------------------------------------------------------------
-
-def _check_ws_token(provided: Optional[str]) -> bool:
-    """Constant-time compare against the dashboard session token.
-
-    Imported lazily so the plugin still loads in test contexts where the
-    dashboard web_server module isn't importable (e.g. the bare-FastAPI
-    test harness).
-    """
-    if not provided:
-        return False
-    try:
-        from hermes_cli import web_server as _ws
-    except Exception:
-        # No dashboard context (tests). Accept so the tail loop is still
-        # testable; in production the dashboard module always imports
-        # cleanly because it's the caller.
-        return True
-    expected = getattr(_ws, "_SESSION_TOKEN", None)
-    if not expected:
-        return True
-    return hmac.compare_digest(str(provided), str(expected))
-
-
-def _conn():
-    """Open a kanban_db connection, creating the schema on first use.
-
-    Every handler that mutates the DB goes through this so the plugin
-    self-heals on a fresh install (no user-visible "no such table"
-    error if somebody hits POST /tasks before GET /board).
-    ``init_db`` is idempotent.
-    """
-    try:
-        kanban_db.init_db()
-    except Exception as exc:
-        log.warning("kanban init_db failed: %s", exc)
-    return kanban_db.connect()
-
-
-# ---------------------------------------------------------------------------
-# Serialization helpers
-# ---------------------------------------------------------------------------
-
-# Columns shown by the dashboard, in left-to-right order. "archived" is
-# available via a filter toggle rather than a visible column.
-BOARD_COLUMNS: list[str] = [
-    "triage", "todo", "ready", "running", "blocked", "done",
-]
-
-
-def _task_dict(task: kanban_db.Task) -> dict[str, Any]:
-    d = asdict(task)
-    # Add derived age metrics so the UI can colour stale cards without
-    # computing deltas client-side.
-    d["age"] = kanban_db.task_age(task)
-    # Keep body short on list endpoints; full body comes from /tasks/:id.
-    return d
-
-
-def _event_dict(event: kanban_db.Event) -> dict[str, Any]:
-    return {
-        "id": event.id,
-        "task_id": event.task_id,
-        "kind": event.kind,
-        "payload": event.payload,
-        "created_at": event.created_at,
-        "run_id": event.run_id,
-    }
-
-
-def _comment_dict(c: kanban_db.Comment) -> dict[str, Any]:
-    return {
-        "id": c.id,
-        "task_id": c.task_id,
-        "author": c.author,
-        "body": c.body,
-        "created_at": c.created_at,
-    }
-
-
-def _run_dict(r: kanban_db.Run) -> dict[str, Any]:
-    """Serialise a Run for the drawer's Run history section."""
-    return {
-        "id": r.id,
-        "task_id": r.task_id,
-        "profile": r.profile,
-        "step_key": r.step_key,
-        "status": r.status,
-        "claim_lock": r.claim_lock,
-        "claim_expires": r.claim_expires,
-        "worker_pid": r.worker_pid,
-        "max_runtime_seconds": r.max_runtime_seconds,
-        "last_heartbeat_at": r.last_heartbeat_at,
-        "started_at": r.started_at,
-        "ended_at": r.ended_at,
-        "outcome": r.outcome,
-        "summary": r.summary,
-        "metadata": r.metadata,
-        "error": r.error,
-    }
-
-
-def _links_for(conn: sqlite3.Connection, task_id: str) -> dict[str, list[str]]:
-    """Return {'parents': [...], 'children': [...]} for a task."""
-    parents = [
-        r["parent_id"]
-        for r in conn.execute(
-            "SELECT parent_id FROM task_links WHERE child_id = ? ORDER BY parent_id",
-            (task_id,),
-        )
-    ]
-    children = [
-        r["child_id"]
-        for r in conn.execute(
-            "SELECT child_id FROM task_links WHERE parent_id = ? ORDER BY child_id",
-            (task_id,),
-        )
-    ]
-    return {"parents": parents, "children": children}
-
-
-# ---------------------------------------------------------------------------
-# GET /board
-# ---------------------------------------------------------------------------
-
-@router.get("/board")
-def get_board(
-    tenant: Optional[str] = Query(None, description="Filter to a single tenant"),
-    include_archived: bool = Query(False),
-):
-    """Return the full board grouped by status column.
-
-    ``_conn()`` auto-initializes ``kanban.db`` on first call so a fresh
-    install doesn't surface a "failed to load" error on the plugin tab.
-    """
-    conn = _conn()
-    try:
-        tasks = kanban_db.list_tasks(
-            conn, tenant=tenant, include_archived=include_archived
-        )
-        # Pre-fetch link counts per task (cheap: one query).
-        link_counts: dict[str, dict[str, int]] = {}
-        for row in conn.execute(
-            "SELECT parent_id, child_id FROM task_links"
-        ).fetchall():
-            link_counts.setdefault(row["parent_id"], {"parents": 0, "children": 0})[
-                "children"
-            ] += 1
-            link_counts.setdefault(row["child_id"], {"parents": 0, "children": 0})[
-                "parents"
-            ] += 1
-
-        # Comment + event counts (both cheap aggregates).
-        comment_counts: dict[str, int] = {
-            r["task_id"]: r["n"]
-            for r in conn.execute(
-                "SELECT task_id, COUNT(*) AS n FROM task_comments GROUP BY task_id"
-            )
-        }
-
-        # Progress rollup: for each parent, how many children are done / total.
-        # One pass over task_links joined with child status — cheaper than
-        # N per-task queries and the plugin uses it to render "N/M".
-        progress: dict[str, dict[str, int]] = {}
-        for row in conn.execute(
-            "SELECT l.parent_id AS pid, t.status AS cstatus "
-            "FROM task_links l JOIN tasks t ON t.id = l.child_id"
-        ).fetchall():
-            p = progress.setdefault(row["pid"], {"done": 0, "total": 0})
-            p["total"] += 1
-            if row["cstatus"] == "done":
-                p["done"] += 1
-
-        latest_event_id = conn.execute(
-            "SELECT COALESCE(MAX(id), 0) AS m FROM task_events"
-        ).fetchone()["m"]
-
-        columns: dict[str, list[dict]] = {c: [] for c in BOARD_COLUMNS}
-        if include_archived:
-            columns["archived"] = []
-
-        for t in tasks:
-            d = _task_dict(t)
-            d["link_counts"] = link_counts.get(t.id, {"parents": 0, "children": 0})
-            d["comment_count"] = comment_counts.get(t.id, 0)
-            d["progress"] = progress.get(t.id)  # None when the task has no children
-            col = t.status if t.status in columns else "todo"
-            columns[col].append(d)
-
-        # Stable per-column ordering already applied by list_tasks
-        # (priority DESC, created_at ASC), keep as-is.
-
-        # List of known tenants for the UI filter dropdown.
-        tenants = [
-            r["tenant"]
-            for r in conn.execute(
-                "SELECT DISTINCT tenant FROM tasks WHERE tenant IS NOT NULL ORDER BY tenant"
-            )
-        ]
-        # List of distinct assignees for the lane-by-profile sub-grouping.
-        assignees = [
-            r["assignee"]
-            for r in conn.execute(
-                "SELECT DISTINCT assignee FROM tasks WHERE assignee IS NOT NULL "
-                "AND status != 'archived' ORDER BY assignee"
-            )
-        ]
-
-        return {
-            "columns": [
-                {"name": name, "tasks": columns[name]} for name in columns.keys()
-            ],
-            "tenants": tenants,
-            "assignees": assignees,
-            "latest_event_id": int(latest_event_id),
-            "now": int(time.time()),
-        }
-    finally:
-        conn.close()
-
-
-# ---------------------------------------------------------------------------
-# GET /tasks/:id
-# ---------------------------------------------------------------------------
-
-@router.get("/tasks/{task_id}")
-def get_task(task_id: str):
-    conn = _conn()
-    try:
-        task = kanban_db.get_task(conn, task_id)
-        if task is None:
-            raise HTTPException(status_code=404, detail=f"task {task_id} not found")
-        return {
-            "task": _task_dict(task),
-            "comments": [_comment_dict(c) for c in kanban_db.list_comments(conn, task_id)],
-            "events": [_event_dict(e) for e in kanban_db.list_events(conn, task_id)],
-            "links": _links_for(conn, task_id),
-            "runs": [_run_dict(r) for r in kanban_db.list_runs(conn, task_id)],
-        }
-    finally:
-        conn.close()
-
-
-# ---------------------------------------------------------------------------
-# POST /tasks
-# ---------------------------------------------------------------------------
-
-class CreateTaskBody(BaseModel):
-    title: str
-    body: Optional[str] = None
-    assignee: Optional[str] = None
-    tenant: Optional[str] = None
-    priority: int = 0
-    workspace_kind: str = "scratch"
-    workspace_path: Optional[str] = None
-    parents: list[str] = Field(default_factory=list)
-    triage: bool = False
-    idempotency_key: Optional[str] = None
-    max_runtime_seconds: Optional[int] = None
-    skills: Optional[list[str]] = None
-
-
-@router.post("/tasks")
-def create_task(payload: CreateTaskBody):
-    conn = _conn()
-    try:
-        task_id = kanban_db.create_task(
-            conn,
-            title=payload.title,
-            body=payload.body,
-            assignee=payload.assignee,
-            created_by="dashboard",
-            workspace_kind=payload.workspace_kind,
-            workspace_path=payload.workspace_path,
-            tenant=payload.tenant,
-            priority=payload.priority,
-            parents=payload.parents,
-            triage=payload.triage,
-            idempotency_key=payload.idempotency_key,
-            max_runtime_seconds=payload.max_runtime_seconds,
-            skills=payload.skills,
-        )
-        task = kanban_db.get_task(conn, task_id)
-        return {"task": _task_dict(task) if task else None}
-    except ValueError as e:
-        raise HTTPException(status_code=400, detail=str(e))
-    finally:
-        conn.close()
-
-
-# ---------------------------------------------------------------------------
-# PATCH /tasks/:id  (status / assignee / priority / title / body)
-# ---------------------------------------------------------------------------
-
-class UpdateTaskBody(BaseModel):
-    status: Optional[str] = None
-    assignee: Optional[str] = None
-    priority: Optional[int] = None
-    title: Optional[str] = None
-    body: Optional[str] = None
-    result: Optional[str] = None
-    block_reason: Optional[str] = None
-    # Structured handoff fields — forwarded to complete_task when status
-    # transitions to 'done'. Dashboard parity with ``hermes kanban
-    # complete --summary ... --metadata ...``.
-    summary: Optional[str] = None
-    metadata: Optional[dict] = None
-
-
-@router.patch("/tasks/{task_id}")
-def update_task(task_id: str, payload: UpdateTaskBody):
-    conn = _conn()
-    try:
-        task = kanban_db.get_task(conn, task_id)
-        if task is None:
-            raise HTTPException(status_code=404, detail=f"task {task_id} not found")
-
-        # --- assignee ----------------------------------------------------
-        if payload.assignee is not None:
-            try:
-                ok = kanban_db.assign_task(
-                    conn, task_id, payload.assignee or None,
-                )
-            except RuntimeError as e:
-                raise HTTPException(status_code=409, detail=str(e))
-            if not ok:
-                raise HTTPException(status_code=404, detail="task not found")
-
-        # --- status -------------------------------------------------------
-        if payload.status is not None:
-            s = payload.status
-            ok = True
-            if s == "done":
-                ok = kanban_db.complete_task(
-                    conn, task_id,
-                    result=payload.result,
-                    summary=payload.summary,
-                    metadata=payload.metadata,
-                )
-            elif s == "blocked":
-                ok = kanban_db.block_task(conn, task_id, reason=payload.block_reason)
-            elif s == "ready":
-                # Re-open a blocked task, or just an explicit status set.
-                current = kanban_db.get_task(conn, task_id)
-                if current and current.status == "blocked":
-                    ok = kanban_db.unblock_task(conn, task_id)
-                else:
-                    # Direct status write for drag-drop (todo -> ready etc).
-                    ok = _set_status_direct(conn, task_id, "ready")
-            elif s == "archived":
-                ok = kanban_db.archive_task(conn, task_id)
-            elif s in ("todo", "running", "triage"):
-                ok = _set_status_direct(conn, task_id, s)
-            else:
-                raise HTTPException(status_code=400, detail=f"unknown status: {s}")
-            if not ok:
-                raise HTTPException(
-                    status_code=409,
-                    detail=f"status transition to {s!r} not valid from current state",
-                )
-
-        # --- priority -----------------------------------------------------
-        if payload.priority is not None:
-            with kanban_db.write_txn(conn):
-                conn.execute(
-                    "UPDATE tasks SET priority = ? WHERE id = ?",
-                    (int(payload.priority), task_id),
-                )
-                conn.execute(
-                    "INSERT INTO task_events (task_id, kind, payload, created_at) "
-                    "VALUES (?, 'reprioritized', ?, ?)",
-                    (task_id, json.dumps({"priority": int(payload.priority)}),
-                     int(time.time())),
-                )
-
-        # --- title / body -------------------------------------------------
-        if payload.title is not None or payload.body is not None:
-            with kanban_db.write_txn(conn):
-                sets, vals = [], []
-                if payload.title is not None:
-                    if not payload.title.strip():
-                        raise HTTPException(status_code=400, detail="title cannot be empty")
-                    sets.append("title = ?")
-                    vals.append(payload.title.strip())
-                if payload.body is not None:
-                    sets.append("body = ?")
-                    vals.append(payload.body)
-                vals.append(task_id)
-                conn.execute(
-                    f"UPDATE tasks SET {', '.join(sets)} WHERE id = ?", vals,
-                )
-                conn.execute(
-                    "INSERT INTO task_events (task_id, kind, payload, created_at) "
-                    "VALUES (?, 'edited', NULL, ?)",
-                    (task_id, int(time.time())),
-                )
-
-        updated = kanban_db.get_task(conn, task_id)
-        return {"task": _task_dict(updated) if updated else None}
-    finally:
-        conn.close()
-
-
-def _set_status_direct(
-    conn: sqlite3.Connection, task_id: str, new_status: str,
-) -> bool:
-    """Direct status write for drag-drop moves that aren't covered by the
-    structured complete/block/unblock/archive verbs (e.g. todo<->ready,
-    running<->ready). Appends a ``status`` event row for the live feed.
-
-    When this transitions OFF ``running`` to anything other than the
-    terminal verbs above (which own their own run closing), we close the
-    active run with outcome='reclaimed' so attempt history isn't
-    orphaned. ``running -> ready`` via drag-drop is the common case
-    (user yanking a stuck worker back to the queue).
-    """
-    with kanban_db.write_txn(conn):
-        # Snapshot current state so we know whether to close a run.
-        prev = conn.execute(
-            "SELECT status, current_run_id FROM tasks WHERE id = ?",
-            (task_id,),
-        ).fetchone()
-        if prev is None:
-            return False
-        was_running = prev["status"] == "running"
-
-        cur = conn.execute(
-            "UPDATE tasks SET status = ?, "
-            "  claim_lock = CASE WHEN ? = 'running' THEN claim_lock ELSE NULL END, "
-            "  claim_expires = CASE WHEN ? = 'running' THEN claim_expires ELSE NULL END, "
-            "  worker_pid = CASE WHEN ? = 'running' THEN worker_pid ELSE NULL END "
-            "WHERE id = ?",
-            (new_status, new_status, new_status, new_status, task_id),
-        )
-        if cur.rowcount != 1:
-            return False
-        run_id = None
-        if was_running and new_status != "running" and prev["current_run_id"]:
-            run_id = kanban_db._end_run(
-                conn, task_id,
-                outcome="reclaimed", status="reclaimed",
-                summary=f"status changed to {new_status} (dashboard/direct)",
-            )
-        conn.execute(
-            "INSERT INTO task_events (task_id, run_id, kind, payload, created_at) "
-            "VALUES (?, ?, 'status', ?, ?)",
-            (task_id, run_id, json.dumps({"status": new_status}), int(time.time())),
-        )
-    # If we re-opened something, children may have gone stale.
-    if new_status in ("done", "ready"):
-        kanban_db.recompute_ready(conn)
-    return True
-
-
-# ---------------------------------------------------------------------------
-# Comments
-# ---------------------------------------------------------------------------
-
-class CommentBody(BaseModel):
-    body: str
-    author: Optional[str] = "dashboard"
-
-
-@router.post("/tasks/{task_id}/comments")
-def add_comment(task_id: str, payload: CommentBody):
-    if not payload.body.strip():
-        raise HTTPException(status_code=400, detail="body is required")
-    conn = _conn()
-    try:
-        if kanban_db.get_task(conn, task_id) is None:
-            raise HTTPException(status_code=404, detail=f"task {task_id} not found")
-        kanban_db.add_comment(
-            conn, task_id, author=payload.author or "dashboard", body=payload.body,
-        )
-        return {"ok": True}
-    finally:
-        conn.close()
-
-
-# ---------------------------------------------------------------------------
-# Links
-# ---------------------------------------------------------------------------
-
-class LinkBody(BaseModel):
-    parent_id: str
-    child_id: str
-
-
-@router.post("/links")
-def add_link(payload: LinkBody):
-    conn = _conn()
-    try:
-        kanban_db.link_tasks(conn, payload.parent_id, payload.child_id)
-        return {"ok": True}
-    except ValueError as e:
-        raise HTTPException(status_code=400, detail=str(e))
-    finally:
-        conn.close()
-
-
-@router.delete("/links")
-def delete_link(parent_id: str = Query(...), child_id: str = Query(...)):
-    conn = _conn()
-    try:
-        ok = kanban_db.unlink_tasks(conn, parent_id, child_id)
-        return {"ok": bool(ok)}
-    finally:
-        conn.close()
-
-
-# ---------------------------------------------------------------------------
-# Bulk actions (multi-select on the board)
-# ---------------------------------------------------------------------------
-
-class BulkTaskBody(BaseModel):
-    ids: list[str]
-    status: Optional[str] = None
-    assignee: Optional[str] = None  # "" or None = unassign
-    priority: Optional[int] = None
-    archive: bool = False
-
-
-@router.post("/tasks/bulk")
-def bulk_update(payload: BulkTaskBody):
-    """Apply the same patch to every id in ``payload.ids``.
-
-    This is an *independent* iteration — per-task failures don't abort
-    siblings. Returns per-id outcome so the UI can surface partials.
-    """
-    ids = [i for i in (payload.ids or []) if i]
-    if not ids:
-        raise HTTPException(status_code=400, detail="ids is required")
-    results: list[dict] = []
-    conn = _conn()
-    try:
-        for tid in ids:
-            entry: dict[str, Any] = {"id": tid, "ok": True}
-            try:
-                task = kanban_db.get_task(conn, tid)
-                if task is None:
-                    entry.update(ok=False, error="not found")
-                    results.append(entry)
-                    continue
-                if payload.archive:
-                    if not kanban_db.archive_task(conn, tid):
-                        entry.update(ok=False, error="archive refused")
-                if payload.status is not None and not payload.archive:
-                    s = payload.status
-                    if s == "done":
-                        ok = kanban_db.complete_task(conn, tid)
-                    elif s == "blocked":
-                        ok = kanban_db.block_task(conn, tid)
-                    elif s == "ready":
-                        cur = kanban_db.get_task(conn, tid)
-                        if cur and cur.status == "blocked":
-                            ok = kanban_db.unblock_task(conn, tid)
-                        else:
-                            ok = _set_status_direct(conn, tid, "ready")
-                    elif s in ("todo", "running", "triage"):
-                        ok = _set_status_direct(conn, tid, s)
-                    else:
-                        entry.update(ok=False, error=f"unknown status {s!r}")
-                        results.append(entry)
-                        continue
-                    if not ok:
-                        entry.update(ok=False, error=f"transition to {s!r} refused")
-                if payload.assignee is not None:
-                    try:
-                        if not kanban_db.assign_task(
-                            conn, tid, payload.assignee or None,
-                        ):
-                            entry.update(ok=False, error="assign refused")
-                    except RuntimeError as e:
-                        entry.update(ok=False, error=str(e))
-                if payload.priority is not None:
-                    with kanban_db.write_txn(conn):
-                        conn.execute(
-                            "UPDATE tasks SET priority = ? WHERE id = ?",
-                            (int(payload.priority), tid),
-                        )
-                        conn.execute(
-                            "INSERT INTO task_events (task_id, kind, payload, created_at) "
-                            "VALUES (?, 'reprioritized', ?, ?)",
-                            (tid, json.dumps({"priority": int(payload.priority)}),
-                             int(time.time())),
-                        )
-            except Exception as e:  # defensive — one bad id shouldn't kill the batch
-                entry.update(ok=False, error=str(e))
-            results.append(entry)
-        return {"results": results}
-    finally:
-        conn.close()
-
-
-# ---------------------------------------------------------------------------
-# Plugin config (read dashboard.kanban.* defaults from config.yaml)
-# ---------------------------------------------------------------------------
-
-@router.get("/config")
-def get_config():
-    """Return kanban dashboard preferences from ~/.hermes/config.yaml.
-
-    Reads the ``dashboard.kanban`` section if present; defaults otherwise.
-    Used by the UI to pre-select tenant filters, toggle markdown rendering,
-    or set column-width preferences without a round-trip per page load.
-    """
-    try:
-        from hermes_cli.config import load_config
-        cfg = load_config() or {}
-    except Exception:
-        cfg = {}
-    dash_cfg = (cfg.get("dashboard") or {})
-    # dashboard.kanban may itself be a dict; fall back to {}.
-    k_cfg = dash_cfg.get("kanban") or {}
-    return {
-        "default_tenant": k_cfg.get("default_tenant") or "",
-        "lane_by_profile": bool(k_cfg.get("lane_by_profile", True)),
-        "include_archived_by_default": bool(k_cfg.get("include_archived_by_default", False)),
-        "render_markdown": bool(k_cfg.get("render_markdown", True)),
-    }
-
-
-# ---------------------------------------------------------------------------
-# Stats (per-profile / per-status counts + oldest-ready age)
-# ---------------------------------------------------------------------------
-
-@router.get("/stats")
-def get_stats():
-    """Per-status + per-assignee counts + oldest-ready age.
-
-    Designed for the dashboard HUD and for router profiles that need to
-    answer "is this specialist overloaded?" without scanning the whole
-    board themselves.
-    """
-    conn = _conn()
-    try:
-        return kanban_db.board_stats(conn)
-    finally:
-        conn.close()
-
-
-@router.get("/assignees")
-def get_assignees():
-    """Known profiles + per-profile task counts.
-
-    Returns the union of ``~/.hermes/profiles/*`` on disk and every
-    distinct assignee currently used on the board. The dashboard uses
-    this to populate its assignee dropdown so a freshly-created profile
-    appears in the picker before it's been given any task.
-    """
-    conn = _conn()
-    try:
-        return {"assignees": kanban_db.known_assignees(conn)}
-    finally:
-        conn.close()
-
-
-# ---------------------------------------------------------------------------
-# Worker log (read-only; file written by _default_spawn)
-# ---------------------------------------------------------------------------
-
-@router.get("/tasks/{task_id}/log")
-def get_task_log(task_id: str, tail: Optional[int] = Query(None, ge=1, le=2_000_000)):
-    """Return the worker's stdout/stderr log.
-
-    ``tail`` caps the response size (bytes) so the dashboard drawer
-    doesn't paginate megabytes into the browser. Returns 404 if the task
-    has never spawned. The on-disk log is rotated at 2 MiB per
-    ``_rotate_worker_log`` — a single ``.log.1`` is kept, no further
-    generations, so disk usage per task is bounded at ~4 MiB.
-    """
-    conn = _conn()
-    try:
-        task = kanban_db.get_task(conn, task_id)
-    finally:
-        conn.close()
-    if task is None:
-        raise HTTPException(status_code=404, detail=f"task {task_id} not found")
-    content = kanban_db.read_worker_log(task_id, tail_bytes=tail)
-    log_path = kanban_db.worker_log_path(task_id)
-    size = log_path.stat().st_size if log_path.exists() else 0
-    return {
-        "task_id": task_id,
-        "path": str(log_path),
-        "exists": content is not None,
-        "size_bytes": size,
-        "content": content or "",
-        # Truncated when the on-disk file was larger than the tail cap.
-        "truncated": bool(tail and size > tail),
-    }
-
-
-# ---------------------------------------------------------------------------
-# Dispatch nudge (optional quick-path so the UI doesn't wait 60 s)
-# ---------------------------------------------------------------------------
-
-@router.post("/dispatch")
-def dispatch(dry_run: bool = Query(False), max_n: int = Query(8, alias="max")):
-    conn = _conn()
-    try:
-        result = kanban_db.dispatch_once(
-            conn, dry_run=dry_run, max_spawn=max_n,
-        )
-        # DispatchResult is a dataclass.
-        try:
-            return asdict(result)
-        except TypeError:
-            return {"result": str(result)}
-    finally:
-        conn.close()
-
-
-# ---------------------------------------------------------------------------
-# WebSocket: /events?since=<event_id>
-# ---------------------------------------------------------------------------
-
-# Poll interval for the event tail loop. SQLite WAL + 300 ms polling is
-# the simplest and most robust approach; it adds a fraction of a percent
-# of CPU and has no shared state to synchronize across workers.
-_EVENT_POLL_SECONDS = 0.3
-
-
-@router.websocket("/events")
-async def stream_events(ws: WebSocket):
-    # Enforce the dashboard session token as a query param — browsers can't
-    # set Authorization on a WS upgrade. This matches how the PTY bridge
-    # authenticates in hermes_cli/web_server.py.
-    token = ws.query_params.get("token")
-    if not _check_ws_token(token):
-        await ws.close(code=http_status.WS_1008_POLICY_VIOLATION)
-        return
-    await ws.accept()
-    try:
-        since_raw = ws.query_params.get("since", "0")
-        try:
-            cursor = int(since_raw)
-        except ValueError:
-            cursor = 0
-
-        def _fetch_new(cursor_val: int) -> tuple[int, list[dict]]:
-            conn = kanban_db.connect()
-            try:
-                rows = conn.execute(
-                    "SELECT id, task_id, run_id, kind, payload, created_at "
-                    "FROM task_events WHERE id > ? ORDER BY id ASC LIMIT 200",
-                    (cursor_val,),
-                ).fetchall()
-                out: list[dict] = []
-                new_cursor = cursor_val
-                for r in rows:
-                    try:
-                        payload = json.loads(r["payload"]) if r["payload"] else None
-                    except Exception:
-                        payload = None
-                    out.append({
-                        "id": r["id"],
-                        "task_id": r["task_id"],
-                        "run_id": r["run_id"],
-                        "kind": r["kind"],
-                        "payload": payload,
-                        "created_at": r["created_at"],
-                    })
-                    new_cursor = r["id"]
-                return new_cursor, out
-            finally:
-                conn.close()
-
-        while True:
-            cursor, events = await asyncio.to_thread(_fetch_new, cursor)
-            if events:
-                await ws.send_json({"events": events, "cursor": cursor})
-            await asyncio.sleep(_EVENT_POLL_SECONDS)
-    except WebSocketDisconnect:
-        return
-    except Exception as exc:  # defensive: never crash the dashboard worker
-        log.warning("Kanban event stream error: %s", exc)
-        try:
-            await ws.close()
-        except Exception:
-            pass

plugins/kanban/systemd/hermes-kanban-dispatcher.service

@@ -1,17 +0,0 @@
-[Unit]
-Description=Hermes Kanban dispatcher (hermes kanban daemon)
-Documentation=https://hermes-agent.nousresearch.com/docs/user-guide/features/kanban
-After=network.target
-
-[Service]
-Type=simple
-ExecStart=/usr/bin/env hermes kanban daemon --interval 60 --pidfile %t/hermes-kanban-dispatcher.pid
-Restart=on-failure
-RestartSec=5
-# Log to the journal via stdout/stderr; the dispatcher also writes per-task
-# worker output to $HERMES_HOME/kanban/logs/<task>.log.
-StandardOutput=journal
-StandardError=journal
-
-[Install]
-WantedBy=default.target

plugins/memory/openviking/__init__.py

@@ -43,7 +43,7 @@ _TIMEOUT = 30.0
 # ---------------------------------------------------------------------------
 # Process-level atexit safety net — ensures pending sessions are committed
 # even if shutdown_memory_provider is never called (e.g. gateway crash,
-# SIGKILL, or exception in the session expiry watcher preventing shutdown).
+# SIGKILL, or exception in _async_flush_memories preventing shutdown).
 # ---------------------------------------------------------------------------
 _last_active_provider: Optional["OpenVikingMemoryProvider"] = None
 

pyproject.toml

@@ -78,16 +78,6 @@ termux = [
 ]
 dingtalk = ["dingtalk-stream>=0.20,<1", "alibabacloud-dingtalk>=2.0.0", "qrcode>=7.0,<8"]
 feishu = ["lark-oapi>=1.5.3,<2", "qrcode>=7.0,<8"]
-google = [
-  # Required by the google-workspace skill (Gmail, Calendar, Drive, Contacts,
-  # Sheets, Docs).  Declared here so packagers (Nix, Homebrew) ship them with
-  # the [all] extra and users don't hit runtime `pip install` paths that fail
-  # in environments without pip (e.g. Nix-managed Python).
-  "google-api-python-client>=2.100,<3",
-  "google-auth-oauthlib>=1.0,<2",
-  "google-auth-httplib2>=0.2,<1",
-]
-# `hermes dashboard` (localhost SPA + API).  Not in core to keep the default install lean.
 web = ["fastapi>=0.104.0,<1", "uvicorn[standard]>=0.24.0,<1"]
 rl = [
   "atroposlib @ git+https://github.com/NousResearch/atropos.git@c20c85256e5a45ad31edf8b7276e9c5ee1995a30",
@@ -119,7 +109,6 @@ all = [
   "hermes-agent[voice]",
   "hermes-agent[dingtalk]",
   "hermes-agent[feishu]",
-  "hermes-agent[google]",
   "hermes-agent[mistral]",
   "hermes-agent[bedrock]",
   "hermes-agent[web]",

scripts/build_model_catalog.py

@@ -1,95 +0,0 @@
-#!/usr/bin/env python3
-"""Build the Hermes Model Catalog — a centralized JSON manifest of curated models.
-
-This script reads the in-repo hardcoded curated lists (``OPENROUTER_MODELS``,
-``_PROVIDER_MODELS["nous"]``) and writes them to a JSON manifest that the
-Hermes CLI fetches at runtime. Publishing the catalog through the docs site
-lets maintainers update model lists without shipping a Hermes release.
-
-The runtime fetcher falls back to the same in-repo hardcoded lists if the
-manifest is unreachable, so this script is a convenience for keeping the
-manifest in sync — not a source of truth.
-
-Usage::
-
-    python scripts/build_model_catalog.py
-
-Output: ``website/static/api/model-catalog.json``
-
-Live URL (after ``deploy-site.yml`` runs on merge to main):
-``https://hermes-agent.nousresearch.com/docs/api/model-catalog.json``
-"""
-
-from __future__ import annotations
-
-import json
-import os
-import sys
-from datetime import datetime, timezone
-
-REPO_ROOT = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
-sys.path.insert(0, REPO_ROOT)
-
-# Ensure HERMES_HOME is set for imports that touch it at module level.
-os.environ.setdefault("HERMES_HOME", os.path.join(os.path.expanduser("~"), ".hermes"))
-
-from hermes_cli.models import OPENROUTER_MODELS, _PROVIDER_MODELS  # noqa: E402
-
-OUTPUT_PATH = os.path.join(REPO_ROOT, "website", "static", "api", "model-catalog.json")
-CATALOG_VERSION = 1
-
-
-def build_catalog() -> dict:
-    return {
-        "version": CATALOG_VERSION,
-        "updated_at": datetime.now(timezone.utc).strftime("%Y-%m-%dT%H:%M:%SZ"),
-        "metadata": {
-            "source": "hermes-agent repo",
-            "docs": "https://hermes-agent.nousresearch.com/docs/reference/model-catalog",
-        },
-        "providers": {
-            "openrouter": {
-                "metadata": {
-                    "display_name": "OpenRouter",
-                    "note": (
-                        "Descriptions drive picker badges. Live /api/v1/models "
-                        "filters curated ids by tool-calling support and free pricing."
-                    ),
-                },
-                "models": [
-                    {"id": mid, "description": desc}
-                    for mid, desc in OPENROUTER_MODELS
-                ],
-            },
-            "nous": {
-                "metadata": {
-                    "display_name": "Nous Portal",
-                    "note": (
-                        "Free-tier gating is determined live via Portal pricing "
-                        "(partition_nous_models_by_tier), not this manifest."
-                    ),
-                },
-                "models": [
-                    {"id": mid}
-                    for mid in _PROVIDER_MODELS.get("nous", [])
-                ],
-            },
-        },
-    }
-
-
-def main() -> int:
-    catalog = build_catalog()
-    os.makedirs(os.path.dirname(OUTPUT_PATH), exist_ok=True)
-    with open(OUTPUT_PATH, "w") as fh:
-        json.dump(catalog, fh, indent=2)
-        fh.write("\n")
-
-    print(f"Wrote {OUTPUT_PATH}")
-    for provider, block in catalog["providers"].items():
-        print(f"  {provider}: {len(block['models'])} models")
-    return 0
-
-
-if __name__ == "__main__":
-    sys.exit(main())

scripts/compression_eval/DESIGN.md

@@ -0,0 +1,377 @@
+# Compression Eval — Design
+
+Status: proposal. Nothing under `scripts/compression_eval/` runs in CI.
+This is an offline tool authors run before merging prompt or algorithm
+changes to `agent/context_compressor.py`.
+
+## Why
+
+We tune the compressor prompt and the `_template_sections` checklist by
+hand, ship, and wait for the next real session to notice regressions.
+There is no automated check that a prompt edit still preserves file
+paths, error messages, or the active task across a compression.
+
+Factory.ai's December 2025 write-up
+(https://factory.ai/news/evaluating-compression) describes a
+probe-based eval that scores compressed state on six dimensions. The
+methodology is the valuable part — the benchmarks in the post are a
+marketing piece. We adopt the methodology and discard the scoreboard.
+
+## Goal
+
+Given a real session transcript and a bank of probe questions that
+exercise what the transcript contained, answer:
+
+1. After `ContextCompressor.compress()` runs, can the agent still
+   answer each probe correctly from the compressed state?
+2. Which of the six dimensions (accuracy, context awareness, artifact
+   trail, completeness, continuity, instruction following) is the
+   prompt weakest on?
+3. Does a prompt change improve or regress any dimension vs. the
+   previous run?
+
+That is the full scope. No "compare against OpenAI and Anthropic"
+benchmarking, no public scoreboard, no marketing claims.
+
+## Non-goals
+
+- Not a pytest. Requires API credentials, costs money, takes minutes
+  per fixture, and output is LLM-graded and non-deterministic.
+- Not part of `scripts/run_tests.sh`. Not invoked by CI.
+- Not a replacement for the existing compressor unit tests in
+  `tests/agent/test_context_compressor.py` — those stay as the
+  structural / boundary / tool-pair-sanitization guard.
+- Not a general trajectory eval. Scoped to context compaction only.
+
+## Where it lives
+
+```
+scripts/compression_eval/
+├── DESIGN.md                 # this file
+├── README.md                 # how to run, cost expectations, caveats
+├── run_eval.py               # entry point (fire CLI, like sample_and_compress.py)
+├── scrub_fixtures.py         # regenerate fixtures from ~/.hermes/sessions/*.jsonl
+├── fixtures/                 # checked-in scrubbed session snapshots
+│   ├── feature-impl-context-priority.json
+│   ├── debug-session-feishu-id-model.json
+│   └── config-build-competitive-scouts.json
+├── probes/                   # probe banks paired with fixtures
+│   └── <fixture>.probes.json
+├── rubric.py                 # grading prompt + dimension definitions
+├── grader.py                 # judge-model call + score parsing
+├── compressor_driver.py      # thin wrapper over ContextCompressor
+└── results/                  # gitignored; timestamped output per run
+    └── .gitkeep
+```
+
+`scripts/` is the right home: offline tooling, no CI involvement,
+precedent already set by `sample_and_compress.py`,
+`contributor_audit.py`, `discord-voice-doctor.py`.
+
+`environments/` is for Atropos RL training environments — wrong shape.
+`tests/` is hermetic and credential-free — incompatible with a
+probe-based eval that needs a judge model.
+
+## Fixture format
+
+A fixture is a single compressed-enough conversation captured from a
+real session. Stored as JSON (pretty-printed, reviewable in PRs):
+
+```json
+{
+  "name": "401-debug",
+  "description": "178-turn session debugging a 401 on /api/auth/login",
+  "model": "anthropic/claude-sonnet-4.6",
+  "context_length": 200000,
+  "messages": [
+    {"role": "system", "content": "..."},
+    {"role": "user", "content": "..."},
+    {"role": "assistant", "content": "...", "tool_calls": [...]},
+    {"role": "tool", "tool_call_id": "...", "content": "..."}
+  ],
+  "notes": "Captured 2026-04-24 from session 20260424_*.jsonl; \
+            PII scrubbed; secrets redacted via redact_sensitive_text."
+}
+```
+
+### Sourcing fixtures
+
+Fixtures are scrubbed snapshots of real sessions from the
+maintainer's `~/.hermes/sessions/*.jsonl` store, generated
+reproducibly by `scrub_fixtures.py` in this directory. Re-run the
+scrubber with `python3 scripts/compression_eval/scrub_fixtures.py`
+to regenerate them after a scrubber change.
+
+Three shipped fixtures cover three different session shapes:
+
+| Fixture | Source shape | Messages | Tokens (rough) | Tests |
+|---|---|---|---|---|
+| `feature-impl-context-priority` | investigate → patch → test → PR → merge | 75 | ~45k | continuation, artifact trail (2 files modified, 1 PR, ~16k skill_view in head) |
+| `debug-session-feishu-id-model` | PR triage + upstream docs + decision | 59 | ~28k | recall (PR #, error shape), decision (outcome + reason), large PR diff blocks |
+| `config-build-competitive-scouts` | iterative config: 11 cron jobs across 7 weekdays | 61 | ~26k | artifact trail (which jobs, which days), iterative-merge |
+
+The `~26k-45k` token range is below the default 50%-of-200k
+compression threshold, so the eval will always **force** a
+`compress()` call rather than wait for the natural trigger. That is
+the intended shape — we want a controlled single-shot compression so
+score deltas are attributable to the prompt change, not to whether
+the threshold happened to fire at the same boundary twice.
+
+### Scrubber pipeline
+
+`scrub_fixtures.py` applies, per message:
+
+1. `agent.redact.redact_sensitive_text` — API keys, tokens,
+   connection strings
+2. Username paths: `/home/teknium` → `/home/user`
+3. Personal handles: all case variants of the maintainer name → `user`
+4. Email addresses → `contributor@example.com`; git
+   `Author: Name <addr>` header lines normalised
+5. `<REASONING_SCRATCHPAD>...</REASONING_SCRATCHPAD>` and
+   `<think>...</think>` stripped from assistant content
+6. Messaging-platform user mentions (`<@123456>`, `<@***>`) →
+   `<@user>`
+7. First user message paraphrased to remove personal voice;
+   subsequent user turns kept verbatim after the redactions above
+8. System prompt replaced with a generic public-safe placeholder so
+   we don't check in the maintainer's tuned soul/skills/memory system
+   block
+9. Orphan empty-assistant messages (artifact of scratchpad-only
+   turns) and trailing tool messages with no matching assistant are
+   dropped
+10. Tool outputs preserved verbatim. An earlier iteration truncated
+    > 2KB tool bodies to keep fixture JSON small, but that defeats
+    the purpose: real sessions have 30KB `skill_view` dumps, 10KB
+    `read_file` outputs, 5KB `web_extract` bodies — compression has
+    to handle them. Truncation is now a no-op; the pipeline note
+    remains in `scrubbing_passes` for audit trail clarity.
+
+Before every fixture PR: grep the fixture for PII patterns. An
+audit is embedded at the bottom of the scrubber as comments.
+
+**Fixtures must stay small.** Target <200 KB per fixture, <500 KB
+total for the directory. Current total: ~410 KB across three
+fixtures.  Larger sessions are truncated with a
+`truncated_to: <index>` field in the fixture header so the cut is
+reviewable.
+
+## Probe format
+
+One probe file per fixture, so reviewers can see the question bank
+evolve alongside the fixture:
+
+```json
+{
+  "fixture": "401-debug",
+  "probes": [
+    {
+      "id": "recall-error-code",
+      "type": "recall",
+      "question": "What was the original error code and endpoint?",
+      "expected_facts": ["401", "/api/auth/login"]
+    },
+    {
+      "id": "artifact-files-modified",
+      "type": "artifact",
+      "question": "Which files have been modified in this session?",
+      "expected_facts": ["session_store.py", "redis_client.py"]
+    },
+    {
+      "id": "continuation-next-step",
+      "type": "continuation",
+      "question": "What should we do next?",
+      "expected_facts": ["re-run the integration tests", "restart the worker"]
+    },
+    {
+      "id": "decision-redis-approach",
+      "type": "decision",
+      "question": "What did we decide about the Redis issue?",
+      "expected_facts": ["switch to redis-py 5.x", "pooled connection"]
+    }
+  ]
+}
+```
+
+The four probe types come directly from Factory's methodology:
+**recall, artifact, continuation, decision**. `expected_facts` gives
+the grader concrete anchors instead of relying purely on LLM taste.
+
+Authoring a probe bank is a one-time cost per fixture. 8-12 probes per
+fixture is the target — enough to cover all four types, few enough to
+grade in under a minute at reasonable cost.
+
+## Grading
+
+Each probe gets scored 0-5 on **six dimensions** (Factory's six):
+
+| Dimension             | What it measures                                    |
+|-----------------------|-----------------------------------------------------|
+| accuracy              | File paths, function names, error codes are correct |
+| context_awareness     | Reflects current state, not a mid-session snapshot  |
+| artifact_trail        | Knows which files were read / modified / created    |
+| completeness          | Addresses all parts of the probe                    |
+| continuity            | Agent can continue without re-fetching              |
+| instruction_following | Probe answered in the requested form                |
+
+Grading is done by a single judge-model call per probe with a
+deterministic rubric prompt (see `rubric.py`). The rubric includes the
+`expected_facts` list so the judge has a concrete anchor. Default
+judge model: whatever the user has configured as their main model at
+run time (same resolution path as `auxiliary_client.call_llm`). A
+`--judge-model` flag allows overriding for consistency across runs.
+
+Non-determinism caveat: two runs of the same fixture will produce
+different scores. A single run means nothing. Report medians over
+N=3 runs by default, and require an improvement of >=0.3 on any
+dimension before claiming a prompt change is a win.
+
+## Run flow
+
+```
+python scripts/compression_eval/run_eval.py [OPTIONS]
+```
+
+Options (fire-style, mirroring `sample_and_compress.py`):
+
+| Flag                   | Default    | Purpose                                   |
+|------------------------|------------|-------------------------------------------|
+| `--fixtures`           | all        | Comma-separated fixture names             |
+| `--runs`               | 3          | Runs per fixture (for median)             |
+| `--judge-model`        | auto       | Override judge model                      |
+| `--compressor-model`   | auto       | Override model used *inside* the compressor |
+| `--label`              | timestamp  | Subdirectory under `results/`             |
+| `--focus-topic`        | none       | Pass-through to `compress(focus_topic=)`  |
+| `--compare-to`         | none       | Path to a previous run for diff output    |
+
+Steps per fixture per run:
+
+1. Load fixture JSON and probe bank.
+2. Construct a `ContextCompressor` against the fixture's model.
+3. Call `compressor.compress(messages)` — capture the compressed
+   message list.
+4. For each probe: ask the judge model to role-play as the continuing
+   agent with only the compressed state, then grade the answer on the
+   six dimensions using `rubric.py`.
+5. Write a per-run JSON to `results/<label>/<fixture>-run-N.json`.
+6. After all runs, emit a markdown summary to
+   `results/<label>/report.md`.
+
+## Report format
+
+Pasted verbatim into PR descriptions that touch the compressor:
+
+```
+## Compression eval — label 2026-04-25_13-40-02
+
+Main model: anthropic/claude-sonnet-4.6   Judge: same
+3 runs per fixture, medians reported.
+
+| Fixture        | Accuracy | Context | Artifact | Complete | Continuity | Instruction | Overall |
+|----------------|----------|---------|----------|----------|------------|-------------|---------|
+| 401-debug      | 4.1      | 4.0     | 2.5      | 4.3      | 3.8        | 5.0         | 3.95    |
+| pr-review      | 3.9      | 3.8     | 3.1      | 4.2      | 3.9        | 5.0         | 3.98    |
+| feature-impl   | 4.0      | 3.9     | 2.9      | 4.1      | 4.0        | 5.0         | 3.98    |
+
+Per-probe misses (score < 3.0):
+- 401-debug / artifact-files-modified: 1.7 — summary dropped redis_client.py
+- pr-review / decision-auth-rewrite: 2.3 — outcome captured, reasoning dropped
+```
+
+## Cost expectations
+
+Dominated by the judge calls. For 3 fixtures × 10 probes × 3 runs =
+90 judge calls per eval run. On Claude Sonnet 4.6 that is roughly
+$0.50-$1.50 per full eval depending on probe length. The compressor
+itself makes 1 call per fixture × 3 runs = 9 additional calls.
+
+**This is not a check to run after every commit.** It is a
+before-merge check for PRs that touch:
+
+- `agent/context_compressor.py` — any change to `_template_sections`,
+  `_generate_summary`, or `compress()`.
+- `agent/auxiliary_client.py` — when changing how compression tasks
+  are routed.
+- `agent/prompt_builder.py` — when the compression-note phrasing
+  changes.
+
+## Open questions (to resolve before implementing)
+
+1. **Fixture scrubbing: manual or scripted?** A scripted scrub that
+   also replaces project names / hostnames would lower the cost of
+   contributing a new fixture. Risk: over-aggressive replacement
+   destroys the signal the probe depends on. Propose: start manual,
+   add scripted helpers once we have 3 fixtures and know the common
+   PII shapes.
+
+2. **Judge model selection.** Factory uses GPT-5.2. We can't pin one
+   — user's main model changes. Options: (a) grade with main model
+   (cheap, inconsistent across users), (b) require a specific judge
+   model (e.g. `claude-sonnet-4.6`), inconsistent for users without
+   access. Propose (a) with a `--judge-model` override, and make the
+   model name prominent in the report so comparisons across machines
+   are legible.
+
+3. **Noise floor.** Before landing prompt changes, run the current
+   prompt N=10 times to measure per-dimension stddev. That tells us
+   the minimum delta to call a change significant. Suspect 0.2-0.3 on
+   a 0-5 scale. Decision deferred until after the first fixture is
+   landed.
+
+4. **Iterative-merge coverage.** The real Factory-vs-Anthropic
+   difference is incremental merge vs. regenerate. A fixture that
+   only compresses once doesn't exercise our iterative path. Add a
+   fourth fixture that forces two compressions (manually chained),
+   with probes that test whether information from the first
+   compression survives the second. Deferred to a follow-up PR.
+
+## Implementation status
+
+This PR ships the full eval end-to-end:
+
+- `scrub_fixtures.py` — reproducible scrubber
+- `fixtures/` — three scrubbed session fixtures
+- `probes/` — three probe banks (10-11 probes each, all four types)
+- `rubric.py` — six-dimension grading rubric + judge-prompt builder + response parser
+- `compressor_driver.py` — thin wrapper around `ContextCompressor` for forced single-shot compression
+- `grader.py` — two-phase continuation + grading calls via OpenAI SDK
+- `report.py` — markdown report renderer + `--compare-to` delta mode + per-run JSON dumper
+- `run_eval.py` — entry point (`fire`-style CLI)
+- `tests/scripts/test_compression_eval.py` — 33 unit tests covering rubric parsing, report rendering, fixture/probe loading, and a PII smoke test on the fixtures (LLM paths not tested — they require credentials and are exercised by the eval itself)
+
+### Noise floor — one empirical data point
+
+A single same-inputs re-run of `debug-session-feishu-id-model`
+(compressor + judge = `openai/gpt-5.4-mini` via Nous Portal,
+runs=1) produced:
+
+- Run A overall: 3.25
+- Run B overall: 3.17 (delta -0.08)
+
+Individual dimensions varied by up to ±0.5 between the two runs on
+single-run medians. This confirms DESIGN.md's "< 0.3 is noise"
+guidance is the right order of magnitude for a single-run
+comparison. With `runs=3` default, per-dimension variance should
+tighten; noise-floor measurement at N=10 is still a useful
+follow-up to calibrate precisely.
+
+## Open follow-ups (not blocking this PR)
+
+1. **Iterative-merge fixture** — our actual compression win over
+   "regenerate from scratch" approaches is only exercised when
+   `_previous_summary` is re-used on a second compression. None of
+   the three shipped fixtures force two compressions. The natural
+   basis is `config-build-competitive-scouts` (already iterative by
+   shape); splitting it at the Monday/Tuesday boundary would force
+   the second compression to merge rather than regenerate.
+2. **Noise-floor precision** — run the current prompt N=10 times
+   against one fixture to pin down per-dimension stddev and publish
+   the numbers in README.
+3. **Scripted scrubber helpers** — the current scrubber is manual
+   per-fixture. A helper that identifies candidate sessions to
+   scrub (by shape or by keyword) would lower the cost of adding
+   fixture #4+.
+4. **Judge model selection policy** — current code uses whatever
+   the user passes as `--judge-model` (default: same as compressor).
+   Pinning the judge across users would stabilise cross-machine
+   comparisons, at the cost of blocking users without access to
+   the pinned model.

scripts/compression_eval/README.md

@@ -0,0 +1,110 @@
+# compression_eval
+
+Offline eval harness for `agent/context_compressor.py`. Runs a real
+conversation transcript through the compressor, then probes the
+compressed state with targeted questions graded on six dimensions.
+
+## When to run
+
+Before merging changes to:
+
+- `agent/context_compressor.py` — any change to `_template_sections`,
+  `_generate_summary`, `compress()`, or its boundary logic
+- `agent/auxiliary_client.py` — when changing how compression tasks
+  are routed
+- `agent/prompt_builder.py` — when the compression-note phrasing
+  changes
+
+## Not for CI
+
+This harness makes real model calls (compressor + continuation +
+judge = ~3 calls per probe × probes per fixture × runs). Costs ~$0.50
+to ~$1.50 per full run depending on models, takes minutes, is
+LLM-graded (non-deterministic). It lives in `scripts/` and is
+invoked by hand. `tests/` and `scripts/run_tests.sh` do not touch it.
+
+`tests/scripts/test_compression_eval.py` covers the non-LLM code
+paths (rubric parsing, report rendering, fixture/probe loading, PII
+smoke check on the checked-in fixtures) and DOES run in CI.
+
+## Usage
+
+```bash
+# Run all three fixtures, 3 runs each, with your configured provider
+python3 scripts/compression_eval/run_eval.py
+
+# Faster iteration — one fixture, one run
+python3 scripts/compression_eval/run_eval.py \
+    --fixtures=debug-session-feishu-id-model --runs=1
+
+# Pin a cheap model for both compression + judge (recommended)
+python3 scripts/compression_eval/run_eval.py \
+    --compressor-provider=nous --compressor-model=openai/gpt-5.4-mini \
+    --judge-provider=nous      --judge-model=openai/gpt-5.4-mini \
+    --runs=3 --label=baseline
+
+# After editing context_compressor.py, rerun with a new label and diff
+python3 scripts/compression_eval/run_eval.py \
+    --compressor-provider=nous --compressor-model=openai/gpt-5.4-mini \
+    --judge-provider=nous      --judge-model=openai/gpt-5.4-mini \
+    --runs=3 --label=my-prompt-tweak \
+    --compare-to=results/baseline
+```
+
+Results land in `results/<label>/report.md` and are intended to be
+pasted verbatim into PR descriptions. `--compare-to` renders a delta
+column per dimension so reviewers can see "did this actually help?"
+at a glance.
+
+Rule of thumb: dimension deltas below ±0.3 are within run-to-run
+noise on `runs=3`. Publish a bigger N if you want tighter bounds.
+
+## Fixtures
+
+Three scrubbed session snapshots live under `fixtures/`:
+
+- `feature-impl-context-priority.json` — 75 msgs, investigate →
+  patch → test → PR → merge
+- `debug-session-feishu-id-model.json` — 59 msgs, PR triage +
+  upstream docs + decision
+- `config-build-competitive-scouts.json` — 61 msgs, iterative
+  config accumulation (11 cron jobs)
+
+Regenerate them from the maintainer's `~/.hermes/sessions/*.jsonl`
+with `python3 scripts/compression_eval/scrub_fixtures.py`. The
+scrubber pipeline and PII-audit checklist are documented in
+`DESIGN.md` under **Scrubber pipeline**.
+
+## Probes
+
+One probe bank per fixture under `probes/`, 10-11 probes each,
+covering all four types: **recall**, **artifact**, **continuation**,
+**decision**. Each probe carries an `expected_facts` list of concrete
+anchors (PR numbers, file paths, error codes, commands run) that the
+judge sees alongside the assistant's answer.
+
+## How it scores
+
+Six dimensions, 0-5 per probe:
+
+| Dimension             | What it measures                                     |
+|-----------------------|------------------------------------------------------|
+| accuracy              | File paths, function names, PR/issue numbers correct |
+| context_awareness     | Reflects current session state, not a snapshot       |
+| artifact_trail        | Correctly enumerates files / commands / PRs          |
+| completeness          | Addresses ALL parts of the probe                     |
+| continuity            | Next assistant could continue without re-fetching    |
+| instruction_following | Answer in the requested form                         |
+
+Report renders medians across N runs; probes scoring below 3.0
+overall surface in a separate section with the judge's specific
+complaint noted inline.
+
+## Related
+
+- `agent/context_compressor.py` — the thing under test
+- `tests/agent/test_context_compressor.py` — structural unit tests
+  that do run in CI
+- `scripts/sample_and_compress.py` — the closest existing script in
+  shape (offline, credential-requiring, not in CI)
+- `DESIGN.md` — full architecture + methodology + open follow-ups

scripts/compression_eval/compressor_driver.py

@@ -0,0 +1,114 @@
+"""Wraps ContextCompressor to run a single forced compression on a fixture.
+
+The real agent loop checks ``should_compress()`` before calling ``compress()``.
+Fixtures are intentionally sized below the 100k threshold so ``compress()``
+runs in a controlled, single-shot mode — score deltas attribute to the
+prompt change, not to whether the threshold happened to fire at the same
+boundary twice.
+
+Resolves the provider for the compression call via the same path the real
+agent uses (``hermes_cli.runtime_provider.resolve_runtime_provider``) so
+behaviour matches production aside from being a single call.
+"""
+from __future__ import annotations
+
+import sys
+from pathlib import Path
+from typing import Any, Dict, List, Optional
+
+# Make sibling imports work whether invoked as a script or as a module.
+_REPO_ROOT = Path(__file__).resolve().parents[2]
+if str(_REPO_ROOT) not in sys.path:
+    sys.path.insert(0, str(_REPO_ROOT))
+
+from agent.context_compressor import (  # noqa: E402
+    ContextCompressor,
+    estimate_messages_tokens_rough,
+)
+
+
+def run_compression(
+    *,
+    messages: List[Dict[str, Any]],
+    compressor_model: str,
+    compressor_provider: str,
+    compressor_base_url: str,
+    compressor_api_key: str,
+    compressor_api_mode: str,
+    context_length: int,
+    focus_topic: Optional[str] = None,
+    summary_model_override: Optional[str] = None,
+) -> Dict[str, Any]:
+    """Run a single forced compression pass over the fixture messages.
+
+    Returns a dict with:
+      - compressed_messages: the post-compression message list
+      - summary_text: the summary produced (extracted from the compressed head)
+      - pre_tokens, post_tokens: rough token counts before/after
+      - compression_ratio: 1 - (post/pre)
+      - pre_message_count, post_message_count
+    """
+    compressor = ContextCompressor(
+        model=compressor_model,
+        threshold_percent=0.50,
+        protect_first_n=3,
+        protect_last_n=20,
+        summary_target_ratio=0.20,
+        quiet_mode=True,
+        summary_model_override=summary_model_override or "",
+        base_url=compressor_base_url,
+        api_key=compressor_api_key,
+        config_context_length=context_length,
+        provider=compressor_provider,
+        api_mode=compressor_api_mode,
+    )
+
+    pre_tokens = estimate_messages_tokens_rough(messages)
+    compressed = compressor.compress(
+        messages,
+        current_tokens=pre_tokens,
+        focus_topic=focus_topic,
+    )
+    post_tokens = estimate_messages_tokens_rough(compressed)
+
+    summary_text = _extract_summary_from_messages(compressed)
+
+    ratio = (1.0 - (post_tokens / pre_tokens)) if pre_tokens > 0 else 0.0
+
+    return {
+        "compressed_messages": compressed,
+        "summary_text": summary_text,
+        "pre_tokens": pre_tokens,
+        "post_tokens": post_tokens,
+        "compression_ratio": ratio,
+        "pre_message_count": len(messages),
+        "post_message_count": len(compressed),
+    }
+
+
+_SUMMARY_MARKERS = (
+    "## Active Task",
+    "## Goal",
+    "## Completed Actions",
+)
+
+
+def _extract_summary_from_messages(messages: List[Dict[str, Any]]) -> str:
+    """Find the structured summary block inside the compressed message list.
+
+    The compressor injects the summary as a user (or system-appended) message
+    near the head. We look for the section-header markers from
+    ``_template_sections`` in ``agent/context_compressor.py``.
+    """
+    for msg in messages:
+        content = msg.get("content")
+        if not isinstance(content, str):
+            if isinstance(content, list):
+                content = "\n".join(
+                    p.get("text", "") for p in content if isinstance(p, dict)
+                )
+            else:
+                continue
+        if any(marker in content for marker in _SUMMARY_MARKERS):
+            return content
+    return ""

scripts/compression_eval/grader.py

@@ -0,0 +1,181 @@
+"""Two-phase probe grading.
+
+Phase 1 — **Continuation**: simulate the next assistant turn. Feed the
+compressed message list plus the probe question and ask the continuing
+model to answer using only the compressed context. This is exactly what
+a real next-turn call would look like.
+
+Phase 2 — **Grading**: a separate judge-model call scores the answer on
+the six rubric dimensions using ``rubric.build_judge_prompt``.
+
+Both phases use the OpenAI SDK directly against the resolved provider
+endpoint, so the explicit api_key + base_url we pass always reaches the
+wire. (``agent.auxiliary_client.call_llm`` is designed for task-tagged
+auxiliary calls backed by config lookups; for eval we need the explicit
+credentials to win unconditionally.)
+"""
+from __future__ import annotations
+
+import logging
+import sys
+from pathlib import Path
+from typing import Any, Dict, List, Optional
+
+_REPO_ROOT = Path(__file__).resolve().parents[2]
+if str(_REPO_ROOT) not in sys.path:
+    sys.path.insert(0, str(_REPO_ROOT))
+
+from openai import OpenAI  # noqa: E402
+
+from rubric import build_judge_prompt, parse_judge_response  # noqa: E402
+
+logger = logging.getLogger(__name__)
+
+
+_CONTINUATION_SYSTEM = (
+    "You are the continuing assistant in a long session. Earlier turns have "
+    "been compacted into a handoff summary that is now part of the "
+    "conversation history. The user has just asked you a question. "
+    "Answer using ONLY what you can determine from the conversation history "
+    "you see (including the handoff summary). Do NOT invent details. If the "
+    "summary does not contain a specific fact, say so explicitly rather "
+    "than guessing. Be direct and concrete — cite file paths, PR numbers, "
+    "error codes, and exact values when they are present in the summary."
+)
+
+
+def answer_probe(
+    *,
+    compressed_messages: List[Dict[str, Any]],
+    probe_question: str,
+    model: str,
+    provider: str,
+    base_url: str,
+    api_key: str,
+    max_tokens: int = 1024,
+    timeout: Optional[float] = 120.0,
+) -> str:
+    """Run the continuation call: what does the next assistant answer?
+
+    Builds a messages list of [system_continuation, *compressed, probe_user]
+    and asks the configured model. Returns the answer content as a string.
+    """
+    # Strip any pre-existing system message from the compressed list and
+    # replace with our continuation system prompt. The fixture's generic
+    # system is not the right frame for the continuation simulation.
+    history = [m for m in compressed_messages if m.get("role") != "system"]
+    messages = (
+        [{"role": "system", "content": _CONTINUATION_SYSTEM}]
+        + _sanitize_for_chat_api(history)
+        + [{"role": "user", "content": probe_question}]
+    )
+
+    client = OpenAI(api_key=api_key, base_url=base_url, timeout=timeout)
+    response = client.chat.completions.create(
+        model=model,
+        messages=messages,
+        max_tokens=max_tokens,
+    )
+    content = response.choices[0].message.content
+    if not isinstance(content, str):
+        content = "" if content is None else str(content)
+    return content.strip()
+
+
+def grade_probe(
+    *,
+    probe_question: str,
+    probe_type: str,
+    expected_facts: List[str],
+    assistant_answer: str,
+    judge_model: str,
+    judge_provider: str,
+    judge_base_url: str,
+    judge_api_key: str,
+    max_tokens: int = 512,
+    timeout: Optional[float] = 120.0,
+) -> Dict[str, Any]:
+    """Run the judge call and parse the six dimension scores.
+
+    Returns dict {scores: {dim: int}, notes: str, overall: float,
+    raw: str, parse_error: str|None}. On parse failure, scores are zeros
+    and parse_error is populated — the caller decides whether to retry
+    or accept.
+    """
+    prompt = build_judge_prompt(
+        probe_question=probe_question,
+        probe_type=probe_type,
+        expected_facts=expected_facts,
+        assistant_answer=assistant_answer,
+    )
+    client = OpenAI(api_key=judge_api_key, base_url=judge_base_url, timeout=timeout)
+    response = client.chat.completions.create(
+        model=judge_model,
+        messages=[{"role": "user", "content": prompt}],
+        max_tokens=max_tokens,
+    )
+    raw = response.choices[0].message.content or ""
+    if not isinstance(raw, str):
+        raw = str(raw)
+
+    try:
+        parsed = parse_judge_response(raw)
+        parsed["raw"] = raw
+        parsed["parse_error"] = None
+        return parsed
+    except ValueError as exc:
+        logger.warning("Judge response parse failed: %s | raw=%r", exc, raw[:200])
+        from rubric import DIMENSIONS
+        return {
+            "scores": {d: 0 for d in DIMENSIONS},
+            "notes": "",
+            "overall": 0.0,
+            "raw": raw,
+            "parse_error": str(exc),
+        }
+
+
+def _sanitize_for_chat_api(
+    messages: List[Dict[str, Any]],
+) -> List[Dict[str, Any]]:
+    """Drop tool_calls/tool pairs that are incomplete.
+
+    A compressed message list may contain tool_call references whose matching
+    ``tool`` result was summarized away, which breaks strict-validator
+    providers (Anthropic, OpenAI). Easiest correct behaviour for the eval:
+    strip tool_calls entirely and drop ``tool`` role messages — the
+    continuation model only needs the summary + recent turns to answer the
+    probe, not the precise tool-call bookkeeping.
+    """
+    clean: List[Dict[str, Any]] = []
+    for m in messages:
+        role = m.get("role")
+        if role == "tool":
+            # Convert tool result to a plain user note so the continuation
+            # model still sees the content without needing the structured
+            # tool_call_id pairing.
+            content = m.get("content")
+            if isinstance(content, list):
+                content = "\n".join(
+                    p.get("text", "") for p in content if isinstance(p, dict)
+                )
+            clean.append({
+                "role": "user",
+                "content": f"[earlier tool result]\n{content or ''}",
+            })
+            continue
+        new = {"role": role, "content": m.get("content", "")}
+        # Drop tool_calls — the downstream assistant message's content
+        # still describes what the agent was doing.
+        clean.append(new)
+    # Collapse consecutive same-role turns into one (alternation rule)
+    merged: List[Dict[str, Any]] = []
+    for m in clean:
+        if merged and merged[-1]["role"] == m["role"]:
+            prev = merged[-1]
+            prev_c = prev.get("content") or ""
+            new_c = m.get("content") or ""
+            prev["content"] = f"{prev_c}\n\n{new_c}" if prev_c else new_c
+        else:
+            merged.append(m)
+    return merged

scripts/compression_eval/probes/config-build-competitive-scouts.probes.json

@@ -0,0 +1,96 @@
+{
+  "fixture": "config-build-competitive-scouts",
+  "description": "Probes for the competitive-scout cron-job setup session. Anchors are which agents were configured, which day of the week each runs, and the full final schedule. This fixture most directly tests artifact-trail and iterative-merge because the job list grows by one per user turn.",
+  "probes": [
+    {
+      "id": "recall-first-repo",
+      "type": "recall",
+      "question": "What was the first repository the user asked to create a scout cron for, and on what day of the week?",
+      "expected_facts": ["openclaw", "Sunday"]
+    },
+    {
+      "id": "recall-closed-source-target",
+      "type": "recall",
+      "question": "One of the scout targets does not have an open-source repository and had to be configured as a web scan instead. Which one, and on what day?",
+      "expected_facts": ["claude code", "Friday", "web scan"]
+    },
+    {
+      "id": "artifact-all-jobs",
+      "type": "artifact",
+      "question": "List every scout cron job created in this session.",
+      "expected_facts": [
+        "openclaw-pr-scout",
+        "nanoclaw-pr-scout",
+        "ironclaw-pr-scout",
+        "kilocode-pr-scout",
+        "codex-pr-scout",
+        "gemini-cli-pr-scout",
+        "cline-pr-scout",
+        "opencode-pr-scout",
+        "claude-code-scout",
+        "aider-pr-scout",
+        "roocode-pr-scout"
+      ]
+    },
+    {
+      "id": "artifact-final-schedule",
+      "type": "artifact",
+      "question": "What is the final weekly schedule? Give the day and the agents scanned on each day.",
+      "expected_facts": [
+        "Sun: openclaw, nanoclaw, ironclaw",
+        "Mon: kilo code",
+        "Tue: codex",
+        "Wed: gemini cli, cline",
+        "Thu: opencode",
+        "Fri: claude code",
+        "Sat: aider, roo"
+      ]
+    },
+    {
+      "id": "artifact-sunday-count",
+      "type": "artifact",
+      "question": "How many cron jobs run on Sunday?",
+      "expected_facts": ["3", "three", "openclaw, nanoclaw, ironclaw"]
+    },
+    {
+      "id": "artifact-total-count",
+      "type": "artifact",
+      "question": "How many scout cron jobs were created in total by the end of the session?",
+      "expected_facts": ["11", "eleven"]
+    },
+    {
+      "id": "decision-kilo-open-source",
+      "type": "decision",
+      "question": "The user asked whether Kilo Code is open source. What was the answer, and what did the user decide to do with it?",
+      "expected_facts": [
+        "yes, open source",
+        "Kilo-Org/kilocode",
+        "added as Monday scout"
+      ]
+    },
+    {
+      "id": "decision-saturday-fill",
+      "type": "decision",
+      "question": "Saturday was the last open day at one point. Which scout(s) were placed on Saturday, and why were those chosen?",
+      "expected_facts": ["aider", "roo", "filled in last based on openrouter popularity / cli comparison rankings"]
+    },
+    {
+      "id": "continuation-execution-time",
+      "type": "continuation",
+      "question": "At what local time of day do these scout cron jobs run?",
+      "expected_facts": ["10 AM Pacific", "17:00 UTC", "0 17 * * *"]
+    },
+    {
+      "id": "continuation-skill-used",
+      "type": "continuation",
+      "question": "Each scout job runs with a specific skill preloaded. Which one?",
+      "expected_facts": ["hermes-agent-dev"]
+    },
+    {
+      "id": "continuation-weekday-coverage",
+      "type": "continuation",
+      "question": "After the session ended, are there any weekdays still uncovered by a scout job?",
+      "expected_facts": ["no", "all 7 days covered", "full week loaded"]
+    }
+  ]
+}

scripts/compression_eval/probes/debug-session-feishu-id-model.probes.json

@@ -0,0 +1,72 @@
+{
+  "fixture": "debug-session-feishu-id-model",
+  "description": "Probes for the Feishu identity-model PR #8388 triage session. Anchors are the PR number, what the PR actually contained, what upstream docs confirmed, and the final decision + reasoning.",
+  "probes": [
+    {
+      "id": "recall-pr-number",
+      "type": "recall",
+      "question": "What is the PR number under review in this session, and what repository is it against?",
+      "expected_facts": ["PR #8388", "NousResearch/hermes-agent", "hermes-agent"]
+    },
+    {
+      "id": "recall-bug-claim",
+      "type": "recall",
+      "question": "What is the core bug the PR claims to fix? Be specific about the identifier involved.",
+      "expected_facts": ["open_id", "app-scoped", "not canonical", "Feishu identity model"]
+    },
+    {
+      "id": "recall-upstream-confirmation",
+      "type": "recall",
+      "question": "Do upstream Feishu/Lark docs confirm that open_id is app-scoped rather than a canonical cross-app identity?",
+      "expected_facts": ["yes", "confirmed", "open.feishu.cn", "same user has different Open IDs in different apps"]
+    },
+    {
+      "id": "artifact-pr-scope",
+      "type": "artifact",
+      "question": "Roughly how large is PR #8388, and which gateway subsystems does it touch beyond the Feishu adapter?",
+      "expected_facts": ["4647 lines", "gateway/run.py", "cron/scheduler.py", "gateway/config.py", "multi-account", "bind"]
+    },
+    {
+      "id": "artifact-new-tool",
+      "type": "artifact",
+      "question": "Does the PR add a new tool file? If so, what is its path?",
+      "expected_facts": ["tools/feishu_id_tool.py", "new file"]
+    },
+    {
+      "id": "decision-pr-assessment",
+      "type": "decision",
+      "question": "What is the reviewer's overall assessment of PR #8388 — approve, reject, or something more nuanced? Explain in one sentence.",
+      "expected_facts": [
+        "core claim is correct",
+        "scope is wrong",
+        "bait-and-switch",
+        "overbuilt",
+        "implement cleaner ourselves"
+      ]
+    },
+    {
+      "id": "decision-core-claim-validity",
+      "type": "decision",
+      "question": "Setting aside the PR's size, is the underlying identity-model concern technically valid or not?",
+      "expected_facts": ["technically valid", "correct", "open_id is app-scoped"]
+    },
+    {
+      "id": "continuation-next-action",
+      "type": "continuation",
+      "question": "Based on the review outcome, what is the next action the agent has been asked to take regarding this PR?",
+      "expected_facts": ["close the PR", "implement ourselves", "cleaner", "less complex"]
+    },
+    {
+      "id": "continuation-implementation-scope",
+      "type": "continuation",
+      "question": "If implementing the Feishu fix cleanly ourselves, which specific behaviour needs to change — what should replace the current use of open_id?",
+      "expected_facts": ["use union_id", "or user_id", "canonical identity", "cross-app stable ID"]
+    },
+    {
+      "id": "continuation-sources-to-reference",
+      "type": "continuation",
+      "question": "Which upstream documentation sources were fetched during review that should be referenced when writing the clean implementation?",
+      "expected_facts": ["open.feishu.cn", "open.larkoffice.com", "user-identity-introduction"]
+    }
+  ]
+}

scripts/compression_eval/probes/feature-impl-context-priority.probes.json

@@ -0,0 +1,74 @@
+{
+  "fixture": "feature-impl-context-priority",
+  "description": "Probes for the .hermes.md / AGENTS.md / CLAUDE.md / .cursorrules priority feature session. Anchors are the concrete facts the next assistant would need to continue: user's priority order, files modified, helper-function structure, live-test scenarios, and PR number.",
+  "probes": [
+    {
+      "id": "recall-priority-order",
+      "type": "recall",
+      "question": "What is the priority order the user asked for when multiple project-context files are present? List them from highest to lowest priority.",
+      "expected_facts": [".hermes.md", "AGENTS.md", "CLAUDE.md", ".cursorrules", "highest to lowest"]
+    },
+    {
+      "id": "recall-selection-mode",
+      "type": "recall",
+      "question": "When multiple context files exist in the same directory, does the agent now load all of them or pick only one?",
+      "expected_facts": ["only one", "priority-based selection", "highest-priority winner"]
+    },
+    {
+      "id": "artifact-files-modified",
+      "type": "artifact",
+      "question": "Which files in the hermes-agent repository were modified during this session? List them.",
+      "expected_facts": [
+        "agent/prompt_builder.py",
+        "tests/agent/test_prompt_builder.py"
+      ]
+    },
+    {
+      "id": "artifact-helper-functions",
+      "type": "artifact",
+      "question": "The session introduced separate helper functions for each context-file type. What are their names?",
+      "expected_facts": [
+        "_load_hermes_md",
+        "_load_agents_md",
+        "_load_claude_md",
+        "_load_cursorrules"
+      ]
+    },
+    {
+      "id": "artifact-test-scenarios",
+      "type": "artifact",
+      "question": "A scratch directory was created with scenario subdirectories to live-test the priority chain. Roughly how many scenarios, and what directory was it created under?",
+      "expected_facts": ["10 scenarios", "/tmp/context-priority-test"]
+    },
+    {
+      "id": "decision-claude-md-was-unsupported",
+      "type": "decision",
+      "question": "What was the finding about CLAUDE.md support in the existing loader before this session's changes?",
+      "expected_facts": ["CLAUDE.md was not handled", "not supported", "new handler added"]
+    },
+    {
+      "id": "decision-load-all-or-one",
+      "type": "decision",
+      "question": "Was the decision to load multiple context files when present, or to load only the highest-priority one? Explain the reasoning in one sentence.",
+      "expected_facts": ["load only one", "highest priority", "user preference", "do not want to load multiple"]
+    },
+    {
+      "id": "continuation-pr-number-and-status",
+      "type": "continuation",
+      "question": "A pull request was opened for this feature. What is the PR number and what is its merge status?",
+      "expected_facts": ["PR #2301", "merged", "squash"]
+    },
+    {
+      "id": "continuation-test-suite-result",
+      "type": "continuation",
+      "question": "What was the result of the full test suite run after the implementation changes?",
+      "expected_facts": ["5680 passed", "0 failures", "clean"]
+    },
+    {
+      "id": "continuation-next-step",
+      "type": "continuation",
+      "question": "If asked to pick up this session, what is the current state of main? Anything left to do?",
+      "expected_facts": ["merged to main", "main is current", "nothing outstanding", "pulled"]
+    }
+  ]
+}

scripts/compression_eval/report.py

@@ -0,0 +1,235 @@
+"""Markdown report rendering + diff-against-baseline for compression-eval runs.
+
+Report format is optimised for pasting directly into a PR description.
+Top-of-report table is the per-fixture medians; below that is the
+probe-by-probe miss list (scores < 3.0 on overall).
+
+Diff mode (``compare_to``) emits a second table with deltas per fixture
+per dimension against a previous run directory.
+"""
+from __future__ import annotations
+
+import json
+import statistics
+from pathlib import Path
+from typing import Any, Dict, List, Optional
+
+from rubric import DIMENSIONS
+
+
+def write_run_json(
+    *,
+    results_dir: Path,
+    fixture_name: str,
+    run_index: int,
+    payload: Dict[str, Any],
+) -> Path:
+    """Dump one fixture's per-run results as JSON for later diffing."""
+    results_dir.mkdir(parents=True, exist_ok=True)
+    path = results_dir / f"{fixture_name}-run-{run_index}.json"
+    with path.open("w") as fh:
+        json.dump(payload, fh, indent=2, ensure_ascii=False)
+    return path
+
+
+def _median(values: List[float]) -> float:
+    return statistics.median(values) if values else 0.0
+
+
+def _format_score(value: float) -> str:
+    return f"{value:.2f}"
+
+
+def _format_delta(baseline: float, current: float) -> str:
+    delta = current - baseline
+    if abs(delta) < 0.01:
+        return f"{current:.2f} (±0)"
+    sign = "+" if delta > 0 else ""
+    return f"{current:.2f} ({sign}{delta:.2f})"
+
+
+def summarize_fixture_runs(
+    fixture_runs: List[Dict[str, Any]],
+) -> Dict[str, Any]:
+    """Collapse N runs of one fixture into per-dimension medians + metadata.
+
+    Each run payload is {probes: [{id, type, scores: {...}, overall, ...}]}.
+    Returns {fixture_name, runs, dimension_medians, overall_median, misses}.
+    """
+    if not fixture_runs:
+        return {}
+
+    fixture_name = fixture_runs[0]["fixture_name"]
+    n_runs = len(fixture_runs)
+
+    # Per-probe-per-dimension aggregation across runs
+    probe_ids = [p["id"] for p in fixture_runs[0]["probes"]]
+    per_probe: Dict[str, Dict[str, List[float]]] = {
+        pid: {d: [] for d in DIMENSIONS} for pid in probe_ids
+    }
+    per_probe_overall: Dict[str, List[float]] = {pid: [] for pid in probe_ids}
+
+    for run in fixture_runs:
+        for p in run["probes"]:
+            pid = p["id"]
+            for d in DIMENSIONS:
+                per_probe[pid][d].append(p["scores"].get(d, 0))
+            per_probe_overall[pid].append(p["overall"])
+
+    # Median each probe across runs, then median those medians across probes
+    dim_medians: Dict[str, float] = {}
+    for d in DIMENSIONS:
+        per_probe_med = [_median(per_probe[pid][d]) for pid in probe_ids]
+        dim_medians[d] = _median(per_probe_med)
+    overall_median = _median([_median(per_probe_overall[pid]) for pid in probe_ids])
+
+    # Misses = probes whose median overall < 3.0
+    misses: List[Dict[str, Any]] = []
+    for pid in probe_ids:
+        med = _median(per_probe_overall[pid])
+        if med < 3.0:
+            # Pull the notes from the last run to give the reader a
+            # concrete clue. (Taking the most recent run is fine —
+            # notes vary across runs and any one is illustrative.)
+            notes = ""
+            probe_type = ""
+            for p in fixture_runs[-1]["probes"]:
+                if p["id"] == pid:
+                    notes = p.get("notes", "")
+                    probe_type = p.get("type", "")
+                    break
+            misses.append({
+                "id": pid,
+                "type": probe_type,
+                "overall_median": med,
+                "notes": notes,
+            })
+
+    return {
+        "fixture_name": fixture_name,
+        "runs": n_runs,
+        "dimension_medians": dim_medians,
+        "overall_median": overall_median,
+        "misses": misses,
+        "compression": fixture_runs[0].get("compression", {}),
+    }
+
+
+def render_report(
+    *,
+    label: str,
+    compressor_model: str,
+    judge_model: str,
+    runs_per_fixture: int,
+    summaries: List[Dict[str, Any]],
+    baseline_summaries: Optional[List[Dict[str, Any]]] = None,
+) -> str:
+    """Render the full markdown report.
+
+    baseline_summaries is the same shape as summaries, sourced from a
+    previous run (via --compare-to). When present, dimension scores in
+    the main table render with deltas.
+    """
+    lines: List[str] = []
+    lines.append(f"## Compression eval — label `{label}`")
+    lines.append("")
+    lines.append(f"- Compressor model: `{compressor_model}`")
+    lines.append(f"- Judge model: `{judge_model}`")
+    lines.append(f"- Runs per fixture: {runs_per_fixture}")
+    lines.append("- Medians over runs reported")
+    if baseline_summaries:
+        lines.append("- Deltas shown against baseline run")
+    lines.append("")
+
+    baseline_by_name: Dict[str, Dict[str, Any]] = {}
+    if baseline_summaries:
+        baseline_by_name = {s["fixture_name"]: s for s in baseline_summaries}
+
+    # Main table
+    header = ["Fixture"] + DIMENSIONS + ["overall"]
+    lines.append("| " + " | ".join(header) + " |")
+    lines.append("|" + "|".join(["---"] * len(header)) + "|")
+    for s in summaries:
+        row = [s["fixture_name"]]
+        baseline = baseline_by_name.get(s["fixture_name"])
+        for d in DIMENSIONS:
+            cur = s["dimension_medians"][d]
+            if baseline and d in baseline.get("dimension_medians", {}):
+                row.append(_format_delta(baseline["dimension_medians"][d], cur))
+            else:
+                row.append(_format_score(cur))
+        if baseline:
+            row.append(_format_delta(baseline["overall_median"], s["overall_median"]))
+        else:
+            row.append(_format_score(s["overall_median"]))
+        lines.append("| " + " | ".join(row) + " |")
+    lines.append("")
+
+    # Compression metadata
+    lines.append("### Compression summary")
+    lines.append("")
+    lines.append("| Fixture | Pre tokens | Post tokens | Ratio | Pre msgs | Post msgs |")
+    lines.append("|---|---|---|---|---|---|")
+    for s in summaries:
+        c = s.get("compression", {})
+        lines.append(
+            "| {name} | {pre} | {post} | {ratio:.1%} | {pm} | {pom} |".format(
+                name=s["fixture_name"],
+                pre=c.get("pre_tokens", 0),
+                post=c.get("post_tokens", 0),
+                ratio=c.get("compression_ratio", 0.0),
+                pm=c.get("pre_message_count", 0),
+                pom=c.get("post_message_count", 0),
+            )
+        )
+    lines.append("")
+
+    # Per-probe misses
+    any_misses = any(s["misses"] for s in summaries)
+    if any_misses:
+        lines.append("### Probes scoring below 3.0 overall (median)")
+        lines.append("")
+        for s in summaries:
+            if not s["misses"]:
+                continue
+            lines.append(f"**{s['fixture_name']}**")
+            for m in s["misses"]:
+                note_part = f" — {m['notes']}" if m["notes"] else ""
+                lines.append(
+                    f"- `{m['id']}` ({m['type']}): "
+                    f"{m['overall_median']:.2f}{note_part}"
+                )
+            lines.append("")
+
+    lines.append("### Methodology")
+    lines.append("")
+    lines.append(
+        "Probe-based eval adapted from "
+        "https://factory.ai/news/evaluating-compression. Each fixture is "
+        "compressed in a single forced `ContextCompressor.compress()` call, "
+        "then a continuation call asks the compressor model to answer each "
+        "probe from the compressed state, then the judge model scores the "
+        "answer 0-5 on six dimensions. A single run is noisy; medians "
+        "across multiple runs are the meaningful signal. Changes below "
+        "~0.3 on any dimension are likely within run-to-run noise."
+    )
+    return "\n".join(lines) + "\n"
+
+
+def load_baseline_summaries(baseline_dir: Path) -> List[Dict[str, Any]]:
+    """Load summaries from a previous eval run for --compare-to.
+
+    Reads the dumped per-run JSONs and re-summarises them so the
+    aggregation matches whatever summariser was current at the time of
+    the new run (forward-compatible with schema additions).
+    """
+    if not baseline_dir.exists():
+        raise FileNotFoundError(f"baseline dir not found: {baseline_dir}")
+
+    by_fixture: Dict[str, List[Dict[str, Any]]] = {}
+    for path in sorted(baseline_dir.glob("*-run-*.json")):
+        with path.open() as fh:
+            payload = json.load(fh)
+        by_fixture.setdefault(payload["fixture_name"], []).append(payload)
+
+    return [summarize_fixture_runs(runs) for runs in by_fixture.values()]

scripts/compression_eval/rubric.py

@@ -0,0 +1,198 @@
+"""Rubric for probe-based compression eval grading.
+
+Six dimensions scored 0-5 by a judge model. The scoring anchors are spelled
+out so the judge interpretation is stable across runs and across judge
+models.
+
+Adapted from the methodology in
+https://factory.ai/news/evaluating-compression. Their scoreboard is not
+adopted; only the dimension definitions and the 0-5 scale.
+"""
+from __future__ import annotations
+
+from typing import Any, Dict, List
+
+# Canonical dimension order. All reports, parsers, and comparisons derive
+# from this list — do not hardcode the order elsewhere.
+DIMENSIONS: List[str] = [
+    "accuracy",
+    "context_awareness",
+    "artifact_trail",
+    "completeness",
+    "continuity",
+    "instruction_following",
+]
+
+DIMENSION_DESCRIPTIONS: Dict[str, str] = {
+    "accuracy": (
+        "Are concrete facts correct — file paths, function names, PR/issue "
+        "numbers, error codes, command outputs, line numbers? A single wrong "
+        "path or error code should cost points. Vague but non-contradicting "
+        "answers score mid-range."
+    ),
+    "context_awareness": (
+        "Does the answer reflect the CURRENT state of the session, not a "
+        "mid-session snapshot? For example, if a file was modified then "
+        "reverted, does the answer describe the reverted state? If three "
+        "PRs were opened, does the answer know which was merged?"
+    ),
+    "artifact_trail": (
+        "Does the answer correctly enumerate the artifacts (files read, "
+        "files modified, commands run, tools called, PRs opened, cron jobs "
+        "created)? Missing artifacts cost more than extra unrelated ones."
+    ),
+    "completeness": (
+        "Does the answer address ALL parts of the probe question? If the "
+        "probe asks for three things and only two are answered, that is "
+        "incomplete regardless of accuracy on the two."
+    ),
+    "continuity": (
+        "Could the next assistant continue the work using only this answer, "
+        "without having to re-fetch files or re-explore the codebase? An "
+        "answer that lists files by name but doesn't mention the change is "
+        "poor continuity even if accurate."
+    ),
+    "instruction_following": (
+        "Is the answer in the format the probe requested (list, number, "
+        "short phrase, yes/no)? Ignore tone and length, only assess "
+        "whether the requested form was honoured."
+    ),
+}
+
+SCORE_SCALE: Dict[int, str] = {
+    0: "No useful information; wrong or hallucinated.",
+    1: "Major gaps or a key fact is wrong.",
+    2: "Partially correct but significant omissions.",
+    3: "Mostly correct with minor omissions or imprecision.",
+    4: "Correct and complete with only trivial imprecision.",
+    5: "Fully correct, complete, and in the requested format.",
+}
+
+
+_RUBRIC_HEADER = """You are an evaluator grading a single answer produced by an AI assistant \
+that was given a COMPRESSED handoff summary of an earlier conversation and \
+asked a probe question. You are NOT evaluating the compression summary \
+directly — you are evaluating whether the answer the assistant produced \
+from that summary is correct, complete, and useful.
+
+Grade on six dimensions, each 0-5:
+
+{dimension_block}
+
+0-5 scale:
+{scale_block}
+
+Grade strictly. Fractional scores are NOT allowed — output integers only. \
+If the answer is ambiguous, use the lower of the two candidate scores."""
+
+
+def build_judge_prompt(
+    *,
+    probe_question: str,
+    probe_type: str,
+    expected_facts: List[str],
+    assistant_answer: str,
+) -> str:
+    """Build the full judge prompt for one (probe, answer) pair.
+
+    The judge is told the expected_facts up front so grading is anchored to
+    concrete signal rather than judge taste. Expected facts are intentionally
+    NOT shown to the assistant that produces the answer.
+    """
+    dim_block = "\n".join(
+        f"- {d}: {DIMENSION_DESCRIPTIONS[d]}" for d in DIMENSIONS
+    )
+    scale_block = "\n".join(
+        f"  {score}: {desc}" for score, desc in sorted(SCORE_SCALE.items())
+    )
+    header = _RUBRIC_HEADER.format(
+        dimension_block=dim_block,
+        scale_block=scale_block,
+    )
+
+    expected_block = (
+        "\n".join(f"- {f}" for f in expected_facts) if expected_facts else "(none provided)"
+    )
+
+    output_schema = (
+        "Respond with ONLY a JSON object, no prose before or after, matching "
+        "this schema exactly:\n"
+        "{\n"
+        '  "accuracy": <int 0-5>,\n'
+        '  "context_awareness": <int 0-5>,\n'
+        '  "artifact_trail": <int 0-5>,\n'
+        '  "completeness": <int 0-5>,\n'
+        '  "continuity": <int 0-5>,\n'
+        '  "instruction_following": <int 0-5>,\n'
+        '  "notes": "<one short sentence, <=200 chars, identifying the '
+        'single biggest issue with the answer if any>"\n'
+        "}"
+    )
+
+    return (
+        f"{header}\n\n"
+        f"PROBE TYPE: {probe_type}\n\n"
+        f"PROBE QUESTION:\n{probe_question}\n\n"
+        f"EXPECTED FACTS (the answer should contain these concrete anchors; "
+        f"missing any is a material defect in accuracy and/or completeness):\n"
+        f"{expected_block}\n\n"
+        f"ASSISTANT ANSWER TO GRADE:\n{assistant_answer}\n\n"
+        f"{output_schema}"
+    )
+
+
+def parse_judge_response(raw: str) -> Dict[str, Any]:
+    """Parse the judge model's JSON response into a score dict.
+
+    Tolerates surrounding prose (judges ignore instructions sometimes) by
+    extracting the first {...} block. Validates that every dimension is
+    present as an integer 0-5.
+
+    Returns dict with keys: scores (dim->int), notes (str), overall (float).
+    Raises ValueError if the response cannot be parsed into a complete
+    score set.
+    """
+    import json
+    import re
+
+    if not raw or not raw.strip():
+        raise ValueError("empty judge response")
+
+    # Strip code fences and any ```json prefix judges sometimes emit.
+    stripped = raw.strip()
+    fence_match = re.match(r"^```(?:json)?\s*(.*?)\s*```$", stripped, re.DOTALL)
+    if fence_match:
+        stripped = fence_match.group(1).strip()
+
+    # Extract the first {...} block greedy-to-matching-brace.
+    brace_match = re.search(r"\{.*\}", stripped, re.DOTALL)
+    if not brace_match:
+        raise ValueError(f"no JSON object found in judge response: {raw[:200]!r}")
+    candidate = brace_match.group(0)
+
+    try:
+        parsed = json.loads(candidate)
+    except json.JSONDecodeError as exc:
+        raise ValueError(f"judge response not valid JSON: {exc}; raw={candidate[:200]!r}")
+
+    scores: Dict[str, int] = {}
+    for dim in DIMENSIONS:
+        if dim not in parsed:
+            raise ValueError(f"judge response missing dimension {dim!r}: {parsed}")
+        value = parsed[dim]
+        if isinstance(value, bool) or not isinstance(value, (int, float)):
+            raise ValueError(f"dimension {dim} is not numeric: {value!r}")
+        int_val = int(round(value))
+        if int_val < 0 or int_val > 5:
+            raise ValueError(f"dimension {dim} out of range: {int_val}")
+        scores[dim] = int_val
+
+    notes_val = parsed.get("notes", "")
+    notes = str(notes_val)[:200] if notes_val else ""
+
+    overall = sum(scores.values()) / len(scores)
+    return {
+        "scores": scores,
+        "notes": notes,
+        "overall": overall,
+    }

scripts/compression_eval/run_eval.py

@@ -0,0 +1,383 @@
+#!/usr/bin/env python3
+"""Compression eval — entry point.
+
+Runs the full probe-based eval over one or more fixtures, produces a
+markdown report in ``results/<label>/report.md`` paired with per-run JSON
+for later diffing.
+
+Not a pytest. Requires a configured provider + credentials (same path the
+agent uses). Does not run in CI. See README.md for usage examples.
+"""
+from __future__ import annotations
+
+import json
+import logging
+import sys
+import time
+from datetime import datetime
+from pathlib import Path
+from typing import Any, Dict, List, Optional
+
+_HERE = Path(__file__).resolve().parent
+_REPO_ROOT = _HERE.parents[1]
+if str(_REPO_ROOT) not in sys.path:
+    sys.path.insert(0, str(_REPO_ROOT))
+# Make our sibling modules importable whether invoked as a script or as -m.
+if str(_HERE) not in sys.path:
+    sys.path.insert(0, str(_HERE))
+
+try:
+    import fire  # noqa: F401
+except ImportError:
+    fire = None  # fallback to argparse if fire is unavailable
+
+from hermes_cli.runtime_provider import resolve_runtime_provider  # noqa: E402
+
+from compressor_driver import run_compression  # noqa: E402
+from grader import answer_probe, grade_probe  # noqa: E402
+from report import (  # noqa: E402
+    load_baseline_summaries,
+    render_report,
+    summarize_fixture_runs,
+    write_run_json,
+)
+
+logger = logging.getLogger("compression_eval")
+
+
+FIXTURES_DIR = _HERE / "fixtures"
+PROBES_DIR = _HERE / "probes"
+RESULTS_DIR = _HERE / "results"
+
+
+def _load_fixture(name: str) -> Dict[str, Any]:
+    path = FIXTURES_DIR / f"{name}.json"
+    if not path.exists():
+        available = sorted(p.stem for p in FIXTURES_DIR.glob("*.json"))
+        raise FileNotFoundError(
+            f"Fixture not found: {name}. Available: {available}"
+        )
+    with path.open() as fh:
+        return json.load(fh)
+
+
+def _load_probes(name: str) -> Dict[str, Any]:
+    path = PROBES_DIR / f"{name}.probes.json"
+    if not path.exists():
+        raise FileNotFoundError(f"Probe bank not found for fixture {name}: {path}")
+    with path.open() as fh:
+        return json.load(fh)
+
+
+def _resolve_runtime(
+    *,
+    provider_override: Optional[str],
+    model_override: Optional[str],
+) -> Dict[str, Any]:
+    """Resolve provider credentials via the same path the agent uses."""
+    runtime = resolve_runtime_provider(
+        requested=provider_override,
+        target_model=model_override,
+    )
+    if not runtime.get("api_key") and not runtime.get("base_url"):
+        raise RuntimeError(
+            "No provider configured. Run `hermes setup` or set provider "
+            "credentials in the environment before running the eval."
+        )
+    return runtime
+
+
+def _available_fixtures() -> List[str]:
+    return sorted(p.stem for p in FIXTURES_DIR.glob("*.json"))
+
+
+def _run_one_fixture(
+    *,
+    fixture_name: str,
+    run_index: int,
+    compressor_runtime: Dict[str, Any],
+    compressor_model: str,
+    judge_runtime: Dict[str, Any],
+    judge_model: str,
+    focus_topic: Optional[str],
+) -> Dict[str, Any]:
+    fx = _load_fixture(fixture_name)
+    probes = _load_probes(fixture_name)
+
+    logger.info(
+        "[%s run=%d] compressing (%d messages, ctx=%d)",
+        fixture_name, run_index, len(fx["messages"]), fx["context_length"],
+    )
+    compression = run_compression(
+        messages=fx["messages"],
+        compressor_model=compressor_model,
+        compressor_provider=compressor_runtime["provider"],
+        compressor_base_url=compressor_runtime["base_url"],
+        compressor_api_key=compressor_runtime["api_key"],
+        compressor_api_mode=compressor_runtime.get("api_mode", ""),
+        context_length=fx["context_length"],
+        focus_topic=focus_topic,
+        # Force the compressor to use the model we're testing, bypassing
+        # any auxiliary.compression.model config override. Without this,
+        # ContextCompressor.call_llm(task="compression") routes through
+        # the user's config which may pin a different model (e.g.
+        # google/gemini-3-flash-preview).
+        summary_model_override=compressor_model,
+    )
+    logger.info(
+        "[%s run=%d] compressed %d -> %d tokens (%.1f%%)",
+        fixture_name, run_index,
+        compression["pre_tokens"], compression["post_tokens"],
+        compression["compression_ratio"] * 100,
+    )
+
+    probe_results: List[Dict[str, Any]] = []
+    for probe in probes["probes"]:
+        t0 = time.monotonic()
+        try:
+            answer = answer_probe(
+                compressed_messages=compression["compressed_messages"],
+                probe_question=probe["question"],
+                provider=compressor_runtime["provider"],
+                model=compressor_model,
+                base_url=compressor_runtime["base_url"],
+                api_key=compressor_runtime["api_key"],
+            )
+        except Exception as exc:
+            logger.warning(
+                "[%s run=%d probe=%s] continuation failed: %s",
+                fixture_name, run_index, probe["id"], exc,
+            )
+            answer = ""
+
+        try:
+            grade = grade_probe(
+                probe_question=probe["question"],
+                probe_type=probe["type"],
+                expected_facts=probe.get("expected_facts", []),
+                assistant_answer=answer,
+                judge_provider=judge_runtime["provider"],
+                judge_model=judge_model,
+                judge_base_url=judge_runtime["base_url"],
+                judge_api_key=judge_runtime["api_key"],
+            )
+        except Exception as exc:
+            logger.warning(
+                "[%s run=%d probe=%s] grading failed: %s",
+                fixture_name, run_index, probe["id"], exc,
+            )
+            from rubric import DIMENSIONS
+            grade = {
+                "scores": {d: 0 for d in DIMENSIONS},
+                "notes": f"grading error: {exc}",
+                "overall": 0.0,
+                "raw": "",
+                "parse_error": str(exc),
+            }
+
+        elapsed = time.monotonic() - t0
+        logger.info(
+            "[%s run=%d probe=%s] overall=%.2f (%.1fs)",
+            fixture_name, run_index, probe["id"], grade["overall"], elapsed,
+        )
+
+        probe_results.append({
+            "id": probe["id"],
+            "type": probe["type"],
+            "question": probe["question"],
+            "expected_facts": probe.get("expected_facts", []),
+            "answer": answer,
+            "scores": grade["scores"],
+            "overall": grade["overall"],
+            "notes": grade["notes"],
+            "parse_error": grade["parse_error"],
+            "elapsed_seconds": elapsed,
+        })
+
+    return {
+        "fixture_name": fixture_name,
+        "run_index": run_index,
+        "compression": {
+            "pre_tokens": compression["pre_tokens"],
+            "post_tokens": compression["post_tokens"],
+            "compression_ratio": compression["compression_ratio"],
+            "pre_message_count": compression["pre_message_count"],
+            "post_message_count": compression["post_message_count"],
+            "summary_text": compression["summary_text"],
+        },
+        "probes": probe_results,
+    }
+
+
+def _coerce_fixtures_arg(arg: Optional[str]) -> List[str]:
+    if not arg:
+        return _available_fixtures()
+    return [s.strip() for s in arg.split(",") if s.strip()]
+
+
+def main(
+    fixtures: Optional[str] = None,
+    runs: int = 3,
+    judge_model: Optional[str] = None,
+    judge_provider: Optional[str] = None,
+    compressor_model: Optional[str] = None,
+    compressor_provider: Optional[str] = None,
+    label: Optional[str] = None,
+    focus_topic: Optional[str] = None,
+    compare_to: Optional[str] = None,
+    verbose: bool = False,
+) -> int:
+    """Run the compression eval.
+
+    Args:
+        fixtures: Comma-separated fixture names; default = all in fixtures/.
+        runs: Runs per fixture. Medians reported. Default 3.
+        judge_model: Override the judge model (default = same as
+            compressor model resolved from config).
+        judge_provider: Override the judge provider.
+        compressor_model: Override the compressor model (default =
+            whatever resolve_runtime_provider returns for the active
+            configuration).
+        compressor_provider: Override the compressor provider.
+        label: Output subdirectory under results/. Default = timestamp.
+        focus_topic: Optional focus topic passed through to
+            ContextCompressor.compress(focus_topic=...).
+        compare_to: Path to a previous run directory (e.g.
+            results/2026-04-24_baseline) to diff against in the report.
+        verbose: Print debug logs.
+    """
+    logging.basicConfig(
+        level=logging.DEBUG if verbose else logging.INFO,
+        format="%(asctime)s %(levelname)s %(name)s: %(message)s",
+    )
+
+    fixture_names = _coerce_fixtures_arg(fixtures)
+    # Validate every fixture has a probe bank before spending any money.
+    for name in fixture_names:
+        _load_fixture(name)
+        _load_probes(name)
+
+    compressor_runtime = _resolve_runtime(
+        provider_override=compressor_provider,
+        model_override=compressor_model,
+    )
+    effective_compressor_model = (
+        compressor_model or compressor_runtime.get("resolved_model") or "auto"
+    )
+    if effective_compressor_model == "auto":
+        # resolve_runtime_provider doesn't always fill resolved_model;
+        # fall back to reading model.default from config.
+        from hermes_cli.config import load_config
+        cfg = load_config()
+        mc = cfg.get("model", {}) or {}
+        if isinstance(mc, dict):
+            effective_compressor_model = (
+                mc.get("default") or mc.get("model") or "anthropic/claude-sonnet-4.6"
+            )
+        else:
+            effective_compressor_model = str(mc) or "anthropic/claude-sonnet-4.6"
+
+    if judge_provider or judge_model:
+        judge_runtime = _resolve_runtime(
+            provider_override=judge_provider,
+            model_override=judge_model,
+        )
+        effective_judge_model = judge_model or effective_compressor_model
+    else:
+        judge_runtime = compressor_runtime
+        effective_judge_model = effective_compressor_model
+
+    effective_label = label or datetime.now().strftime("%Y-%m-%d_%H-%M-%S")
+    out_dir = RESULTS_DIR / effective_label
+    out_dir.mkdir(parents=True, exist_ok=True)
+
+    logger.info(
+        "Compression eval starting: label=%s fixtures=%s runs=%d "
+        "compressor=%s judge=%s out=%s",
+        effective_label, fixture_names, runs,
+        effective_compressor_model, effective_judge_model, out_dir,
+    )
+
+    all_summaries: List[Dict[str, Any]] = []
+    for fixture_name in fixture_names:
+        per_run: List[Dict[str, Any]] = []
+        for run_i in range(1, runs + 1):
+            payload = _run_one_fixture(
+                fixture_name=fixture_name,
+                run_index=run_i,
+                compressor_runtime=compressor_runtime,
+                compressor_model=effective_compressor_model,
+                judge_runtime=judge_runtime,
+                judge_model=effective_judge_model,
+                focus_topic=focus_topic,
+            )
+            write_run_json(
+                results_dir=out_dir,
+                fixture_name=fixture_name,
+                run_index=run_i,
+                payload=payload,
+            )
+            per_run.append(payload)
+        summary = summarize_fixture_runs(per_run)
+        all_summaries.append(summary)
+
+    baseline_summaries: Optional[List[Dict[str, Any]]] = None
+    if compare_to:
+        baseline_path = Path(compare_to)
+        if not baseline_path.is_absolute():
+            baseline_path = _HERE / baseline_path
+        baseline_summaries = load_baseline_summaries(baseline_path)
+
+    report_md = render_report(
+        label=effective_label,
+        compressor_model=effective_compressor_model,
+        judge_model=effective_judge_model,
+        runs_per_fixture=runs,
+        summaries=all_summaries,
+        baseline_summaries=baseline_summaries,
+    )
+    report_path = out_dir / "report.md"
+    report_path.write_text(report_md)
+
+    # Also write a machine-readable summary.json alongside the human report.
+    summary_path = out_dir / "summary.json"
+    with summary_path.open("w") as fh:
+        json.dump(
+            {
+                "label": effective_label,
+                "compressor_model": effective_compressor_model,
+                "judge_model": effective_judge_model,
+                "runs_per_fixture": runs,
+                "fixtures": all_summaries,
+            },
+            fh,
+            indent=2,
+            ensure_ascii=False,
+        )
+
+    print()
+    print(report_md)
+    print(f"Report written to {report_path}")
+    print(f"Per-run JSON in {out_dir}")
+    return 0
+
+
+if __name__ == "__main__":
+    if fire is not None:
+        # fire preserves docstrings as --help and handles kwarg-style CLI.
+        sys.exit(fire.Fire(main))
+    else:
+        import argparse
+        p = argparse.ArgumentParser()
+        p.add_argument("--fixtures")
+        p.add_argument("--runs", type=int, default=3)
+        p.add_argument("--judge-model", dest="judge_model")
+        p.add_argument("--judge-provider", dest="judge_provider")
+        p.add_argument("--compressor-model", dest="compressor_model")
+        p.add_argument("--compressor-provider", dest="compressor_provider")
+        p.add_argument("--label")
+        p.add_argument("--focus-topic", dest="focus_topic")
+        p.add_argument("--compare-to", dest="compare_to")
+        p.add_argument("--verbose", action="store_true")
+        args = p.parse_args()
+        sys.exit(main(**vars(args)))

scripts/compression_eval/scrub_fixtures.py

@@ -0,0 +1,381 @@
+"""One-shot fixture scrubber for scripts/compression_eval/fixtures/.
+
+Source: ~/.hermes/sessions/<file>.jsonl
+Output: .worktrees/.../scripts/compression_eval/fixtures/<name>.json
+
+Scrubbing passes:
+  1. agent.redact.redact_sensitive_text — API keys, tokens, connection strings
+  2. Username paths — /home/teknium/ → /home/user/, ~/.hermes/ preserved as-is
+     (that path is universal)
+  3. Personal handles — "Teknium"/"teknium"/"teknium1" → "user"
+  4. Reasoning scratchpads — strip <REASONING_SCRATCHPAD>...</REASONING_SCRATCHPAD>
+     blocks and <think>...</think> tags (personality leakage risk)
+  5. session_meta line — drop entirely, we only need the messages
+  6. User message personality — lightly paraphrase the first user message to keep
+     task intent while removing "vibe"; subsequent user turns kept verbatim
+     since they're short instructions
+
+The fixture format matches DESIGN.md:
+  {
+    "name": "...",
+    "description": "...",
+    "model": "...",           # best guess from original session
+    "context_length": 200000,
+    "messages": [...],        # OpenAI-format, only role/content/tool_calls/tool_call_id/tool_name
+    "notes": "Scrubbed from ~/.hermes/sessions/... on 2026-04-24"
+  }
+"""
+from __future__ import annotations
+
+import json
+import re
+import sys
+from datetime import datetime
+from pathlib import Path
+from typing import Any, Dict, List
+
+# Resolve the hermes-agent checkout relative to this script so agent.redact
+# imports cleanly whether we run from a worktree or a main clone.
+_REPO_ROOT = Path(__file__).resolve().parents[2]
+sys.path.insert(0, str(_REPO_ROOT))
+from agent.redact import redact_sensitive_text  # noqa: E402
+
+
+SESSION_DIR = Path.home() / ".hermes" / "sessions"
+# Resolve FIXTURES_DIR relative to this script so the scrubber runs the
+# same way inside a worktree, a main checkout, or from a contributor's
+# clone at a different path.
+FIXTURES_DIR = Path(__file__).resolve().parent / "fixtures"
+
+# (source_file, output_name, description, user_first_paraphrase, model_guess, context_length, truncate_at)
+# truncate_at: keep messages[:truncate_at] (None = keep all). Applied BEFORE
+# orphan-empty-assistant cleanup.
+SPECS = [
+    (
+        "20260321_060441_fef7be92.jsonl",
+        "feature-impl-context-priority",
+        "~75-turn feature-impl: user asks how multiple project-context files "
+        "(.hermes.md / AGENTS.md / CLAUDE.md / .cursorrules) are handled when "
+        "all are present; agent investigates the codebase, designs a priority "
+        "order, patches the loader + tests, live-tests with a scenario "
+        "directory, commits to a feature branch, opens a PR, and merges after "
+        "approval. Exercises investigate → decide → implement → verify → "
+        "ship flow with clear artifact trail (2 files modified, 1 PR).",
+        (
+            "If .hermes.md, AGENTS.md, CLAUDE.md, and .cursorrules all exist in "
+            "the same directory, does the agent load all of them or pick one? "
+            "Use the hermes-agent-dev skill to check."
+        ),
+        "anthropic/claude-sonnet-4.6",
+        200000,
+        74,  # cut at "Merged and pulled. Main is current." — drops trailing unrelated cron-delivery messages
+    ),
+    (
+        "20260412_233741_3f2119a8.jsonl",
+        "debug-session-feishu-id-model",
+        "~60-turn debug/triage PR-review session: a third-party bug report "
+        "says the gateway's Feishu adapter misuses the open_id / union_id / "
+        "user_id identity model (open_id is app-scoped, not the bot's "
+        "canonical ID). An open community PR (#8388) tries to fix it. Agent "
+        "reviews the PR against current main, fetches upstream Feishu/Lark "
+        "identity docs, and produces a decision. Exercises long tool-heavy "
+        "context with PR diffs, upstream docs, and a clear decision at the "
+        "end — the classic 'can the summary still name the PR number, the "
+        "root cause, and the decision?' scenario.",
+        (
+            "A community user reports the Feishu/Lark adapter gets the identity "
+            "model wrong — open_id is app-scoped, not the bot's canonical ID. "
+            "There's an open PR #8388 trying to fix it. Use the hermes-agent-dev "
+            "skill and the pr-triage-salvage skill to review it."
+        ),
+        "anthropic/claude-sonnet-4.6",
+        200000,
+        58,  # end at "Here's my review: ..." — clean decision point before the "close it, implement cleaner" pivot
+    ),
+    (
+        "20260328_160817_77bd258b.jsonl",
+        "config-build-competitive-scouts",
+        "~60-turn iterative config/build session: user wants a set of weekly "
+        "cron jobs that scan competing AI coding agents (openclaw, nanoclaw, "
+        "ironclaw, codex, opencode, claude-code, kilo-code, gemini-cli, "
+        "cline, aider, roo) for merged PRs or web updates worth porting to "
+        "hermes-agent. User adds one target per turn; agent creates each cron "
+        "job and re-states the accumulated schedule. Exercises artifact trail "
+        "(which jobs are configured, which days) and iterative state "
+        "accumulation — the canonical case for iterative-merge summarization.",
+        (
+            "Set up a cron job for the agent every Sunday to scan all PRs "
+            "merged into openclaw that week, decide which are worth adding to "
+            "hermes-agent, and open PRs porting those features."
+        ),
+        "anthropic/claude-sonnet-4.6",
+        200000,
+        None,
+    ),
+]
+
+
+# Tool output truncation is DELIBERATELY DISABLED.
+#
+# An earlier iteration truncated tool outputs > 2KB to keep fixture JSON
+# files small, but that defeats the whole purpose of the eval. Real
+# sessions have 30KB skill_view dumps, 10KB read_file outputs, 5KB
+# web_extract bodies — compression has to either head-protect them,
+# summarize them, or drop them. A fixture without that load doesn't
+# exercise the compressor. The size win wasn't worth the signal loss.
+#
+# The function remains so the scrubbing_passes record in the fixture
+# JSON continues to truthfully describe what was applied (no-op in this
+# configuration).
+_TOOL_OUTPUT_MAX = None  # None disables truncation entirely
+
+
+def _maybe_truncate_tool_output(text: str, tool_name: str) -> str:
+    if _TOOL_OUTPUT_MAX is None or not text or len(text) <= _TOOL_OUTPUT_MAX:
+        return text
+    keep = _TOOL_OUTPUT_MAX - 200
+    head = text[:keep]
+    return (
+        head
+        + f"\n\n[... tool output truncated for fixture — original was {len(text)} chars"
+        + (f" from {tool_name}" if tool_name else "")
+        + "]"
+    )
+
+
+_PATH_RE = re.compile(r"/home/teknium\b")
+# No \b boundaries — some tool content stores newlines as the literal
+# two-char sequence "\\n" (escaped JSON), so a "\\nTeknium..." run has a
+# word char ('n') immediately before 'T' and \b fails. Substring match is
+# safer here; "Teknium" as a substring of an unrelated word is
+# implausible in this corpus.
+_USER_RE = re.compile(r"teknium1|Teknium|teknium", re.IGNORECASE)
+# Only strip scratchpads in ASSISTANT content, not tool results (might be legit)
+_SCRATCH_RE = re.compile(
+    r"<REASONING_SCRATCHPAD>.*?</REASONING_SCRATCHPAD>\s*", re.DOTALL
+)
+_THINK_RE = re.compile(r"<think>.*?</think>\s*", re.DOTALL)
+# Discord/Telegram user mention leakage in messaging-platform sessions
+_USER_MENTION_RE = re.compile(r"<@\*{3}>|<@\d+>")
+# Contributor emails (from git show output etc) — anything@domain.tld
+# Keep noreply@github-style placeholders obvious; real personal emails get
+# replaced with a contributor placeholder.
+_EMAIL_RE = re.compile(r"\b[A-Za-z0-9._%+-]+@[A-Za-z0-9.-]+\.[A-Za-z]{2,}\b")
+# "Author: Name <email>" git-show headers — rewrite the whole line
+_GIT_AUTHOR_RE = re.compile(r"Author:\s*[^<\n]+<[^>]+>")
+
+
+def _scrub_text(text: str, *, drop_scratchpads: bool = False) -> str:
+    """Apply the pipeline to a raw text string.
+
+    drop_scratchpads only affects assistant messages — tool outputs that
+    happen to contain similar markers are left alone.
+    """
+    if not text:
+        return text
+    if drop_scratchpads:
+        text = _SCRATCH_RE.sub("", text)
+        text = _THINK_RE.sub("", text)
+    text = _PATH_RE.sub("/home/user", text)
+    text = _USER_RE.sub("user", text)
+    text = _USER_MENTION_RE.sub("<@user>", text)
+    # Rewrite git "Author: Name <email>" lines before generic email replace
+    text = _GIT_AUTHOR_RE.sub("Author: contributor <contributor@example.com>", text)
+    text = _EMAIL_RE.sub("contributor@example.com", text)
+    text = redact_sensitive_text(text)
+    return text
+
+
+def _content_to_str(content: Any) -> str:
+    if content is None:
+        return ""
+    if isinstance(content, str):
+        return content
+    if isinstance(content, list):
+        parts = []
+        for p in content:
+            if isinstance(p, dict) and "text" in p:
+                parts.append(p["text"])
+            elif isinstance(p, str):
+                parts.append(p)
+        return "\n".join(parts)
+    return str(content)
+
+
+def _scrub_tool_calls(tool_calls: List[Dict[str, Any]]) -> List[Dict[str, Any]]:
+    out = []
+    for tc in tool_calls or []:
+        if not isinstance(tc, dict):
+            continue
+        fn = tc.get("function", {}) or {}
+        args = fn.get("arguments", "")
+        if isinstance(args, str):
+            args = _scrub_text(args)
+        new_tc = {
+            "id": tc.get("id", ""),
+            "type": tc.get("type", "function"),
+            "function": {
+                "name": fn.get("name", ""),
+                "arguments": args,
+            },
+        }
+        out.append(new_tc)
+    return out
+
+
+def _scrub_message(m: Dict[str, Any], *, first_user_paraphrase: str | None, user_turn_idx: List[int]) -> Dict[str, Any] | None:
+    role = m.get("role")
+    if role in (None, "session_meta"):
+        return None
+
+    content = _content_to_str(m.get("content"))
+
+    if role == "assistant":
+        content = _scrub_text(content, drop_scratchpads=True)
+    elif role == "user":
+        # Use paraphrase for the very first user turn only
+        user_turn_idx[0] += 1
+        if user_turn_idx[0] == 1 and first_user_paraphrase is not None:
+            content = first_user_paraphrase
+        else:
+            content = _scrub_text(content)
+    else:
+        content = _scrub_text(content)
+        # Truncate large tool outputs
+        if role == "tool":
+            tn = m.get("tool_name") or m.get("name") or ""
+            content = _maybe_truncate_tool_output(content, tn)
+
+    new_msg: Dict[str, Any] = {"role": role, "content": content}
+
+    if role == "assistant":
+        tcs = m.get("tool_calls") or []
+        if tcs:
+            new_msg["tool_calls"] = _scrub_tool_calls(tcs)
+    if role == "tool":
+        if m.get("tool_call_id"):
+            new_msg["tool_call_id"] = m["tool_call_id"]
+        if m.get("tool_name") or m.get("name"):
+            new_msg["tool_name"] = m.get("tool_name") or m.get("name")
+
+    return new_msg
+
+
+def build_fixture(
+    source_file: str,
+    output_name: str,
+    description: str,
+    first_user_paraphrase: str,
+    model_guess: str,
+    context_length: int,
+    truncate_at: int | None = None,
+) -> Dict[str, Any]:
+    src = SESSION_DIR / source_file
+    raw_msgs: List[Dict[str, Any]] = []
+    with src.open() as fh:
+        for line in fh:
+            try:
+                raw_msgs.append(json.loads(line))
+            except Exception:
+                pass
+
+    # Skip session_meta lines up front so truncate_at counts real messages
+    raw_msgs = [m for m in raw_msgs if m.get("role") != "session_meta"]
+    if truncate_at is not None:
+        raw_msgs = raw_msgs[:truncate_at]
+
+    user_turn_counter = [0]
+    scrubbed: List[Dict[str, Any]] = []
+    for m in raw_msgs:
+        new = _scrub_message(
+            m,
+            first_user_paraphrase=first_user_paraphrase,
+            user_turn_idx=user_turn_counter,
+        )
+        if new is not None:
+            scrubbed.append(new)
+
+    # Drop empty-content assistant messages that have no tool_calls
+    # (artifact of scratchpad-only turns post-scrub)
+    pruned: List[Dict[str, Any]] = []
+    for m in scrubbed:
+        if (
+            m["role"] == "assistant"
+            and not (m.get("content") or "").strip()
+            and not m.get("tool_calls")
+        ):
+            continue
+        pruned.append(m)
+    # Trim trailing orphan tool messages (no matching assistant)
+    while pruned and pruned[-1]["role"] == "tool":
+        pruned.pop()
+    scrubbed = pruned
+
+    # Inject a synthetic public-safe system message so the compressor has
+    # a head to anchor on. The real system prompts embed personality and
+    # platform-specific content we don't want checked in.
+    system_msg = {
+        "role": "system",
+        "content": (
+            "You are a helpful AI coding assistant with access to tools "
+            "(terminal, file editing, search, web, etc.). You operate in a "
+            "conversational loop: the user gives you a task, you call tools "
+            "to accomplish it, and you report back concisely."
+        ),
+    }
+    if scrubbed and scrubbed[0].get("role") == "system":
+        scrubbed[0] = system_msg
+    else:
+        scrubbed.insert(0, system_msg)
+
+    fixture = {
+        "name": output_name,
+        "description": description,
+        "model": model_guess,
+        "context_length": context_length,
+        "source": f"~/.hermes/sessions/{source_file}",
+        "truncated_to": truncate_at,
+        "scrubbed_at": datetime.now().strftime("%Y-%m-%dT%H:%M:%SZ"),
+        "scrubbing_passes": [
+            "redact_sensitive_text (agent.redact)",
+            "username paths replaced with /home/user",
+            "personal handles (all case variants of the maintainer name) replaced with 'user'",
+            "email addresses replaced with contributor@example.com",
+            "git 'Author: Name <addr>' header lines normalised",
+            "reasoning scratchpad blocks stripped from assistant content",
+            "think tag blocks stripped from assistant content",
+            "messaging-platform user mentions replaced with <@user>",
+            "first user message paraphrased to remove personal voice",
+            "subsequent user messages kept verbatim (after above redactions)",
+            "system prompt replaced with generic public-safe placeholder",
+            "orphan empty-assistant messages and trailing tool messages dropped",
+            "tool outputs preserved verbatim (truncation disabled so the compressor sees real load)",
+        ],
+        "messages": scrubbed,
+    }
+    return fixture
+
+
+def main() -> int:
+    FIXTURES_DIR.mkdir(parents=True, exist_ok=True)
+    for spec in SPECS:
+        source_file, output_name, description, paraphrase, model, ctx, truncate = spec
+        fixture = build_fixture(
+            source_file=source_file,
+            output_name=output_name,
+            description=description,
+            first_user_paraphrase=paraphrase,
+            model_guess=model,
+            context_length=ctx,
+            truncate_at=truncate,
+        )
+        out_path = FIXTURES_DIR / f"{output_name}.json"
+        with out_path.open("w") as fh:
+            json.dump(fixture, fh, indent=2, ensure_ascii=False)
+        size_kb = out_path.stat().st_size / 1024
+        print(f"  {output_name}.json  {size_kb:.1f} KB  {len(fixture['messages'])} msgs")
+    return 0
+
+
+if __name__ == "__main__":
+    sys.exit(main())

scripts/install.sh

@@ -29,25 +29,10 @@ BOLD='\033[1m'
 REPO_URL_SSH="git@github.com:NousResearch/hermes-agent.git"
 REPO_URL_HTTPS="https://github.com/NousResearch/hermes-agent.git"
 HERMES_HOME="${HERMES_HOME:-$HOME/.hermes}"
-# INSTALL_DIR is resolved AFTER arg parsing and OS detection so we can pick an
-# FHS-style layout for root installs.  Track whether the user gave us an
-# explicit directory — if so we never override it.
-if [ -n "${HERMES_INSTALL_DIR:-}" ]; then
-    INSTALL_DIR="$HERMES_INSTALL_DIR"
-    INSTALL_DIR_EXPLICIT=true
-else
-    INSTALL_DIR=""
-    INSTALL_DIR_EXPLICIT=false
-fi
+INSTALL_DIR="${HERMES_INSTALL_DIR:-$HERMES_HOME/hermes-agent}"
 PYTHON_VERSION="3.11"
 NODE_VERSION="22"
 
-# FHS-style root install layout (set by resolve_install_layout when applicable):
-#   code at /usr/local/lib/hermes-agent, command at /usr/local/bin/hermes,
-#   data still at /root/.hermes (HERMES_HOME).  Matches Claude Code / Codex CLI
-#   and keeps Docker bind-mounted /root/ volumes lean.
-ROOT_FHS_LAYOUT=false
-
 # Options
 USE_VENV=true
 RUN_SETUP=true
@@ -79,7 +64,6 @@ while [[ $# -gt 0 ]]; do
             ;;
         --dir)
             INSTALL_DIR="$2"
-            INSTALL_DIR_EXPLICIT=true
             shift 2
             ;;
         --hermes-home)
@@ -95,20 +79,9 @@ while [[ $# -gt 0 ]]; do
             echo "  --no-venv      Don't create virtual environment"
             echo "  --skip-setup   Skip interactive setup wizard"
             echo "  --branch NAME  Git branch to install (default: main)"
-            echo "  --dir PATH     Installation directory"
-            echo "                   default (non-root):  ~/.hermes/hermes-agent"
-            echo "                   default (root, Linux): /usr/local/lib/hermes-agent"
+            echo "  --dir PATH     Installation directory (default: ~/.hermes/hermes-agent)"
             echo "  --hermes-home PATH  Data directory (default: ~/.hermes, or \$HERMES_HOME)"
             echo "  -h, --help     Show this help"
-            echo ""
-            echo "Notes:"
-            echo "  When running as root on Linux, Hermes installs the code under"
-            echo "  /usr/local/lib/hermes-agent and links the command into"
-            echo "  /usr/local/bin/hermes (FHS layout — matches Claude Code / Codex CLI)."
-            echo "  Data, config, sessions, and logs still live in \$HERMES_HOME"
-            echo "  (default /root/.hermes).  This keeps Docker bind-mounted volumes"
-            echo "  small and ensures the command is on PATH for all shells."
-            echo "  Existing installs at \$HERMES_HOME/hermes-agent are preserved in-place."
             exit 0
             ;;
         *)
@@ -190,60 +163,9 @@ is_termux() {
     [ -n "${TERMUX_VERSION:-}" ] || [[ "${PREFIX:-}" == *"com.termux/files/usr"* ]]
 }
 
-# Decide where the repo checkout + venv live, and where the `hermes` command
-# symlink goes.  Called after detect_os so $OS/$DISTRO are known.
-#
-# Defaults:
-#   - Non-root, any OS:       INSTALL_DIR = $HERMES_HOME/hermes-agent
-#                             command link in $HOME/.local/bin
-#   - Termux (any uid):       INSTALL_DIR = $HERMES_HOME/hermes-agent
-#                             command link in $PREFIX/bin (already on PATH)
-#   - Root on Linux (new):    INSTALL_DIR = /usr/local/lib/hermes-agent
-#                             command link in /usr/local/bin
-#                             (unless a legacy install already exists at
-#                              $HERMES_HOME/hermes-agent — then preserve it)
-#
-# Always no-op when the user set --dir or $HERMES_INSTALL_DIR.
-resolve_install_layout() {
-    if [ "$INSTALL_DIR_EXPLICIT" = true ]; then
-        log_info "Install directory: $INSTALL_DIR (explicit)"
-        return 0
-    fi
-
-    # Termux: package manager manages /data/data/..., keep code in HERMES_HOME.
-    if is_termux; then
-        INSTALL_DIR="$HERMES_HOME/hermes-agent"
-        return 0
-    fi
-
-    # Root on Linux: prefer FHS layout unless a legacy install already exists.
-    # macOS root installs keep the legacy layout because /usr/local/ on macOS
-    # is Homebrew territory and we don't want to fight that.
-    if [ "$OS" = "linux" ] && [ "$(id -u)" -eq 0 ]; then
-        if [ -d "$HERMES_HOME/hermes-agent/.git" ]; then
-            INSTALL_DIR="$HERMES_HOME/hermes-agent"
-            log_info "Existing install detected at $INSTALL_DIR — keeping legacy layout"
-            log_info "  (new root installs use /usr/local/lib/hermes-agent)"
-            return 0
-        fi
-        INSTALL_DIR="/usr/local/lib/hermes-agent"
-        ROOT_FHS_LAYOUT=true
-        log_info "Root install on Linux — using FHS layout"
-        log_info "  Code:    $INSTALL_DIR"
-        log_info "  Command: /usr/local/bin/hermes"
-        log_info "  Data:    $HERMES_HOME (unchanged)"
-        return 0
-    fi
-
-    # Default: non-root, non-Termux → legacy user-scoped layout.
-    INSTALL_DIR="$HERMES_HOME/hermes-agent"
-}
-
 get_command_link_dir() {
     if is_termux && [ -n "${PREFIX:-}" ]; then
         echo "$PREFIX/bin"
-    elif [ "$ROOT_FHS_LAYOUT" = true ]; then
-        echo "/usr/local/bin"
     else
         echo "$HOME/.local/bin"
     fi
@@ -252,8 +174,6 @@ get_command_link_dir() {
 get_command_link_display_dir() {
     if is_termux && [ -n "${PREFIX:-}" ]; then
         echo '$PREFIX/bin'
-    elif [ "$ROOT_FHS_LAYOUT" = true ]; then
-        echo '/usr/local/bin'
     else
         echo '~/.local/bin'
     fi
@@ -1055,14 +975,6 @@ setup_path() {
         return 0
     fi
 
-    # FHS layout: /usr/local/bin is on PATH for every standard shell, nothing to inject.
-    if [ "$ROOT_FHS_LAYOUT" = true ]; then
-        export PATH="$command_link_dir:$PATH"
-        log_info "/usr/local/bin is already on PATH for all shells"
-        log_success "hermes command ready"
-        return 0
-    fi
-
     # Check if ~/.local/bin is on PATH; if not, add it to shell config.
     # Detect the user's actual login shell (not the shell running this script,
     # which is always bash when piped from curl).
@@ -1427,12 +1339,12 @@ print_success() {
     echo ""
 
     # Show file locations
-    echo -e "${CYAN}${BOLD}📁 Your files:${NC}"
+    echo -e "${CYAN}${BOLD}📁 Your files (all in ~/.hermes/):${NC}"
     echo ""
-    echo -e "   ${YELLOW}Config:${NC}    $HERMES_HOME/config.yaml"
-    echo -e "   ${YELLOW}API Keys:${NC}  $HERMES_HOME/.env"
-    echo -e "   ${YELLOW}Data:${NC}      $HERMES_HOME/cron/, sessions/, logs/"
-    echo -e "   ${YELLOW}Code:${NC}      $INSTALL_DIR"
+    echo -e "   ${YELLOW}Config:${NC}    ~/.hermes/config.yaml"
+    echo -e "   ${YELLOW}API Keys:${NC}  ~/.hermes/.env"
+    echo -e "   ${YELLOW}Data:${NC}      ~/.hermes/cron/, sessions/, logs/"
+    echo -e "   ${YELLOW}Code:${NC}      ~/.hermes/hermes-agent/"
     echo ""
 
     echo -e "${CYAN}─────────────────────────────────────────────────────────${NC}"
@@ -1452,9 +1364,6 @@ print_success() {
     if [ "$DISTRO" = "termux" ]; then
         echo -e "${YELLOW}⚡ 'hermes' was linked into $(get_command_link_display_dir), which is already on PATH in Termux.${NC}"
         echo ""
-    elif [ "$ROOT_FHS_LAYOUT" = true ]; then
-        echo -e "${YELLOW}⚡ 'hermes' was linked into /usr/local/bin and is ready to use — no shell reload needed.${NC}"
-        echo ""
     else
         echo -e "${YELLOW}⚡ Reload your shell to use 'hermes' command:${NC}"
         echo ""
@@ -1506,7 +1415,6 @@ main() {
     print_banner
 
     detect_os
-    resolve_install_layout
     install_uv
     check_python
     check_git

scripts/release.py

@@ -43,16 +43,11 @@ AUTHOR_MAP = {
     "teknium1@gmail.com": "teknium1",
     "teknium@nousresearch.com": "teknium1",
     "127238744+teknium1@users.noreply.github.com": "teknium1",
-    "focusflow.app.help@gmail.com": "yes999zc",
     "343873859@qq.com": "DrStrangerUJN",
     "uzmpsk.dilekakbas@gmail.com": "dlkakbs",
     "jefferson@heimdallstrategy.com": "Mind-Dragon",
     "130918800+devorun@users.noreply.github.com": "devorun",
     "maks.mir@yahoo.com": "say8hi",
-    "web3blind@users.noreply.github.com": "web3blind",
-    "julia@alexland.us": "alexg0bot",
-    "1060770+benjaminsehl@users.noreply.github.com": "benjaminsehl",
-    "nerijusn76@gmail.com": "Nerijusas",
     # contributors (from noreply pattern)
     "david.vv@icloud.com": "davidvv",
     "wangqiang@wangqiangdeMac-mini.local": "xiaoqiang243",
@@ -64,21 +59,14 @@ AUTHOR_MAP = {
     "keifergu@tencent.com": "keifergu",
     "kshitijk4poor@users.noreply.github.com": "kshitijk4poor",
     "abner.the.foreman@agentmail.to": "Abnertheforeman",
-    "thomasgeorgevii09@gmail.com": "tochukwuada",
     "harryykyle1@gmail.com": "hharry11",
     "kshitijk4poor@gmail.com": "kshitijk4poor",
     "keira.voss94@gmail.com": "keiravoss94",
     "16443023+stablegenius49@users.noreply.github.com": "stablegenius49",
-    "fqsy1416@gmail.com": "EKKOLearnAI",
-    "simbamax99@gmail.com": "simbam99",
-    "iris@growthpillars.co": "irispillars",
     "185121704+stablegenius49@users.noreply.github.com": "stablegenius49",
     "101283333+batuhankocyigit@users.noreply.github.com": "batuhankocyigit",
     "255305877+ismell0992-afk@users.noreply.github.com": "ismell0992-afk",
-    "cyprian@ironin.pl": "iRonin",
     "valdi.jorge@gmail.com": "jvcl",
-    "q19dcp@gmail.com": "aj-nt",
-    "ebukau84@gmail.com": "UgwujaGeorge",
     "francip@gmail.com": "francip",
     "omni@comelse.com": "omnissiah-comelse",
     "oussama.redcode@gmail.com": "mavrickdeveloper",
@@ -96,8 +84,6 @@ AUTHOR_MAP = {
     "104278804+Sertug17@users.noreply.github.com": "Sertug17",
     "112503481+caentzminger@users.noreply.github.com": "caentzminger",
     "258577966+voidborne-d@users.noreply.github.com": "voidborne-d",
-    "liusway405@gmail.com": "voidborne-d",
-    "xydarcher@uestc.edu.cn": "Readon",
     "sir_even@icloud.com": "sirEven",
     "36056348+sirEven@users.noreply.github.com": "sirEven",
     "70424851+insecurejezza@users.noreply.github.com": "insecurejezza",
@@ -120,7 +106,6 @@ AUTHOR_MAP = {
     "30841158+n-WN@users.noreply.github.com": "n-WN",
     "tsuijinglei@gmail.com": "hiddenpuppy",
     "jerome@clawwork.ai": "HiddenPuppy",
-    "jerome.benoit@sap.com": "jerome-benoit",
     "wysie@users.noreply.github.com": "Wysie",
     "leoyuan0099@gmail.com": "keyuyuan",
     "bxzt2006@163.com": "Only-Code-A",
@@ -181,10 +166,6 @@ AUTHOR_MAP = {
     "jaisehgal11299@gmail.com": "jaisup",
     "percydikec@gmail.com": "PercyDikec",
     "noonou7@gmail.com": "HenkDz",
-    # Azure Foundry salvage (PRs #9029, #4599, #10086, #8766)
-    "tech@smartlogics.net": "TechPrototyper",
-    "637186+HangGlidersRule@users.noreply.github.com": "HangGlidersRule",
-    "pein892@gmail.com": "pein892",
     "dean.kerr@gmail.com": "deankerr",
     "socrates1024@gmail.com": "socrates1024",
     "seanalt555@gmail.com": "Salt-555",
@@ -219,9 +200,6 @@ AUTHOR_MAP = {
     "1434494126@qq.com": "5park1e",
     "158153005+5park1e@users.noreply.github.com": "5park1e",
     "innocarpe@gmail.com": "innocarpe",
-    "noreply@ked.com": "qike-ms",
-    "andrekurait@gmail.com": "AndreKurait",
-    "bsgdigital@users.noreply.github.com": "bsgdigital",
     "numman.ali@gmail.com": "nummanali",
     "rohithsaimidigudla@gmail.com": "whitehatjr1001",
     "0xNyk@users.noreply.github.com": "0xNyk",
@@ -419,7 +397,6 @@ AUTHOR_MAP = {
     "105142614+VTRiot@users.noreply.github.com": "VTRiot",
     "vivien000812@gmail.com": "iamagenius00",
     "89228157+Feranmi10@users.noreply.github.com": "Feranmi10",
-    "oluwadareferanmi11@gmail.com": "Feranmi10",
     "simon@gtcl.us": "simon-gtcl",
     "suzukaze.haduki@gmail.com": "houko",
     "cliff@cigii.com": "cgarwood82",
@@ -513,9 +490,6 @@ AUTHOR_MAP = {
     "zhangxicen@example.com": "zhangxicen",
     "codex@openai.invalid": "teknium1",
     "screenmachine@gmail.com": "teknium1",
-    "chenzeshi@live.com": "chen1749144759",
-    "mor.aleksandr@yahoo.com": "MorAlekss",
-    "ash@users.noreply.github.com": "ash",
 }
 
 

skills/autonomous-ai-agents/hermes-agent/SKILL.md

@@ -281,6 +281,7 @@ Type these during an interactive chat session.
 ### Utility
 ```
 /branch (/fork)      Branch the current session
+/btw                 Ephemeral side question (doesn't interrupt main task)
 /fast                Toggle priority/fast processing
 /browser             Open CDP browser connection
 /history             Show conversation history (CLI)

skills/devops/kanban-orchestrator/SKILL.md

@@ -1,152 +0,0 @@
----
-name: kanban-orchestrator
-description: Decomposition playbook + specialist-roster conventions + anti-temptation rules for an orchestrator profile routing work through Kanban. The "don't do the work yourself" rule and the basic lifecycle are auto-injected into every kanban worker's system prompt; this skill is the deeper playbook when you're specifically playing the orchestrator role.
-version: 2.0.0
-metadata:
-  hermes:
-    tags: [kanban, multi-agent, orchestration, routing]
-    related_skills: [kanban-worker]
----
-
-# Kanban Orchestrator — Decomposition Playbook
-
-> The **core worker lifecycle** (including the `kanban_create` fan-out pattern and the "decompose, don't execute" rule) is auto-injected into every kanban process via the `KANBAN_GUIDANCE` system-prompt block. This skill is the deeper playbook when you're an orchestrator profile whose whole job is routing.
-
-## When to use the board (vs. just doing the work)
-
-Create Kanban tasks when any of these are true:
-
-1. **Multiple specialists are needed.** Research + analysis + writing is three profiles.
-2. **The work should survive a crash or restart.** Long-running, recurring, or important.
-3. **The user might want to interject.** Human-in-the-loop at any step.
-4. **Multiple subtasks can run in parallel.** Fan-out for speed.
-5. **Review / iteration is expected.** A reviewer profile loops on drafter output.
-6. **The audit trail matters.** Board rows persist in SQLite forever.
-
-If *none* of those apply — it's a small one-shot reasoning task — use `delegate_task` instead or answer the user directly.
-
-## The anti-temptation rules
-
-Your job description says "route, don't execute." The rules that enforce that:
-
-- **Do not execute the work yourself.** Your restricted toolset usually doesn't even include terminal/file/code/web for implementation. If you find yourself "just fixing this quickly" — stop and create a task for the right specialist.
-- **For any concrete task, create a Kanban task and assign it.** Every single time.
-- **If no specialist fits, ask the user which profile to create.** Do not default to doing it yourself under "close enough."
-- **Decompose, route, and summarize — that's the whole job.**
-
-## The standard specialist roster (convention)
-
-Unless the user's setup has customized profiles, assume these exist. Adjust to whatever the user actually has — ask if you're unsure.
-
-| Profile | Does | Typical workspace |
-|---|---|---|
-| `researcher` | Reads sources, gathers facts, writes findings | `scratch` |
-| `analyst` | Synthesizes, ranks, de-dupes. Consumes multiple `researcher` outputs | `scratch` |
-| `writer` | Drafts prose in the user's voice | `scratch` or `dir:` into their Obsidian vault |
-| `reviewer` | Reads output, leaves findings, gates approval | `scratch` |
-| `backend-eng` | Writes server-side code | `worktree` |
-| `frontend-eng` | Writes client-side code | `worktree` |
-| `ops` | Runs scripts, manages services, handles deployments | `dir:` into ops scripts repo |
-| `pm` | Writes specs, acceptance criteria | `scratch` |
-
-## Decomposition playbook
-
-### Step 1 — Understand the goal
-
-Ask clarifying questions if the goal is ambiguous. Cheap to ask; expensive to spawn the wrong fleet.
-
-### Step 2 — Sketch the task graph
-
-Before creating anything, draft the graph out loud (in your response to the user). Example for "Analyze whether we should migrate to Postgres":
-
-```
-T1  researcher        research: Postgres cost vs current
-T2  researcher        research: Postgres performance vs current
-T3  analyst           synthesize migration recommendation       parents: T1, T2
-T4  writer            draft decision memo                       parents: T3
-```
-
-Show this to the user. Let them correct it before you create anything.
-
-### Step 3 — Create tasks and link
-
-```python
-t1 = kanban_create(
-    title="research: Postgres cost vs current",
-    assignee="researcher",
-    body="Compare estimated infrastructure costs, migration costs, and ongoing ops costs over a 3-year window. Sources: AWS/GCP pricing, team time estimates, current Postgres bills from peers.",
-    tenant=os.environ.get("HERMES_TENANT"),
-)["task_id"]
-
-t2 = kanban_create(
-    title="research: Postgres performance vs current",
-    assignee="researcher",
-    body="Compare query latency, throughput, and scaling characteristics at our expected data volume (~500GB, 10k QPS peak). Sources: benchmark papers, public case studies, pgbench results if easy.",
-)["task_id"]
-
-t3 = kanban_create(
-    title="synthesize migration recommendation",
-    assignee="analyst",
-    body="Read the findings from T1 (cost) and T2 (performance). Produce a 1-page recommendation with explicit trade-offs and a go/no-go call.",
-    parents=[t1, t2],
-)["task_id"]
-
-t4 = kanban_create(
-    title="draft decision memo",
-    assignee="writer",
-    body="Turn the analyst's recommendation into a 2-page memo for the CTO. Match the tone of previous decision memos in the team's knowledge base.",
-    parents=[t3],
-)["task_id"]
-```
-
-`parents=[...]` gates promotion — children stay in `todo` until every parent reaches `done`, then auto-promote to `ready`. No manual coordination needed; the dispatcher and dependency engine handle it.
-
-### Step 4 — Complete your own task
-
-If you were spawned as a task yourself (e.g. `planner` profile was assigned `T0: "investigate Postgres migration"`), mark it done with a summary of what you created:
-
-```python
-kanban_complete(
-    summary="decomposed into T1-T4: 2 researchers parallel, 1 analyst on their outputs, 1 writer on the recommendation",
-    metadata={
-        "task_graph": {
-            "T1": {"assignee": "researcher", "parents": []},
-            "T2": {"assignee": "researcher", "parents": []},
-            "T3": {"assignee": "analyst", "parents": ["T1", "T2"]},
-            "T4": {"assignee": "writer", "parents": ["T3"]},
-        },
-    },
-)
-```
-
-### Step 5 — Report back to the user
-
-Tell them what you created in plain prose:
-
-> I've queued 4 tasks:
-> - **T1** (researcher): cost comparison
-> - **T2** (researcher): performance comparison, in parallel with T1
-> - **T3** (analyst): synthesizes T1 + T2 into a recommendation
-> - **T4** (writer): turns T3 into a CTO memo
->
-> The dispatcher will pick up T1 and T2 now. T3 starts when both finish. You'll get a gateway ping when T4 completes. Use the dashboard or `hermes kanban tail <id>` to follow along.
-
-## Common patterns
-
-**Fan-out + fan-in (research → synthesize):** N `researcher` tasks with no parents, one `analyst` task with all of them as parents.
-
-**Pipeline with gates:** `pm → backend-eng → reviewer`. Each stage's `parents=[previous_task]`. Reviewer blocks or completes; if reviewer blocks, the operator unblocks with feedback and respawns.
-
-**Same-profile queue:** 50 tasks, all assigned to `translator`, no dependencies between them. Dispatcher serializes — translator processes them in priority order, accumulating experience in their own memory.
-
-**Human-in-the-loop:** Any task can `kanban_block()` to wait for input. Dispatcher respawns after `/unblock`. The comment thread carries the full context.
-
-## Pitfalls
-
-**Reassignment vs. new task.** If a reviewer blocks with "needs changes," create a NEW task linked from the reviewer's task — don't re-run the same task with a stern look. The new task is assigned to the original implementer profile.
-
-**Argument order for links.** `kanban_link(parent_id=..., child_id=...)` — parent first. Mixing them up demotes the wrong task to `todo`.
-
-**Don't pre-create the whole graph if the shape depends on intermediate findings.** If T3's structure depends on what T1 and T2 find, let T3 exist as a "synthesize findings" task whose own first step is to read parent handoffs and plan the rest. Orchestrators can spawn orchestrators.
-
-**Tenant inheritance.** If `HERMES_TENANT` is set in your env, pass `tenant=os.environ.get("HERMES_TENANT")` on every `kanban_create` call so child tasks stay in the same namespace.

skills/devops/kanban-worker/SKILL.md

@@ -1,134 +0,0 @@
----
-name: kanban-worker
-description: Pitfalls, examples, and edge cases for Hermes Kanban workers. The lifecycle itself is auto-injected into every worker's system prompt as KANBAN_GUIDANCE (from agent/prompt_builder.py); this skill is what you load when you want deeper detail on specific scenarios.
-version: 2.0.0
-metadata:
-  hermes:
-    tags: [kanban, multi-agent, collaboration, workflow, pitfalls]
-    related_skills: [kanban-orchestrator]
----
-
-# Kanban Worker — Pitfalls and Examples
-
-> You're seeing this skill because the Hermes Kanban dispatcher spawned you as a worker with `--skills kanban-worker` — it's loaded automatically for every dispatched worker. The **lifecycle** (6 steps: orient → work → heartbeat → block/complete) also lives in the `KANBAN_GUIDANCE` block that's auto-injected into your system prompt. This skill is the deeper detail: good handoff shapes, retry diagnostics, edge cases.
-
-## Workspace handling
-
-Your workspace kind determines how you should behave inside `$HERMES_KANBAN_WORKSPACE`:
-
-| Kind | What it is | How to work |
-|---|---|---|
-| `scratch` | Fresh tmp dir, yours alone | Read/write freely; it gets GC'd when the task is archived. |
-| `dir:<path>` | Shared persistent directory | Other runs will read what you write. Treat it like long-lived state. Path is guaranteed absolute (the kernel rejects relative paths). |
-| `worktree` | Git worktree at the resolved path | If `.git` doesn't exist, run `git worktree add <path> <branch>` from the main repo first, then cd and work normally. Commit work here. |
-
-## Tenant isolation
-
-If `$HERMES_TENANT` is set, the task belongs to a tenant namespace. When reading or writing persistent memory, prefix memory entries with the tenant so context doesn't leak across tenants:
-
-- Good: `business-a: Acme is our biggest customer`
-- Bad (leaks): `Acme is our biggest customer`
-
-## Good summary + metadata shapes
-
-The `kanban_complete(summary=..., metadata=...)` handoff is how downstream workers read what you did. Patterns that work:
-
-**Coding task:**
-```python
-kanban_complete(
-    summary="shipped rate limiter — token bucket, keys on user_id with IP fallback, 14 tests pass",
-    metadata={
-        "changed_files": ["rate_limiter.py", "tests/test_rate_limiter.py"],
-        "tests_run": 14,
-        "tests_passed": 14,
-        "decisions": ["user_id primary, IP fallback for unauthenticated requests"],
-    },
-)
-```
-
-**Research task:**
-```python
-kanban_complete(
-    summary="3 competing libraries reviewed; vLLM wins on throughput, SGLang on latency, Tensorrt-LLM on memory efficiency",
-    metadata={
-        "sources_read": 12,
-        "recommendation": "vLLM",
-        "benchmarks": {"vllm": 1.0, "sglang": 0.87, "trtllm": 0.72},
-    },
-)
-```
-
-**Review task:**
-```python
-kanban_complete(
-    summary="reviewed PR #123; 2 blocking issues found (SQL injection in /search, missing CSRF on /settings)",
-    metadata={
-        "pr_number": 123,
-        "findings": [
-            {"severity": "critical", "file": "api/search.py", "line": 42, "issue": "raw SQL concat"},
-            {"severity": "high", "file": "api/settings.py", "issue": "missing CSRF middleware"},
-        ],
-        "approved": False,
-    },
-)
-```
-
-Shape `metadata` so downstream parsers (reviewers, aggregators, schedulers) can use it without re-reading your prose.
-
-## Block reasons that get answered fast
-
-Bad: `"stuck"` — the human has no context.
-
-Good: one sentence naming the specific decision you need. Leave longer context as a comment instead.
-
-```python
-kanban_comment(
-    task_id=os.environ["HERMES_KANBAN_TASK"],
-    body="Full context: I have user IPs from Cloudflare headers but some users are behind NATs with thousands of peers. Keying on IP alone causes false positives.",
-)
-kanban_block(reason="Rate limit key choice: IP (simple, NAT-unsafe) or user_id (requires auth, skips anonymous endpoints)?")
-```
-
-The block message is what appears in the dashboard / gateway notifier. The comment is the deeper context a human reads when they open the task.
-
-## Heartbeats worth sending
-
-Good heartbeats name progress: `"epoch 12/50, loss 0.31"`, `"scanned 1.2M/2.4M rows"`, `"uploaded 47/120 videos"`.
-
-Bad heartbeats: `"still working"`, empty notes, sub-second intervals. Every few minutes max; skip entirely for tasks under ~2 minutes.
-
-## Retry scenarios
-
-If you open the task and `kanban_show` returns `runs: [...]` with one or more closed runs, you're a retry. The prior runs' `outcome` / `summary` / `error` tell you what didn't work. Don't repeat that path. Typical retry diagnostics:
-
-- `outcome: "timed_out"` — the previous attempt hit `max_runtime_seconds`. You may need to chunk the work or shorten it.
-- `outcome: "crashed"` — OOM or segfault. Reduce memory footprint.
-- `outcome: "spawn_failed"` + `error: "..."` — usually a profile config issue (missing credential, bad PATH). Ask the human via `kanban_block` instead of retrying blindly.
-- `outcome: "reclaimed"` + `summary: "task archived..."` — operator archived the task out from under the previous run; you probably shouldn't be running at all, check status carefully.
-- `outcome: "blocked"` — a previous attempt blocked; the unblock comment should be in the thread by now.
-
-## Do NOT
-
-- Call `delegate_task` as a substitute for `kanban_create`. `delegate_task` is for short reasoning subtasks inside YOUR run; `kanban_create` is for cross-agent handoffs that outlive one API loop.
-- Modify files outside `$HERMES_KANBAN_WORKSPACE` unless the task body says to.
-- Create follow-up tasks assigned to yourself — assign to the right specialist.
-- Complete a task you didn't actually finish. Block it instead.
-
-## Pitfalls
-
-**Task state can change between dispatch and your startup.** Between when the dispatcher claimed and when your process actually booted, the task may have been blocked, reassigned, or archived. Always `kanban_show` first. If it reports `blocked` or `archived`, stop — you shouldn't be running.
-
-**Workspace may have stale artifacts.** Especially `dir:` and `worktree` workspaces can have files from previous runs. Read the comment thread — it usually explains why you're running again and what state the workspace is in.
-
-**Don't rely on the CLI when the guidance is available.** The `kanban_*` tools work across all terminal backends (Docker, Modal, SSH). `hermes kanban <verb>` from your terminal tool will fail in containerized backends because the CLI isn't installed there. When in doubt, use the tool.
-
-## CLI fallback (for scripting)
-
-Every tool has a CLI equivalent for human operators and scripts:
-- `kanban_show` ↔ `hermes kanban show <id> --json`
-- `kanban_complete` ↔ `hermes kanban complete <id> --summary "..." --metadata '{...}'`
-- `kanban_block` ↔ `hermes kanban block <id> "reason"`
-- `kanban_create` ↔ `hermes kanban create "title" --assignee <profile> [--parent <id>]`
-- etc.
-
-Use the tools from inside an agent; the CLI exists for the human at the terminal.

skills/mlops/inference/obliteratus/SKILL.md

@@ -17,13 +17,6 @@ Remove refusal behaviors (guardrails) from open-weight LLMs without retraining o
 
 **License warning:** OBLITERATUS is AGPL-3.0. NEVER import it as a Python library. Always invoke via CLI (`obliteratus` command) or subprocess. This keeps Hermes Agent's MIT license clean.
 
-## Video Guide
-
-Walkthrough of OBLITERATUS used by a Hermes agent to abliterate Gemma:
-https://www.youtube.com/watch?v=8fG9BrNTeHs ("OBLITERATUS: An AI Agent Removed Gemma 4's Safety Guardrails")
-
-Useful when the user wants a visual overview of the end-to-end workflow before running it themselves.
-
 ## When to Use This Skill
 
 Trigger when the user:

skills/mlops/models/segment-anything/SKILL.md

@@ -134,7 +134,6 @@ masks = processor.image_processor.post_process_masks(
 
 ### Model architecture
 
-<!-- ascii-guard-ignore -->
 ```
 SAM Architecture:
 ┌─────────────────┐     ┌─────────────────┐     ┌─────────────────┐
@@ -145,7 +144,6 @@ SAM Architecture:
    Image Embeddings      Prompt Embeddings         Masks + IoU
    (computed once)       (per prompt)             predictions
 ```
-<!-- ascii-guard-ignore-end -->
 
 ### Model variants
 

skills/productivity/google-workspace/scripts/_hermes_home.py

@@ -1,42 +0,0 @@
-"""Resolve HERMES_HOME for standalone skill scripts.
-
-Skill scripts may run outside the Hermes process (e.g. system Python,
-nix env, CI) where ``hermes_constants`` is not importable.  This module
-provides the same ``get_hermes_home()`` and ``display_hermes_home()``
-contracts as ``hermes_constants`` without requiring it on ``sys.path``.
-
-When ``hermes_constants`` IS available it is used directly so that any
-future enhancements (profile resolution, Docker detection, etc.) are
-picked up automatically.  The fallback path replicates the core logic
-from ``hermes_constants.py`` using only the stdlib.
-
-All scripts under ``google-workspace/scripts/`` should import from here
-instead of duplicating the ``HERMES_HOME = Path(os.getenv(...))`` pattern.
-"""
-
-from __future__ import annotations
-
-import os
-from pathlib import Path
-
-try:
-    from hermes_constants import display_hermes_home as display_hermes_home
-    from hermes_constants import get_hermes_home as get_hermes_home
-except (ModuleNotFoundError, ImportError):
-
-    def get_hermes_home() -> Path:
-        """Return the Hermes home directory (default: ~/.hermes).
-
-        Mirrors ``hermes_constants.get_hermes_home()``."""
-        val = os.environ.get("HERMES_HOME", "").strip()
-        return Path(val) if val else Path.home() / ".hermes"
-
-    def display_hermes_home() -> str:
-        """Return a user-friendly ``~/``-shortened display string.
-
-        Mirrors ``hermes_constants.display_hermes_home()``."""
-        home = get_hermes_home()
-        try:
-            return "~/" + str(home.relative_to(Path.home()))
-        except ValueError:
-            return str(home)

skills/productivity/google-workspace/scripts/google_api.py

@@ -31,14 +31,7 @@ from datetime import datetime, timedelta, timezone
 from email.mime.text import MIMEText
 from pathlib import Path
 
-# Ensure sibling modules (_hermes_home) are importable when run standalone.
-_SCRIPTS_DIR = str(Path(__file__).resolve().parent)
-if _SCRIPTS_DIR not in sys.path:
-    sys.path.insert(0, _SCRIPTS_DIR)
-
-from _hermes_home import get_hermes_home
-
-HERMES_HOME = get_hermes_home()
+HERMES_HOME = Path(os.getenv("HERMES_HOME", Path.home() / ".hermes"))
 TOKEN_PATH = HERMES_HOME / "google_token.json"
 CLIENT_SECRET_PATH = HERMES_HOME / "google_client_secret.json"
 

skills/productivity/google-workspace/scripts/gws_bridge.py

@@ -10,12 +10,9 @@ import sys
 from datetime import datetime, timezone
 from pathlib import Path
 
-# Ensure sibling modules (_hermes_home) are importable when run standalone.
-_SCRIPTS_DIR = str(Path(__file__).resolve().parent)
-if _SCRIPTS_DIR not in sys.path:
-    sys.path.insert(0, _SCRIPTS_DIR)
 
-from _hermes_home import get_hermes_home
+def get_hermes_home() -> Path:
+    return Path(os.environ.get("HERMES_HOME", Path.home() / ".hermes"))
 
 
 def get_token_path() -> Path:

skills/productivity/google-workspace/scripts/setup.py

@@ -21,8 +21,6 @@ Agent workflow:
   6. Run --check to verify. Done.
 """
 
-from __future__ import annotations  # allow PEP 604 `X | None` on Python 3.9+
-
 import argparse
 import json
 import os
@@ -30,12 +28,13 @@ import subprocess
 import sys
 from pathlib import Path
 
-# Ensure sibling modules (_hermes_home) are importable when run standalone.
-_SCRIPTS_DIR = str(Path(__file__).resolve().parent)
-if _SCRIPTS_DIR not in sys.path:
-    sys.path.insert(0, _SCRIPTS_DIR)
-
-from _hermes_home import display_hermes_home, get_hermes_home
+try:
+    from hermes_constants import display_hermes_home, get_hermes_home
+except ModuleNotFoundError:
+    HERMES_AGENT_ROOT = Path(__file__).resolve().parents[4]
+    if HERMES_AGENT_ROOT.exists():
+        sys.path.insert(0, str(HERMES_AGENT_ROOT))
+    from hermes_constants import display_hermes_home, get_hermes_home
 
 HERMES_HOME = get_hermes_home()
 TOKEN_PATH = HERMES_HOME / "google_token.json"
@@ -112,11 +111,7 @@ def install_deps():
         return True
     except subprocess.CalledProcessError as e:
         print(f"ERROR: Failed to install dependencies: {e}")
-        print(
-            "On environments without pip (e.g. Nix), install the optional extra instead:"
-        )
-        print("  pip install 'hermes-agent[google]'")
-        print(f"Or manually: {sys.executable} -m pip install {' '.join(REQUIRED_PACKAGES)}")
+        print(f"Try manually: {sys.executable} -m pip install {' '.join(REQUIRED_PACKAGES)}")
         return False