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

website/docs/reference/optional-skills-catalog.md

@@ -145,6 +145,7 @@ hermes skills uninstall <skill-name>
 | [**llava**](/docs/user-guide/skills/optional/mlops/mlops-llava) | Large Language and Vision Assistant. Enables visual instruction tuning and image-based conversations. Combines CLIP vision encoder with Vicuna/LLaMA language models. Supports multi-turn image chat, visual question answering, and instruct... |
 | [**modal-serverless-gpu**](/docs/user-guide/skills/optional/mlops/mlops-modal) | Serverless GPU cloud platform for running ML workloads. Use when you need on-demand GPU access without infrastructure management, deploying ML models as APIs, or running batch jobs with automatic scaling. |
 | [**nemo-curator**](/docs/user-guide/skills/optional/mlops/mlops-nemo-curator) | GPU-accelerated data curation for LLM training. Supports text/image/video/audio. Features fuzzy deduplication (16× faster), quality filtering (30+ heuristics), semantic deduplication, PII redaction, NSFW detection. Scales across GPUs wit... |
+| [**obliteratus**](/docs/user-guide/skills/optional/mlops/mlops-obliteratus) | OBLITERATUS: abliterate LLM refusals (diff-in-means). |
 | [**outlines**](/docs/user-guide/skills/optional/mlops/mlops-inference-outlines) | Outlines: structured JSON/regex/Pydantic LLM generation. |
 | [**peft-fine-tuning**](/docs/user-guide/skills/optional/mlops/mlops-peft) | Parameter-efficient fine-tuning for LLMs using LoRA, QLoRA, and 25+ methods. Use when fine-tuning large models (7B-70B) with limited GPU memory, when you need to train &lt;1% of parameters with minimal accuracy loss, or for multi-adapter se... |
 | [**pinecone**](/docs/user-guide/skills/optional/mlops/mlops-pinecone) | Managed vector database for production AI applications. Fully managed, auto-scaling, with hybrid search (dense + sparse), metadata filtering, and namespaces. Low latency (&lt;100ms p95). Use for production RAG, recommendation systems, or se... |
@@ -194,6 +195,7 @@ hermes skills uninstall <skill-name>
 | Skill | Description |
 |-------|-------------|
 | [**1password**](/docs/user-guide/skills/optional/security/security-1password) | Set up and use 1Password CLI (op). Use when installing the CLI, enabling desktop app integration, signing in, and reading/injecting secrets for commands. |
+| [**godmode**](/docs/user-guide/skills/optional/security/security-godmode) | Jailbreak LLMs: Parseltongue, GODMODE, ULTRAPLINIAN. |
 | [**oss-forensics**](/docs/user-guide/skills/optional/security/security-oss-forensics) | Supply chain investigation, evidence recovery, and forensic analysis for GitHub repositories. Covers deleted commit recovery, force-push detection, IOC extraction, multi-source evidence collection, hypothesis formation/validation, and st... |
 | [**sherlock**](/docs/user-guide/skills/optional/security/security-sherlock) | OSINT username search across 400+ social networks. Hunt down social media accounts by username. |
 | [**web-pentest**](/docs/user-guide/skills/optional/security/security-web-pentest) | Authorized web application penetration testing — reconnaissance, vulnerability analysis, proof-based exploitation, and professional reporting. Adapts Shannon's "No Exploit, No Report" methodology with hard guardrails for scope, authoriza... |

website/docs/reference/skills-catalog.md

@@ -105,7 +105,6 @@ If a skill is missing from this list but present in the repo, the catalog is reg
 | [`huggingface-hub`](/docs/user-guide/skills/bundled/mlops/mlops-huggingface-hub) | HuggingFace hf CLI: search/download/upload models, datasets. | `mlops/huggingface-hub` |
 | [`llama-cpp`](/docs/user-guide/skills/bundled/mlops/mlops-inference-llama-cpp) | llama.cpp local GGUF inference + HF Hub model discovery. | `mlops/inference/llama-cpp` |
 | [`evaluating-llms-harness`](/docs/user-guide/skills/bundled/mlops/mlops-evaluation-lm-evaluation-harness) | lm-eval-harness: benchmark LLMs (MMLU, GSM8K, etc.). | `mlops/evaluation/lm-evaluation-harness` |
-| [`obliteratus`](/docs/user-guide/skills/bundled/mlops/mlops-inference-obliteratus) | OBLITERATUS: abliterate LLM refusals (diff-in-means). | `mlops/inference/obliteratus` |
 | [`segment-anything-model`](/docs/user-guide/skills/bundled/mlops/mlops-models-segment-anything) | SAM: zero-shot image segmentation via points, boxes, masks. | `mlops/models/segment-anything` |
 | [`serving-llms-vllm`](/docs/user-guide/skills/bundled/mlops/mlops-inference-vllm) | vLLM: high-throughput LLM serving, OpenAI API, quantization. | `mlops/inference/vllm` |
 | [`weights-and-biases`](/docs/user-guide/skills/bundled/mlops/mlops-evaluation-weights-and-biases) | W&B: log ML experiments, sweeps, model registry, dashboards. | `mlops/evaluation/weights-and-biases` |
@@ -129,12 +128,6 @@ If a skill is missing from this list but present in the repo, the catalog is reg
 | [`powerpoint`](/docs/user-guide/skills/bundled/productivity/productivity-powerpoint) | Create, read, edit .pptx decks, slides, notes, templates. | `productivity/powerpoint` |
 | [`teams-meeting-pipeline`](/docs/user-guide/skills/bundled/productivity/productivity-teams-meeting-pipeline) | Operate the Teams meeting summary pipeline via Hermes CLI — summarize meetings, inspect pipeline status, replay jobs, manage Microsoft Graph subscriptions. | `productivity/teams-meeting-pipeline` |
 
-## red-teaming
-
-| Skill | Description | Path |
-|-------|-------------|------|
-| [`godmode`](/docs/user-guide/skills/bundled/red-teaming/red-teaming-godmode) | Jailbreak LLMs: Parseltongue, GODMODE, ULTRAPLINIAN. | `red-teaming/godmode` |
-
 ## research
 
 | Skill | Description | Path |