253bfc0e3d7ca96c11d59ae0eaef996b5edcc14c
13
Commits
| Author | SHA1 | Message | Date | |
|---|---|---|---|---|
 Teknium
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fdc90346ea |
chore(skills): move red-team skills (godmode, obliteratus) to optional-skills — Anthropic classifier (#43221)
* chore(skills): remove red-team skills (godmode, obliteratus) from bundled catalog Anthropic's output classifier on claude-fable-5 (and likely other Claude models served through it) intermittently returns empty content for sessions whose system prompt advertises these skills. The bundled skills-catalog block is injected into every session's system prompt, so the descriptions - red-teaming/godmode 'Jailbreak LLMs: Parseltongue, GODMODE, ULTRAPLINIAN' - mlops/inference/obliteratus 'OBLITERATUS: abliterate LLM refusals (diff-in-means)' trip the classifier on EVERY session regardless of which skill is actually loaded, killing unrelated legitimate work (PR review, codebase audits, etc.). Measured impact (controlled, interleaved A/B, claude-fable-5 via OpenRouter, prompts differing only by the ~204 chars of these catalog lines, N=20 each): catalog lines present -> 19/20 (95%) blocked catalog lines absent -> 5/20 (25%) blocked Removing them ~quartered the block rate. Rewording the descriptions was not enough; the skills must leave the bundled catalog. - Delete skills/red-teaming/godmode and skills/mlops/inference/obliteratus - Drop their generated doc pages + catalog/sidebar entries (EN + zh-Hans) - Drop the godmode hand-written-page exception in generate-skill-docs.py * chore(skills): relocate godmode + obliteratus to optional-skills Rather than deleting outright, move both into optional-skills/ so they remain installable via `hermes skills install` while leaving the always-injected bundled catalog (which is what tripped Anthropic's classifier). - optional-skills/security/godmode (was skills/red-teaming/godmode) - optional-skills/mlops/obliteratus (was skills/mlops/inference/obliteratus) - regenerate optional-skills catalog + sidebar entries |
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Teknium
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38d3c49aaf |
refactor(skills): clean up bundled skill set + add environments: relevance gate (#39028)
* refactor(skills): clean up bundled skill set + add environments: relevance gate Bundled skills cleanup pass plus a new offer-time relevance gate. Removals (redundant / dead): - spotify (covered by the spotify plugin's 7 native tools) - linear (covered by `hermes mcp install linear`) - kanban-codex-lane, debugging-hermes-tui-commands - empty category markers: diagramming, gifs, inference-sh, mlops/training, mlops/vector-databases - domain (stale orphan dup of optional/research/domain-intel) Bundled -> optional: - baoyu-article-illustrator, baoyu-comic, creative-ideation, pixel-art - dspy, subagent-driven-development - minecraft-modpack-server, pokemon-player - hermes-s6-container-supervision (-> optional/devops) Consolidation: - webhook-subscriptions + native-mcp folded into the hermes-agent skill as references/webhooks.md + references/native-mcp.md with SKILL.md pointers - writing-plans merged into plan (v2.0.0); related_skills + prose refs updated New: environments: frontmatter gate (agent/skill_utils.skill_matches_environment) - Offer-time relevance filter (kanban / docker / s6), parallel to platforms:. - Wired into the 3 OFFER surfaces only (prompt_builder skills index, skills_tool.list_skills, skill_commands slash discovery). - Explicit loads (skill_view, --skills preload) intentionally BYPASS it, so load-bearing force-loads like the kanban dispatcher's `--skills kanban-worker` always resolve. Verified via E2E. - kanban-orchestrator/kanban-worker tagged environments: [kanban]; hermes-s6-container-supervision tagged environments: [s6] + platforms: [linux]. Validation: 8/8 E2E gating assertions (incl force-load invariant); 442 targeted tests green (agent, skills_tool, skill_commands, kanban worker). * docs: regenerate skill catalogs + pages for the bundled cleanup Regenerated per-skill doc pages, catalogs, and sidebar to match the skill moves/removals in the parent commit. Moved skills' pages relocate bundled -> optional (history preserved); removed skills' pages deleted; edited skills' pages refreshed (hermes-agent now embeds the webhook + native-mcp reference pointers). zh-Hans i18n mirror: stale bundled pages and catalog rows for moved/removed skills pruned (new optional translations land via the translation pipeline). * test: drop regression test for removed kanban-codex-lane skill The kanban-codex-lane skill was removed in the bundled-skills cleanup; its dedicated regression test read the now-deleted SKILL.md and failed with FileNotFoundError on CI shard 6. |
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Siddharth Balyan
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5af672c753 |
chore: remove Atropos RL environments and tinker-atropos integration (#26106)
* chore: remove Atropos RL environments, tools, tests, skill, and tinker-atropos submodule Delete: - environments/ (43 files — base env, agent loop, tool call parsers, benchmarks) - rl_cli.py (standalone RL training CLI) - tools/rl_training_tool.py (all 10 rl_* tools) - tests: test_rl_training_tool, test_tool_call_parsers, test_managed_server_tool_support, test_agent_loop, test_agent_loop_vllm, test_agent_loop_tool_calling, test_terminalbench2_env_security - optional-skills/mlops/hermes-atropos-environments/ - tinker-atropos git submodule + .gitmodules * chore: remove RL/Atropos references from Python source - toolsets.py: remove rl toolset block + update comment - model_tools.py: remove rl_tools group + update async bridging comment - hermes_cli/tools_config.py: remove RL display entry, _DEFAULT_OFF_TOOLSETS, setup block, and rl_training post-setup handler - tools/budget_config.py: remove RL environment reference in docstring - tests/test_model_tools.py: remove rl_tools from expected groups - tests/run_agent/test_streaming_tool_call_repair.py: fix stale cross-reference * chore: remove rl/yc-bench extras and tinker-atropos refs from pyproject.toml - Remove rl extra (atroposlib, tinker, fastapi, uvicorn, wandb) - Remove yc-bench extra - Remove rl_cli from py-modules - Remove [tool.ty.src] exclude for tinker-atropos - Remove [tool.ruff] exclude for tinker-atropos - Regenerate uv.lock * chore: remove tinker-atropos from install/setup scripts - setup-hermes.sh: remove entire tinker-atropos submodule install block - scripts/install.sh: remove both tinker-atropos blocks (Termux + standard) - scripts/install.ps1: remove tinker-atropos block - nix/hermes-agent.nix: remove tinker-atropos pip install line * chore: remove RL references from cli-config.yaml.example * docs: remove Atropos/RL references from README, CONTRIBUTING, AGENTS.md * docs: remove RL/Atropos references from website - Delete: environments.md, rl-training.md, mlops-hermes-atropos-environments.md - sidebars.ts: remove rl-training and environments sidebar entries - optional-skills-catalog.md: remove hermes-atropos-environments row - tools-reference.md: remove entire rl toolset section - toolsets-reference.md: remove rl row + update example - integrations/index.md: remove RL Training bullet - architecture.md: remove environments/ from tree + RL section - contributing.md: remove tinker-atropos setup - updating.md: remove tinker-atropos install + stale submodule update * chore: remove remaining RL/Atropos stragglers - hermes_cli/config.py: remove TINKER_API_KEY + WANDB_API_KEY env var defs - hermes_cli/doctor.py: remove Submodules check section (tinker-atropos) - hermes_cli/setup.py: remove RL Training status check - hermes_cli/status.py: remove Tinker + WandB from API key status display - agent/display.py: remove both rl_* tool preview/activity blocks - website/docs: remove RL references from providers.md + env-variables.md - tests: remove TINKER_API_KEY from conftest, set_config_value, setup_script * chore: remove RL training section from .env.example |
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Teknium
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ded194eb6a |
chore(skills): move heavy training skills + outlines to optional-skills (#22912)
These skills require heavy GPU/CUDA stacks or are niche enough that they shouldn't be active by default. Moved to optional-skills/ where users opt-in via `hermes skills install official/...`. Moved: - mlops/training/axolotl - mlops/training/trl-fine-tuning - mlops/training/unsloth - mlops/inference/outlines Counts: 91 -> 87 built-in, 72 -> 76 optional. Auto-regenerated docs (per-skill pages + catalogs) reflect the move. |
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Teknium
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db22efbe88 |
feat(optional-skills): declare platforms frontmatter for all 63 undeclared skills
Extends the Windows-gating work to the optional-skills/ tree. Every
SKILL.md that previously omitted the platforms: field now carries an
explicit declaration, which Hermes's loader (agent.skill_utils.
skill_matches_platform) honors to skip-load on incompatible OSes.
58 skills declared cross-platform (platforms: [linux, macos, windows]):
autonomous-ai-agents/blackbox, autonomous-ai-agents/honcho
blockchain/base, blockchain/solana
communication/one-three-one-rule
creative/blender-mcp, creative/concept-diagrams, creative/hyperframes,
creative/kanban-video-orchestrator, creative/meme-generation
devops/cli (inference-sh-cli), devops/docker-management
dogfood/adversarial-ux-test
email/agentmail
finance/3-statement-model, finance/comps-analysis, finance/dcf-model,
finance/excel-author, finance/lbo-model, finance/merger-model,
finance/pptx-author
health/fitness-nutrition, health/neuroskill-bci
mcp/fastmcp, mcp/mcporter
migration/openclaw-migration
mlops/accelerate, mlops/chroma, mlops/clip, mlops/guidance,
mlops/hermes-atropos-environments, mlops/huggingface-tokenizers,
mlops/instructor, mlops/lambda-labs, mlops/llava, mlops/modal,
mlops/peft, mlops/pinecone, mlops/pytorch-lightning, mlops/qdrant,
mlops/saelens, mlops/simpo, mlops/stable-diffusion
productivity/canvas, productivity/shop-app, productivity/shopify,
productivity/siyuan, productivity/telephony
research/domain-intel, research/drug-discovery, research/duckduckgo-search,
research/gitnexus-explorer, research/parallel-cli, research/scrapling
security/1password, security/oss-forensics, security/sherlock
web-development/page-agent
5 skills gated from Windows (platforms: [linux, macos]):
mlops/flash-attention - Flash Attention wheels are Linux-first; Windows
install requires building from source with CUDA
mlops/faiss - faiss-gpu has no Windows wheel; gate rather than
leak partial (faiss-cpu) support
mlops/nemo-curator - NVIDIA NeMo ecosystem has no first-class Windows path
mlops/slime - Megatron+SGLang RL stack is Linux-only in practice
mlops/whisper - openai-whisper + ffmpeg setup on Windows is
non-trivial; gate until Windows install stanza lands
Methodology: scanned every SKILL.md for Windows-hostile signals
(apt-get, brew, systemd, osascript, ptrace, X11 binaries, POSIX-only
Python APIs, Docker POSIX $(pwd) bind-mounts, explicit 'linux-only' /
'macos-only' text). 3 skills flagged as having hard signals on review:
docker-management and qdrant only had POSIX $(pwd) docker examples and
the tools themselves (Docker Desktop, Qdrant) run fine on Windows —
declared ALL. whisper had an apt/brew ffmpeg install path and nothing
else but the openai-whisper Windows install story is rough enough to
warrant gating.
Strict-over-lenient policy: when in doubt, gate. Easier to un-gate after
verified Windows support lands than to leak partial support that
manifests as mid-task failures for Windows users.
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Teknium
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b18b17f9c9 |
feat(skills): gate 7 Linux/macOS-only skills from Windows via platforms frontmatter
Hermes's skill loader (agent/skill_utils.skill_matches_platform) already honors the 'platforms:' frontmatter field and skip-loads skills whose declared platform list doesn't include sys.platform. Seven bundled skills are in fact Linux/macOS-only but never declared it, so they leak into Windows skill listings and sometimes load with broken instructions. Audited all 160 SKILL.md files (skills/ + optional-skills/) for Windows- hostile signals: apt-get/brew/systemd/chmod+x install flows, ptrace/proc runtime dependencies, bash-only launcher scripts, and package dependencies with no Windows build. The 7 below fail one or more of those tests in a way that fundamentally can't be papered over by docs edits: minecraft-modpack-server bash start.sh + chmod +x + apt openjdk evaluating-llms-harness lm-eval-harness bash launcher scripts distributed-llm-pretraining- torchtitan bash multi-node torchrun launcher python-debugpy remote attach relies on /proc ptrace_scope pytorch-fsdp NCCL backend; Windows path is WSL only tensorrt-llm NVIDIA TensorRT-LLM has no Windows build searxng-search Docker volume flow assumes POSIX $(pwd) All seven get 'platforms: [linux, macos]'. On Windows the loader now skips them silently — no more phantom skill listings, no more mid-task failures because an Apple-only path was surfaced as a suggestion. Cross-platform skills that merely CONTAIN signals in examples or install-instructions (brew install as one of several paths, /tmp/ in a code snippet, etc.) are NOT touched by this commit. A broader audit that declares the ~140 cross-platform skills as 'platforms: [linux, macos, windows]' can follow as a separate change once each has been verified working on Windows. The installed user copies under ~/AppData/Local/hermes/skills/ (when they exist) are also patched so the running session reflects the gating immediately, but only the in-repo files are committed here. |
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WadydX
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58f93fb7d3 | docs: remove dead papers.md link from saelens references | ||
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WadydX
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2d5f20684a | docs: remove dead reference links in flash-attention skill | ||
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Teknium
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66ee081dc1 |
skills: move 7 niche mlops/mcp skills to optional (#12474)
Built-in → optional-skills/: mlops/training/peft → optional-skills/mlops/peft mlops/training/pytorch-fsdp → optional-skills/mlops/pytorch-fsdp mlops/models/clip → optional-skills/mlops/clip mlops/models/stable-diffusion → optional-skills/mlops/stable-diffusion mlops/models/whisper → optional-skills/mlops/whisper mlops/cloud/modal → optional-skills/mlops/modal mcp/mcporter → optional-skills/mcp/mcporter Built-in mlops training kept: axolotl, trl-fine-tuning, unsloth. Built-in mlops models kept: audiocraft, segment-anything. Built-in mlops evaluation/research/huggingface-hub/inference all kept. native-mcp stays built-in (documents the native MCP tool); mcporter was a redundant alternative CLI. Also: removed now-empty skills/mlops/cloud/ dir, refreshed skills/mlops/models/DESCRIPTION.md and skills/mcp/DESCRIPTION.md to match what's left, and synchronized both catalog pages (skills-catalog.md, optional-skills-catalog.md). |
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Teknium
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73bccc94c7 |
skills: consolidate mlops redundancies (gguf+llama-cpp, grpo+trl, guidance→optional) (#11965)
Three tightly-scoped built-in skill consolidations to reduce redundancy in the available_skills listing injected into every system prompt: 1. gguf-quantization → llama-cpp (merged) GGUF is llama.cpp's format; two skills covered the same toolchain. The merged llama-cpp skill keeps the full K-quant table + imatrix workflow from gguf and the ROCm/benchmarks/supported-models sections from the original llama-cpp. All 5 reference files preserved. 2. grpo-rl-training → fine-tuning-with-trl (folded in) GRPO isn't a framework, it's a trainer inside TRL. Moved the 17KB deep-dive SKILL.md to references/grpo-training.md and the working template to templates/basic_grpo_training.py. TRL's GRPO workflow section now points to both. Atropos skill's related_skills updated. 3. guidance → optional-skills/mlops/ Dropped from built-in. Outlines (still built-in) covers the same structured-generation ground with wider adoption. Listed in the optional catalog for users who specifically want Guidance. Net: 3 fewer built-in skill lines in every system prompt, zero content loss. Contributor authorship preserved via git rename detection. |
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Teknium
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5ceed021dc |
feat(gateway): skill-aware slash commands, paginated /commands, Telegram 100-cap (#3934)
* feat(gateway): skill-aware slash commands, paginated /commands, Telegram 100-cap Map active skills to Telegram's slash command menu so users can discover and invoke skills directly. Three changes: 1. Telegram menu now includes active skill commands alongside built-in commands, capped at 100 entries (Telegram Bot API limit). Overflow commands remain callable but hidden from the picker. Logged at startup when cap is hit. 2. New /commands [page] gateway command for paginated browsing of all commands + skills. /help now shows first 10 skill commands and points to /commands for the full list. 3. When a user types a slash command that matches a disabled or uninstalled skill, they get actionable guidance: - Disabled: 'Enable it with: hermes skills config' - Optional (not installed): 'Install with: hermes skills install official/<path>' Built on ideas from PR #3921 by @kshitijk4poor. * chore: move 21 niche skills to optional-skills Move specialized/niche skills from built-in (skills/) to optional (optional-skills/) to reduce the default skill count. Users can install them with: hermes skills install official/<category>/<name> Moved skills (21): - mlops: accelerate, chroma, faiss, flash-attention, hermes-atropos-environments, huggingface-tokenizers, instructor, lambda-labs, llava, nemo-curator, pinecone, pytorch-lightning, qdrant, saelens, simpo, slime, tensorrt-llm, torchtitan - research: domain-intel, duckduckgo-search - devops: inference-sh cli Built-in skills: 96 → 75 Optional skills: 22 → 43 * fix: only include repo built-in skills in Telegram menu, not user-installed User-installed skills (from hub or manually added) stay accessible via /skills and by typing the command directly, but don't get registered in the Telegram slash command picker. Only skills whose SKILL.md is under the repo's skills/ directory are included in the menu. This keeps the Telegram menu focused on the curated built-in set while user-installed skills remain discoverable through /skills and /commands. |
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Teknium
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d50e0711c2 |
refactor(tts): replace NeuTTS optional skill with built-in provider + setup flow
Remove the optional skill (redundant now that NeuTTS is a built-in TTS provider). Replace neutts_cli dependency with a standalone synthesis helper (tools/neutts_synth.py) that calls the neutts Python API directly in a subprocess. Add TTS provider selection to hermes setup: - 'hermes setup' now prompts for TTS provider after model selection - 'hermes setup tts' available as standalone section - Selecting NeuTTS checks for deps and offers to install: espeak-ng (system) + neutts[all] (pip) - ElevenLabs/OpenAI selections prompt for API keys - Tool status display shows NeuTTS install state Changes: - Remove optional-skills/mlops/models/neutts/ (skill + CLI scaffold) - Add tools/neutts_synth.py (standalone synthesis subprocess helper) - Move jo.wav/jo.txt to tools/neutts_samples/ (bundled default voice) - Refactor _generate_neutts() — uses neutts API via subprocess, no neutts_cli dependency, config-driven ref_audio/ref_text/model/device - Add TTS setup to hermes_cli/setup.py (SETUP_SECTIONS, tool status) - Update config.py defaults (ref_audio, ref_text, model, device) |
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Tekniumandunmodeled-tyler
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cb0deb5f9d |
feat: add NeuTTS optional skill + local TTS provider backend
* feat(skills): add bundled neutts optional skill Add NeuTTS optional skill with CLI scaffold, bootstrap helper, and sample voice profile. Also fixes skills_hub.py to handle binary assets (WAV files) during skill installation. Changes: - optional-skills/mlops/models/neutts/ — skill + CLI scaffold - tools/skills_hub.py — binary asset support (read_bytes, write_bytes) - tests/tools/test_skills_hub.py — regression tests for binary assets * feat(tts): add NeuTTS as local TTS provider backend Add NeuTTS as a fourth TTS provider option alongside Edge, ElevenLabs, and OpenAI. NeuTTS runs fully on-device via neutts_cli — no API key needed. Provider behavior: - Explicit: set tts.provider to 'neutts' in config.yaml - Fallback: when Edge TTS is unavailable and neutts_cli is installed, automatically falls back to NeuTTS instead of failing - check_tts_requirements() now includes NeuTTS in availability checks NeuTTS outputs WAV natively. For Telegram voice bubbles, ffmpeg converts to Opus (same pattern as Edge TTS). Changes: - tools/tts_tool.py — _generate_neutts(), _check_neutts_available(), provider dispatch, fallback logic, Opus conversion - hermes_cli/config.py — tts.neutts config defaults --------- Co-authored-by: unmodeled-tyler <unmodeled.tyler@proton.me> |