docs: deep audit — fix stale config keys, missing commands, and registry drift (#22784)

* docs: deep audit — fix stale config keys, missing commands, and registry drift

Cross-checked ~80 high-impact docs pages (getting-started, reference, top-level
user-guide, user-guide/features) against the live registries:

  hermes_cli/commands.py    COMMAND_REGISTRY (slash commands)
  hermes_cli/auth.py        PROVIDER_REGISTRY (providers)
  hermes_cli/config.py      DEFAULT_CONFIG (config keys)
  toolsets.py               TOOLSETS (toolsets)
  tools/registry.py         get_all_tool_names() (tools)
  python -m hermes_cli.main <subcmd> --help (CLI args)

reference/
- cli-commands.md: drop duplicate hermes fallback row + duplicate section,
  add stepfun/lmstudio to --provider enum, expand auth/mcp/curator subcommand
  lists to match --help output (status/logout/spotify, login, archive/prune/
  list-archived).
- slash-commands.md: add missing /sessions and /reload-skills entries +
  correct the cross-platform Notes line.
- tools-reference.md: drop bogus '68 tools' headline, drop fictional
  'browser-cdp toolset' (these tools live in 'browser' and are runtime-gated),
  add missing 'kanban' and 'video' toolset sections, fix MCP example to use
  the real mcp_<server>_<tool> prefix.
- toolsets-reference.md: list browser_cdp/browser_dialog inside the 'browser'
  row, add missing 'kanban' and 'video' toolset rows, drop the stale
  '38 tools' count for hermes-cli.
- profile-commands.md: add missing install/update/info subcommands, document
  fish completion.
- environment-variables.md: dedupe GMI_API_KEY/GMI_BASE_URL rows (kept the
  one with the correct gmi-serving.com default).
- faq.md: Anthropic/Google/OpenAI examples — direct providers exist (not just
  via OpenRouter), refresh the OpenAI model list.

getting-started/
- installation.md: PortableGit (not MinGit) is what the Windows installer
  fetches; document the 32-bit MinGit fallback.
- installation.md / termux.md: installer prefers .[termux-all] then falls
  back to .[termux].
- nix-setup.md: Python 3.12 (not 3.11), Node.js 22 (not 20); fix invalid
  'nix flake update --flake' invocation.
- updating.md: 'hermes backup restore --state pre-update' doesn't exist —
  point at the snapshot/quick-snapshot flow; correct config key
  'updates.pre_update_backup' (was 'update.backup').

user-guide/
- configuration.md: api_max_retries default 3 (not 2); display.runtime_footer
  is the real key (not display.runtime_metadata_footer); checkpoints defaults
  enabled=false / max_snapshots=20 (not true / 50).
- configuring-models.md: 'hermes model list' / 'hermes model set ...' don't
  exist — hermes model is interactive only.
- tui.md: busy_indicator -> tui_status_indicator with values
  kaomoji|emoji|unicode|ascii (not kawaii|minimal|dots|wings|none).
- security.md: SSH backend keys (TERMINAL_SSH_HOST/USER/KEY) live in .env,
  not config.yaml.
- windows-wsl-quickstart.md: there is no 'hermes api' subcommand — the
  OpenAI-compatible API server runs inside hermes gateway.

user-guide/features/
- computer-use.md: approvals.mode (not security.approval_level); fix broken
  ./browser-use.md link to ./browser.md.
- fallback-providers.md: top-level fallback_providers (not
  model.fallback_providers); the picker is subcommand-based, not modal.
- api-server.md: API_SERVER_* are env vars — write to per-profile .env,
  not 'hermes config set' which targets YAML.
- web-search.md: drop web_crawl as a registered tool (it isn't); deep-crawl
  modes are exposed through web_extract.
- kanban.md: failure_limit default is 2, not '~5'.
- plugins.md: drop hard-coded '33 providers' count.
- honcho.md: fix unclosed quote in echo HONCHO_API_KEY snippet; document
  that 'hermes honcho' subcommand is gated on memory.provider=honcho;
  reconcile subcommand list with actual --help output.
- memory-providers.md: legacy 'hermes honcho setup' redirect documented.

Verified via 'npm run build' — site builds cleanly; broken-link count went
from 149 to 146 (no regressions, fixed a few in passing).

* docs: round 2 audit fixes + regenerate skill catalogs

Follow-up to the previous commit on this branch:

Round 2 manual fixes:
- quickstart.md: KIMI_CODING_API_KEY mentioned alongside KIMI_API_KEY;
  voice-mode and ACP install commands rewritten — bare 'pip install ...'
  doesn't work for curl-installed setups (no pip on PATH, not in repo
  dir); replaced with 'cd ~/.hermes/hermes-agent && uv pip install -e
  ".[voice]"'. ACP already ships in [all] so the curl install includes it.
- cli.md / configuration.md: 'auxiliary.compression.model' shown as
  'google/gemini-3-flash-preview' (the doc's own claimed default);
  actual default is empty (= use main model). Reworded as 'leave empty
  (default) or pin a cheap model'.
- built-in-plugins.md: added the bundled 'kanban/dashboard' plugin row
  that was missing from the table.

Regenerated skill catalogs:
- ran website/scripts/generate-skill-docs.py to refresh all 163 per-skill
  pages and both reference catalogs (skills-catalog.md,
  optional-skills-catalog.md). This adds the entries that were genuinely
  missing — productivity/teams-meeting-pipeline (bundled),
  optional/finance/* (entire category — 7 skills:
  3-statement-model, comps-analysis, dcf-model, excel-author, lbo-model,
  merger-model, pptx-author), creative/hyperframes,
  creative/kanban-video-orchestrator, devops/watchers,
  productivity/shop-app, research/searxng-search,
  apple/macos-computer-use — and rewrites every other per-skill page from
  the current SKILL.md. Most diffs are tiny (one line of refreshed
  metadata).

Validation:
- 'npm run build' succeeded.
- Broken-link count moved 146 -> 155 — the +9 are zh-Hans translation
  shells that lag every newly-added skill page (pre-existing pattern).
  No regressions on any en/ page.

website/docs/user-guide/skills/bundled/mlops/mlops-evaluation-lm-evaluation-harness.md

@@ -20,6 +20,7 @@ lm-eval-harness: benchmark LLMs (MMLU, GSM8K, etc.).
 | Author | Orchestra Research |
 | License | MIT |
 | Dependencies | `lm-eval`, `transformers`, `vllm` |
+| Platforms | linux, macos |
 | Tags | `Evaluation`, `LM Evaluation Harness`, `Benchmarking`, `MMLU`, `HumanEval`, `GSM8K`, `EleutherAI`, `Model Quality`, `Academic Benchmarks`, `Industry Standard` |
 
 ## Reference: full SKILL.md

website/docs/user-guide/skills/bundled/mlops/mlops-evaluation-weights-and-biases.md

@@ -20,6 +20,7 @@ W&B: log ML experiments, sweeps, model registry, dashboards.
 | Author | Orchestra Research |
 | License | MIT |
 | Dependencies | `wandb` |
+| Platforms | linux, macos, windows |
 | Tags | `MLOps`, `Weights And Biases`, `WandB`, `Experiment Tracking`, `Hyperparameter Tuning`, `Model Registry`, `Collaboration`, `Real-Time Visualization`, `PyTorch`, `TensorFlow`, `HuggingFace` |
 
 ## Reference: full SKILL.md

website/docs/user-guide/skills/bundled/mlops/mlops-huggingface-hub.md

@@ -19,6 +19,7 @@ HuggingFace hf CLI: search/download/upload models, datasets.
 | Version | `1.0.0` |
 | Author | Hugging Face |
 | License | MIT |
+| Platforms | linux, macos, windows |
 
 ## Reference: full SKILL.md
 

website/docs/user-guide/skills/bundled/mlops/mlops-inference-llama-cpp.md

@@ -20,6 +20,7 @@ llama.cpp local GGUF inference + HF Hub model discovery.
 | Author | Orchestra Research |
 | License | MIT |
 | Dependencies | `llama-cpp-python>=0.2.0` |
+| Platforms | linux, macos, windows |
 | Tags | `llama.cpp`, `GGUF`, `Quantization`, `Hugging Face Hub`, `CPU Inference`, `Apple Silicon`, `Edge Deployment`, `AMD GPUs`, `Intel GPUs`, `NVIDIA`, `URL-first` |
 
 ## Reference: full SKILL.md

website/docs/user-guide/skills/bundled/mlops/mlops-inference-obliteratus.md

@@ -20,6 +20,7 @@ OBLITERATUS: abliterate LLM refusals (diff-in-means).
 | Author | Hermes Agent |
 | License | MIT |
 | Dependencies | `obliteratus`, `torch`, `transformers`, `bitsandbytes`, `accelerate`, `safetensors` |
+| Platforms | linux, macos |
 | Tags | `Abliteration`, `Uncensoring`, `Refusal-Removal`, `LLM`, `Weight-Projection`, `SVD`, `Mechanistic-Interpretability`, `HuggingFace`, `Model-Surgery` |
 | Related skills | `vllm`, `gguf`, [`huggingface-tokenizers`](/docs/user-guide/skills/optional/mlops/mlops-huggingface-tokenizers) |
 

website/docs/user-guide/skills/bundled/mlops/mlops-inference-outlines.md

@@ -20,6 +20,7 @@ Outlines: structured JSON/regex/Pydantic LLM generation.
 | Author | Orchestra Research |
 | License | MIT |
 | Dependencies | `outlines`, `transformers`, `vllm`, `pydantic` |
+| Platforms | linux, macos, windows |
 | Tags | `Prompt Engineering`, `Outlines`, `Structured Generation`, `JSON Schema`, `Pydantic`, `Local Models`, `Grammar-Based Generation`, `vLLM`, `Transformers`, `Type Safety` |
 
 ## Reference: full SKILL.md

website/docs/user-guide/skills/bundled/mlops/mlops-inference-vllm.md

@@ -20,6 +20,7 @@ vLLM: high-throughput LLM serving, OpenAI API, quantization.
 | Author | Orchestra Research |
 | License | MIT |
 | Dependencies | `vllm`, `torch`, `transformers` |
+| Platforms | linux, macos |
 | Tags | `vLLM`, `Inference Serving`, `PagedAttention`, `Continuous Batching`, `High Throughput`, `Production`, `OpenAI API`, `Quantization`, `Tensor Parallelism` |
 
 ## Reference: full SKILL.md

website/docs/user-guide/skills/bundled/mlops/mlops-models-audiocraft.md

@@ -20,6 +20,7 @@ AudioCraft: MusicGen text-to-music, AudioGen text-to-sound.
 | Author | Orchestra Research |
 | License | MIT |
 | Dependencies | `audiocraft`, `torch>=2.0.0`, `transformers>=4.30.0` |
+| Platforms | linux, macos |
 | Tags | `Multimodal`, `Audio Generation`, `Text-to-Music`, `Text-to-Audio`, `MusicGen` |
 
 ## Reference: full SKILL.md

website/docs/user-guide/skills/bundled/mlops/mlops-models-segment-anything.md

@@ -20,6 +20,7 @@ SAM: zero-shot image segmentation via points, boxes, masks.
 | Author | Orchestra Research |
 | License | MIT |
 | Dependencies | `segment-anything`, `transformers>=4.30.0`, `torch>=1.7.0` |
+| Platforms | linux, macos, windows |
 | Tags | `Multimodal`, `Image Segmentation`, `Computer Vision`, `SAM`, `Zero-Shot` |
 
 ## Reference: full SKILL.md

website/docs/user-guide/skills/bundled/mlops/mlops-research-dspy.md

@@ -20,6 +20,7 @@ DSPy: declarative LM programs, auto-optimize prompts, RAG.
 | Author | Orchestra Research |
 | License | MIT |
 | Dependencies | `dspy`, `openai`, `anthropic` |
+| Platforms | linux, macos, windows |
 | Tags | `Prompt Engineering`, `DSPy`, `Declarative Programming`, `RAG`, `Agents`, `Prompt Optimization`, `LM Programming`, `Stanford NLP`, `Automatic Optimization`, `Modular AI` |
 
 ## Reference: full SKILL.md

website/docs/user-guide/skills/bundled/mlops/mlops-training-axolotl.md

@@ -20,6 +20,7 @@ Axolotl: YAML LLM fine-tuning (LoRA, DPO, GRPO).
 | Author | Orchestra Research |
 | License | MIT |
 | Dependencies | `axolotl`, `torch`, `transformers`, `datasets`, `peft`, `accelerate`, `deepspeed` |
+| Platforms | linux, macos |
 | Tags | `Fine-Tuning`, `Axolotl`, `LLM`, `LoRA`, `QLoRA`, `DPO`, `KTO`, `ORPO`, `GRPO`, `YAML`, `HuggingFace`, `DeepSpeed`, `Multimodal` |
 
 ## Reference: full SKILL.md

website/docs/user-guide/skills/bundled/mlops/mlops-training-trl-fine-tuning.md

@@ -20,6 +20,7 @@ TRL: SFT, DPO, PPO, GRPO, reward modeling for LLM RLHF.
 | Author | Orchestra Research |
 | License | MIT |
 | Dependencies | `trl`, `transformers`, `datasets`, `peft`, `accelerate`, `torch` |
+| Platforms | linux, macos, windows |
 | Tags | `Post-Training`, `TRL`, `Reinforcement Learning`, `Fine-Tuning`, `SFT`, `DPO`, `PPO`, `GRPO`, `RLHF`, `Preference Alignment`, `HuggingFace` |
 
 ## Reference: full SKILL.md

website/docs/user-guide/skills/bundled/mlops/mlops-training-unsloth.md

@@ -20,6 +20,7 @@ Unsloth: 2-5x faster LoRA/QLoRA fine-tuning, less VRAM.
 | Author | Orchestra Research |
 | License | MIT |
 | Dependencies | `unsloth`, `torch`, `transformers`, `trl`, `datasets`, `peft` |
+| Platforms | linux, macos |
 | Tags | `Fine-Tuning`, `Unsloth`, `Fast Training`, `LoRA`, `QLoRA`, `Memory-Efficient`, `Optimization`, `Llama`, `Mistral`, `Gemma`, `Qwen` |
 
 ## Reference: full SKILL.md