mirror of
https://github.com/NousResearch/hermes-agent.git
synced 2026-04-25 00:51:20 +00:00
docs: correctness audit — fix wrong values, add missing coverage (#11972)
Comprehensive audit of every reference/messaging/feature doc page against the
live code registries (PROVIDER_REGISTRY, OPTIONAL_ENV_VARS, COMMAND_REGISTRY,
TOOLSETS, tool registry, on-disk skills). Every fix was verified against code
before writing.
### Wrong values fixed (users would paste-and-fail)
- reference/environment-variables.md:
- DASHSCOPE_BASE_URL default was `coding-intl.dashscope.aliyuncs.com/v1` \u2192
actual `dashscope-intl.aliyuncs.com/compatible-mode/v1`.
- MINIMAX_BASE_URL and MINIMAX_CN_BASE_URL defaults were `/v1` \u2192 actual
`/anthropic` (Hermes calls MiniMax via its Anthropic Messages endpoint).
- reference/toolsets-reference.md MCP example used the non-existent nested
`mcp: servers:` key \u2192 real key is the flat `mcp_servers:`.
- reference/skills-catalog.md listed ~20 bundled skills that no longer exist
on disk (all moved to `optional-skills/`). Regenerated the whole bundled
section from `skills/**/SKILL.md` \u2014 79 skills, accurate paths and names.
- messaging/slack.md ":::info" callout claimed Slack has no
`free_response_channels` equivalent; both the env var and the yaml key are
in fact read.
- messaging/qqbot.md documented `QQ_MARKDOWN_SUPPORT` as an env var, but the
adapter only reads `extra.markdown_support` from config.yaml. Removed the
env var row and noted config-only nature.
- messaging/qqbot.md `hermes setup gateway` \u2192 `hermes gateway setup`.
### Missing coverage added
- Providers: AWS Bedrock and Qwen Portal (qwen-oauth) \u2014 both in
PROVIDER_REGISTRY but undocumented everywhere. Added sections to
integrations/providers.md, rows to quickstart.md and fallback-providers.md.
- integrations/providers.md "Fallback Model" provider list now includes
gemini, google-gemini-cli, qwen-oauth, xai, nvidia, ollama-cloud, bedrock.
- reference/cli-commands.md `--provider` enum and HERMES_INFERENCE_PROVIDER
enum in env-vars now include the same set.
- reference/slash-commands.md: added `/agents` (alias `/tasks`) and `/copy`.
Removed duplicate rows for `/snapshot`, `/fast` (\u00d72), `/debug`.
- reference/tools-reference.md: fixed "47 built-in tools" \u2192 52. Added
`feishu_doc` and `feishu_drive` toolset sections.
- reference/toolsets-reference.md: added `feishu_doc` / `feishu_drive` core
rows + all missing `hermes-<platform>` toolsets in the platform table
(bluebubbles, dingtalk, feishu, qqbot, wecom, wecom-callback, weixin,
homeassistant, webhook, gateway). Fixed the `debugging` composite to
describe the actual `includes=[...]` mechanism.
- reference/optional-skills-catalog.md: added `fitness-nutrition`.
- reference/environment-variables.md: added NOUS_BASE_URL,
NOUS_INFERENCE_BASE_URL, NVIDIA_API_KEY/BASE_URL, OLLAMA_API_KEY/BASE_URL,
XAI_API_KEY/BASE_URL, MISTRAL_API_KEY, AWS_REGION/AWS_PROFILE,
BEDROCK_BASE_URL, HERMES_QWEN_BASE_URL, DISCORD_ALLOWED_CHANNELS,
DISCORD_PROXY, TELEGRAM_REPLY_TO_MODE, MATRIX_DEVICE_ID, MATRIX_REACTIONS,
QQBOT_HOME_CHANNEL_NAME, QQ_SANDBOX.
- messaging/discord.md: documented DISCORD_ALLOWED_CHANNELS, DISCORD_PROXY,
HERMES_DISCORD_TEXT_BATCH_DELAY_SECONDS and HERMES_DISCORD_TEXT_BATCH_SPLIT
_DELAY_SECONDS (all actively read by the adapter).
- messaging/matrix.md: documented MATRIX_REACTIONS (default true).
- messaging/telegram.md: removed the redundant second Webhook Mode section
that invented a `telegram.webhook_mode: true` yaml key the adapter does
not read.
- user-guide/features/hooks.md: added `on_session_finalize` and
`on_session_reset` (both emitted via invoke_hook but undocumented).
- user-guide/features/api-server.md: documented GET /health/detailed, the
`/api/jobs/*` CRUD surface, POST /v1/runs, and GET /v1/runs/{id}/events
(10 routes that were live but undocumented).
- user-guide/features/fallback-providers.md: added `approval` and
`title_generation` auxiliary-task rows; added gemini, bedrock, qwen-oauth
to the supported-providers table.
- user-guide/features/tts.md: "seven providers" \u2192 "eight" (post-xAI add
oversight in #11942).
- user-guide/configuration.md: TTS provider enum gains `xai` and `gemini`;
yaml example block gains `mistral:`, `gemini:`, `xai:` subsections.
Auxiliary-provider enum now enumerates all real registry entries.
- reference/faq.md: stale AIAgent/config examples bumped from
`nous/hermes-3-llama-3.1-70b` and `claude-sonnet-4.6` to
`claude-opus-4.7`.
### Docs-site integrity
- guides/build-a-hermes-plugin.md referenced two nonexistent hooks
(`pre_api_request`, `post_api_request`). Replaced with the real
`on_session_finalize` / `on_session_reset` entries.
- messaging/open-webui.md and features/api-server.md had pre-existing
broken links to `/docs/user-guide/features/profiles` (actual path is
`/docs/user-guide/profiles`). Fixed.
- reference/skills-catalog.md had one `<1%` literal that MDX parsed as a
JSX tag. Escaped to `<1%`.
### False positives filtered out (not changed, verified correct)
- `/set-home` is a registered alias of `/sethome` \u2014 docs were fine.
- `hermes setup gateway` is valid syntax (`hermes setup \<section\>`);
changed in qqbot.md for cross-doc consistency, not as a bug fix.
- Telegram reactions "disabled by default" matches code (default `"false"`).
- Matrix encryption "opt-in" matches code (empty env default \u2192 disabled).
- `pre_api_request` / `post_api_request` hooks do NOT exist in current code;
documented instead the real `on_session_finalize` / `on_session_reset`.
- SIGNAL_IGNORE_STORIES is already in env-vars.md (subagent missed it).
Validation:
- `docusaurus build` \u2014 passes (only pre-existing nix-setup anchor warning).
- `ascii-guard lint docs` \u2014 124 files, 0 errors.
- 22 files changed, +317 / \u2212158.
This commit is contained in:
Teknium
GitHub
parent
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commit
54e0eb24c0
22 changed files with 326 additions and 166 deletions
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@ -63,9 +63,6 @@ hermes [global-options] <command> [subcommand/options]
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| `hermes insights` | Show token/cost/activity analytics. |
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| `hermes claw` | OpenClaw migration helpers. |
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| `hermes dashboard` | Launch the web dashboard for managing config, API keys, and sessions. |
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| `hermes debug` | Debug tools — upload logs and system info for support. |
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| `hermes backup` | Back up Hermes home directory to a zip file. |
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| `hermes import` | Restore a Hermes backup from a zip file. |
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| `hermes profile` | Manage profiles — multiple isolated Hermes instances. |
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| `hermes completion` | Print shell completion scripts (bash/zsh). |
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| `hermes version` | Show version information. |
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@ -85,7 +82,7 @@ Common options:
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| `-q`, `--query "..."` | One-shot, non-interactive prompt. |
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| `-m`, `--model <model>` | Override the model for this run. |
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| `-t`, `--toolsets <csv>` | Enable a comma-separated set of toolsets. |
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| `--provider <provider>` | Force a provider: `auto`, `openrouter`, `nous`, `openai-codex`, `copilot-acp`, `copilot`, `anthropic`, `gemini`, `google-gemini-cli`, `huggingface`, `zai`, `kimi-coding`, `minimax`, `minimax-cn`, `kilocode`, `xiaomi`, `arcee`, `alibaba`, `deepseek`, `nvidia`, `ollama-cloud`, `xai` (alias `grok`). |
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| `--provider <provider>` | Force a provider: `auto`, `openrouter`, `nous`, `openai-codex`, `copilot-acp`, `copilot`, `anthropic`, `gemini`, `google-gemini-cli`, `huggingface`, `zai`, `kimi-coding`, `kimi-coding-cn`, `minimax`, `minimax-cn`, `kilocode`, `xiaomi`, `arcee`, `alibaba`, `deepseek`, `nvidia`, `ollama-cloud`, `xai` (alias `grok`), `qwen-oauth`, `bedrock`, `opencode-zen`, `opencode-go`, `ai-gateway`. |
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| `-s`, `--skills <name>` | Preload one or more skills for the session (can be repeated or comma-separated). |
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| `-v`, `--verbose` | Verbose output. |
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| `-Q`, `--quiet` | Programmatic mode: suppress banner/spinner/tool previews. |
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@ -14,6 +14,8 @@ All variables go in `~/.hermes/.env`. You can also set them with `hermes config
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|----------|-------------|
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| `OPENROUTER_API_KEY` | OpenRouter API key (recommended for flexibility) |
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| `OPENROUTER_BASE_URL` | Override the OpenRouter-compatible base URL |
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| `NOUS_BASE_URL` | Override Nous Portal base URL (rarely needed; development/testing only) |
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| `NOUS_INFERENCE_BASE_URL` | Override Nous inference endpoint directly |
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| `AI_GATEWAY_API_KEY` | Vercel AI Gateway API key ([ai-gateway.vercel.sh](https://ai-gateway.vercel.sh)) |
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| `AI_GATEWAY_BASE_URL` | Override AI Gateway base URL (default: `https://ai-gateway.vercel.sh/v1`) |
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| `OPENAI_API_KEY` | API key for custom OpenAI-compatible endpoints (used with `OPENAI_BASE_URL`) |
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@ -35,9 +37,9 @@ All variables go in `~/.hermes/.env`. You can also set them with `hermes config
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| `ARCEEAI_API_KEY` | Arcee AI API key ([chat.arcee.ai](https://chat.arcee.ai/)) |
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| `ARCEE_BASE_URL` | Override Arcee base URL (default: `https://api.arcee.ai/api/v1`) |
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| `MINIMAX_API_KEY` | MiniMax API key — global endpoint ([minimax.io](https://www.minimax.io)) |
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| `MINIMAX_BASE_URL` | Override MiniMax base URL (default: `https://api.minimax.io/v1`) |
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| `MINIMAX_BASE_URL` | Override MiniMax base URL (default: `https://api.minimax.io/anthropic` — Hermes uses MiniMax's Anthropic Messages-compatible endpoint) |
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| `MINIMAX_CN_API_KEY` | MiniMax API key — China endpoint ([minimaxi.com](https://www.minimaxi.com)) |
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| `MINIMAX_CN_BASE_URL` | Override MiniMax China base URL (default: `https://api.minimaxi.com/v1`) |
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| `MINIMAX_CN_BASE_URL` | Override MiniMax China base URL (default: `https://api.minimaxi.com/anthropic`) |
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| `KILOCODE_API_KEY` | Kilo Code API key ([kilo.ai](https://kilo.ai)) |
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| `KILOCODE_BASE_URL` | Override Kilo Code base URL (default: `https://api.kilo.ai/api/gateway`) |
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| `XIAOMI_API_KEY` | Xiaomi MiMo API key ([platform.xiaomimimo.com](https://platform.xiaomimimo.com)) |
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@ -53,7 +55,7 @@ All variables go in `~/.hermes/.env`. You can also set them with `hermes config
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| `ANTHROPIC_API_KEY` | Anthropic Console API key ([console.anthropic.com](https://console.anthropic.com/)) |
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| `ANTHROPIC_TOKEN` | Manual or legacy Anthropic OAuth/setup-token override |
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| `DASHSCOPE_API_KEY` | Alibaba Cloud DashScope API key for Qwen models ([modelstudio.console.alibabacloud.com](https://modelstudio.console.alibabacloud.com/)) |
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| `DASHSCOPE_BASE_URL` | Custom DashScope base URL (default: `https://coding-intl.dashscope.aliyuncs.com/v1`) |
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| `DASHSCOPE_BASE_URL` | Custom DashScope base URL (default: `https://dashscope-intl.aliyuncs.com/compatible-mode/v1`; use `https://dashscope.aliyuncs.com/compatible-mode/v1` for mainland-China region) |
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| `DEEPSEEK_API_KEY` | DeepSeek API key for direct DeepSeek access ([platform.deepseek.com](https://platform.deepseek.com/api_keys)) |
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| `DEEPSEEK_BASE_URL` | Custom DeepSeek API base URL |
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| `NVIDIA_API_KEY` | NVIDIA NIM API key — Nemotron and open models ([build.nvidia.com](https://build.nvidia.com)) |
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@ -62,6 +64,11 @@ All variables go in `~/.hermes/.env`. You can also set them with `hermes config
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| `OLLAMA_BASE_URL` | Override Ollama Cloud base URL (default: `https://ollama.com/v1`) |
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| `XAI_API_KEY` | xAI (Grok) API key for chat + TTS ([console.x.ai](https://console.x.ai/)) |
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| `XAI_BASE_URL` | Override xAI base URL (default: `https://api.x.ai/v1`) |
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| `MISTRAL_API_KEY` | Mistral API key for Voxtral TTS and Voxtral STT ([console.mistral.ai](https://console.mistral.ai)) |
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| `AWS_REGION` | AWS region for Bedrock inference (e.g. `us-east-1`, `eu-central-1`). Read by boto3. |
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| `AWS_PROFILE` | AWS named profile for Bedrock authentication (reads `~/.aws/credentials`). Leave unset to use default boto3 credential chain. |
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| `BEDROCK_BASE_URL` | Override Bedrock runtime base URL (default: `https://bedrock-runtime.us-east-1.amazonaws.com`; usually leave unset and use `AWS_REGION` instead) |
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| `HERMES_QWEN_BASE_URL` | Qwen Portal base URL override (default: `https://portal.qwen.ai/v1`) |
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| `OPENCODE_ZEN_API_KEY` | OpenCode Zen API key — pay-as-you-go access to curated models ([opencode.ai](https://opencode.ai/auth)) |
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| `OPENCODE_ZEN_BASE_URL` | Override OpenCode Zen base URL |
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| `OPENCODE_GO_API_KEY` | OpenCode Go API key — $10/month subscription for open models ([opencode.ai](https://opencode.ai/auth)) |
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@ -79,7 +86,7 @@ For native Anthropic auth, Hermes prefers Claude Code's own credential files whe
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| Variable | Description |
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|----------|-------------|
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| `HERMES_INFERENCE_PROVIDER` | Override provider selection: `auto`, `openrouter`, `nous`, `openai-codex`, `copilot`, `copilot-acp`, `anthropic`, `huggingface`, `zai`, `kimi-coding`, `kimi-coding-cn`, `minimax`, `minimax-cn`, `kilocode`, `xiaomi`, `arcee`, `alibaba`, `deepseek`, `nvidia`, `ollama-cloud`, `xai` (alias `grok`), `google-gemini-cli`, `opencode-zen`, `opencode-go`, `ai-gateway` (default: `auto`) |
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| `HERMES_INFERENCE_PROVIDER` | Override provider selection: `auto`, `openrouter`, `nous`, `openai-codex`, `copilot`, `copilot-acp`, `anthropic`, `huggingface`, `zai`, `kimi-coding`, `kimi-coding-cn`, `minimax`, `minimax-cn`, `kilocode`, `xiaomi`, `arcee`, `alibaba`, `deepseek`, `nvidia`, `ollama-cloud`, `xai` (alias `grok`), `google-gemini-cli`, `qwen-oauth`, `bedrock`, `opencode-zen`, `opencode-go`, `ai-gateway` (default: `auto`) |
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| `HERMES_PORTAL_BASE_URL` | Override Nous Portal URL (for development/testing) |
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| `NOUS_INFERENCE_BASE_URL` | Override Nous inference API URL |
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| `HERMES_NOUS_MIN_KEY_TTL_SECONDS` | Min agent key TTL before re-mint (default: 1800 = 30min) |
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@ -189,11 +196,14 @@ For cloud sandbox backends, persistence is filesystem-oriented. `TERMINAL_LIFETI
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| `TELEGRAM_WEBHOOK_PORT` | Local listen port for webhook server (default: `8443`) |
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| `TELEGRAM_WEBHOOK_SECRET` | Secret token for verifying updates come from Telegram |
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| `TELEGRAM_REACTIONS` | Enable emoji reactions on messages during processing (default: `false`) |
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| `TELEGRAM_REPLY_TO_MODE` | Reply-reference behavior: `off`, `first` (default), or `all`. Matches the Discord pattern. |
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| `TELEGRAM_IGNORED_THREADS` | Comma-separated Telegram forum topic/thread IDs where the bot never responds |
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| `TELEGRAM_PROXY` | Proxy URL for Telegram connections — overrides `HTTPS_PROXY`. Supports `http://`, `https://`, `socks5://` |
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| `DISCORD_BOT_TOKEN` | Discord bot token |
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| `DISCORD_ALLOWED_USERS` | Comma-separated Discord user IDs allowed to use the bot |
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| `DISCORD_ALLOWED_ROLES` | Comma-separated Discord role IDs allowed to use the bot (OR with `DISCORD_ALLOWED_USERS`). Auto-enables the Members intent. Useful when moderation teams churn — role grants propagate automatically. |
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| `DISCORD_ALLOWED_CHANNELS` | Comma-separated Discord channel IDs. When set, the bot only responds in these channels (plus DMs if allowed). Overrides `config.yaml` `discord.allowed_channels`. |
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| `DISCORD_PROXY` | Proxy URL for Discord connections — overrides `HTTPS_PROXY`. Supports `http://`, `https://`, `socks5://` |
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| `DISCORD_HOME_CHANNEL` | Default Discord channel for cron delivery |
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| `DISCORD_HOME_CHANNEL_NAME` | Display name for the Discord home channel |
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| `DISCORD_REQUIRE_MENTION` | Require an @mention before responding in server channels |
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@ -298,6 +308,8 @@ For cloud sandbox backends, persistence is filesystem-oriented. `TERMINAL_LIFETI
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| `QQ_GROUP_ALLOWED_USERS` | Comma-separated QQ group IDs for group @-message access |
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| `QQ_ALLOW_ALL_USERS` | Allow all users (`true`/`false`, overrides `QQ_ALLOWED_USERS`) |
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| `QQBOT_HOME_CHANNEL` | QQ user/group openID for cron delivery and notifications |
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| `QQBOT_HOME_CHANNEL_NAME` | Display name for the QQ home channel |
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| `QQ_SANDBOX` | Route QQ Bot to the sandbox gateway for development testing (`true`/`false`). Use with a sandbox app credential from [q.qq.com](https://q.qq.com). |
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| `MATTERMOST_URL` | Mattermost server URL (e.g. `https://mm.example.com`) |
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| `MATTERMOST_TOKEN` | Bot token or personal access token for Mattermost |
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| `MATTERMOST_ALLOWED_USERS` | Comma-separated Mattermost user IDs allowed to message the bot |
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| `MATRIX_ALLOWED_USERS` | Comma-separated Matrix user IDs allowed to message the bot (e.g. `@alice:matrix.org`) |
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| `MATRIX_HOME_ROOM` | Room ID for proactive message delivery (e.g. `!abc123:matrix.org`) |
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| `MATRIX_ENCRYPTION` | Enable end-to-end encryption (`true`/`false`, default: `false`) |
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| `MATRIX_DEVICE_ID` | Stable Matrix device ID for E2EE persistence across restarts (e.g. `HERMES_BOT`). Without this, E2EE keys rotate every startup and historic-room decrypt breaks. |
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| `MATRIX_REACTIONS` | Enable processing-lifecycle emoji reactions on inbound messages (default: `true`). Set to `false` to disable. |
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| `MATRIX_REQUIRE_MENTION` | Require `@mention` in rooms (default: `true`). Set to `false` to respond to all messages. |
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| `MATRIX_FREE_RESPONSE_ROOMS` | Comma-separated room IDs where bot responds without `@mention` |
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| `MATRIX_AUTO_THREAD` | Auto-create threads for room messages (default: `true`) |
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@ -110,7 +110,7 @@ Yes. Import the `AIAgent` class and use Hermes programmatically:
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```python
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from run_agent import AIAgent
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agent = AIAgent(model="openrouter/nous/hermes-3-llama-3.1-70b")
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agent = AIAgent(model="anthropic/claude-opus-4.7")
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response = agent.chat("Explain quantum computing briefly")
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```
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@ -243,7 +243,7 @@ Make sure the key matches the provider. An OpenAI key won't work with OpenRouter
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hermes model
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# Set a valid model
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hermes config set HERMES_MODEL openrouter/nous/hermes-3-llama-3.1-70b
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hermes config set HERMES_MODEL anthropic/claude-opus-4.7
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# Or specify per-session
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hermes chat --model openrouter/meta-llama/llama-3.1-70b-instruct
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@ -781,7 +781,7 @@ hermes config show | head -20
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hermes model
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# Or test with a known-good model
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hermes chat -q "hello" --model anthropic/claude-sonnet-4.6
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hermes chat -q "hello" --model anthropic/claude-opus-4.7
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```
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If using OpenRouter, make sure your API key has credits. A 400 from OpenRouter often means the model requires a paid plan or the model ID has a typo.
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@ -74,6 +74,7 @@ hermes skills uninstall <skill-name>
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| Skill | Description |
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|-------|-------------|
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| **fitness-nutrition** | Gym workout planner and nutrition tracker. Search 690+ exercises by muscle, equipment, or category via wger. Look up macros and calories for 380,000+ foods via USDA FoodData Central. Computes BMI, TDEE, one-rep max, macro splits, and body fat — pure Python, no pip installs. |
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| **neuroskill-bci** | Brain-Computer Interface (BCI) integration for neuroscience research workflows. |
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## MCP
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@ -27,27 +27,32 @@ Skills for spawning and orchestrating autonomous AI coding agents and multi-agen
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|-------|-------------|------|
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| `claude-code` | Delegate coding tasks to Claude Code (Anthropic's CLI agent). Use for building features, refactoring, PR reviews, and iterative coding. Requires the claude CLI installed. | `autonomous-ai-agents/claude-code` |
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| `codex` | Delegate coding tasks to OpenAI Codex CLI agent. Use for building features, refactoring, PR reviews, and batch issue fixing. Requires the codex CLI and a git repository. | `autonomous-ai-agents/codex` |
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| `hermes-agent-spawning` | Spawn additional Hermes Agent instances as autonomous subprocesses for independent long-running tasks. Supports non-interactive one-shot mode (-q) and interactive PTY mode for multi-turn collaboration. Different from delegate_task — this runs a full separate hermes process. | `autonomous-ai-agents/hermes-agent` |
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| `hermes-agent` | Complete guide to using and extending Hermes Agent — CLI usage, setup, configuration, spawning additional agents, gateway platforms, skills, voice, tools, profiles, and a concise contributor reference. Load this skill when helping users configure Hermes, troubleshoot issues, s… | `autonomous-ai-agents/hermes-agent` |
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| `opencode` | Delegate coding tasks to OpenCode CLI agent for feature implementation, refactoring, PR review, and long-running autonomous sessions. Requires the opencode CLI installed and authenticated. | `autonomous-ai-agents/opencode` |
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## creative
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Creative content generation — ASCII art, hand-drawn diagrams, animations, music, and visual design tools.
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| Skill | Description | Path |
|
||||
|-------|-------------|------|
|
||||
| `architecture-diagram` | Generate dark-themed SVG diagrams of software systems and cloud infrastructure as standalone HTML files with inline SVG graphics. Semantic component colors (cyan=frontend, emerald=backend, violet=database, amber=cloud/AWS, rose=security, orange=message bus), JetBrains Mono fon… | `creative/architecture-diagram` |
|
||||
| `ascii-art` | Generate ASCII art using pyfiglet (571 fonts), cowsay, boxes, toilet, image-to-ascii, remote APIs (asciified, ascii.co.uk), and LLM fallback. No API keys required. | `creative/ascii-art` |
|
||||
| `ascii-video` | Production pipeline for ASCII art video — any format. Converts video/audio/images/generative input into colored ASCII character video output (MP4, GIF, image sequence). Covers: video-to-ASCII conversion, audio-reactive music visualizers, generative ASCII art animations, hybrid… | `creative/ascii-video` |
|
||||
| `excalidraw` | Create hand-drawn style diagrams using Excalidraw JSON format. Generate .excalidraw files for architecture diagrams, flowcharts, sequence diagrams, concept maps, and more. Files can be opened at excalidraw.com or uploaded for shareable links. | `creative/excalidraw` |
|
||||
| `ideation` | Generate project ideas through creative constraints. Use when the user says 'I want to build something', 'give me a project idea', 'I'm bored', 'what should I make', 'inspire me', or any variant of 'I have tools but no direction'. Works for code, art, hardware, writing, tools,… | `creative/creative-ideation` |
|
||||
| `manim-video` | Production pipeline for mathematical and technical animations using Manim Community Edition. Creates 3Blue1Brown-style explainer videos, algorithm visualizations, equation derivations, architecture diagrams, and data stories. Use when users request: animated explanations, math… | `creative/manim-video` |
|
||||
| `p5js` | Production pipeline for interactive and generative visual art using p5.js. Creates browser-based sketches, generative art, data visualizations, interactive experiences, 3D scenes, audio-reactive visuals, and motion graphics — exported as HTML, PNG, GIF, MP4, or SVG. Covers: 2D… | `creative/p5js` |
|
||||
| `popular-web-designs` | 54 production-quality design systems extracted from real websites. Load a template to generate HTML/CSS that matches the visual identity of sites like Stripe, Linear, Vercel, Notion, Airbnb, and more. Each template includes colors, typography, components, layout rules, and rea… | `creative/popular-web-designs` |
|
||||
| `songwriting-and-ai-music` | Songwriting craft, AI music generation prompts (Suno focus), parody/adaptation techniques, phonetic tricks, and lessons learned. These are tools and ideas, not rules. Break any of them when the art calls for it. | `creative/songwriting-and-ai-music` |
|
||||
|
||||
## data-science
|
||||
|
||||
Skills for data science workflows — interactive exploration, Jupyter notebooks, data analysis, and visualization.
|
||||
|
||||
| Skill | Description | Path |
|
||||
|-------|-------------|------|
|
||||
| `jupyter-live-kernel` | Use a live Jupyter kernel for stateful, iterative Python execution via hamelnb. Load this skill when the task involves exploration, iteration, or inspecting intermediate results. | `data-science/jupyter-live-kernel` |
|
||||
|
||||
## creative
|
||||
|
||||
Creative content generation — ASCII art, hand-drawn style diagrams, and visual design tools.
|
||||
|
||||
| Skill | Description | Path |
|
||||
|-------|-------------|------|
|
||||
| `ascii-art` | Generate ASCII art using pyfiglet (571 fonts), cowsay, boxes, toilet, image-to-ascii, remote APIs (asciified, ascii.co.uk), and LLM fallback. No API keys required. | `creative/ascii-art` |
|
||||
| `ascii-video` | "Production pipeline for ASCII art video — any format. Converts video/audio/images/generative input into colored ASCII character video output (MP4, GIF, image sequence). Covers: video-to-ASCII conversion, audio-reactive music visualizers, generative ASCII art animations, hybrid… | `creative/ascii-video` |
|
||||
| `excalidraw` | Create hand-drawn style diagrams using Excalidraw JSON format. Generate .excalidraw files for architecture diagrams, flowcharts, sequence diagrams, concept maps, and more. Files can be opened at excalidraw.com or uploaded for shareable links. | `creative/excalidraw` |
|
||||
| `p5js` | Production pipeline for interactive and generative visual art using p5.js. Create sketches, render them to images/video via headless browser, and serve live previews. Supports canvas animations, data visualizations, and creative coding experiments. | `creative/p5js` |
|
||||
| `jupyter-live-kernel` | Use a live Jupyter kernel for stateful, iterative Python execution via hamelnb. Load this skill when the task involves exploration, iteration, or inspecting intermediate results — data science, ML experimentation, API exploration, or building up complex code step-by-step. Uses… | `data-science/jupyter-live-kernel` |
|
||||
|
||||
## devops
|
||||
|
||||
|
|
@ -55,14 +60,15 @@ DevOps and infrastructure automation skills.
|
|||
|
||||
| Skill | Description | Path |
|
||||
|-------|-------------|------|
|
||||
| `webhook-subscriptions` | Create and manage webhook subscriptions for event-driven agent activation. External services (GitHub, Stripe, CI/CD, IoT) POST events to trigger agent runs. Requires webhook platform to be enabled. | `devops/webhook-subscriptions` |
|
||||
| `webhook-subscriptions` | Create and manage webhook subscriptions for event-driven agent activation. Use when the user wants external services to trigger agent runs automatically. | `devops/webhook-subscriptions` |
|
||||
|
||||
## dogfood
|
||||
|
||||
Internal dogfooding and QA skills used to test Hermes Agent itself.
|
||||
|
||||
| Skill | Description | Path |
|
||||
|-------|-------------|------|
|
||||
| `dogfood` | Systematic exploratory QA testing of web applications — find bugs, capture evidence, and generate structured reports. | `dogfood/dogfood` |
|
||||
| `hermes-agent-setup` | Help users configure Hermes Agent — CLI usage, setup wizard, model/provider selection, tools, skills, voice/STT/TTS, gateway, and troubleshooting. | `dogfood/hermes-agent-setup` |
|
||||
| `dogfood` | Systematic exploratory QA testing of web applications — find bugs, capture evidence, and generate structured reports | `dogfood` |
|
||||
|
||||
## email
|
||||
|
||||
|
|
@ -83,7 +89,7 @@ Skills for setting up, configuring, and managing game servers, modpacks, and gam
|
|||
|
||||
## github
|
||||
|
||||
GitHub workflow skills for managing repositories, pull requests, code reviews, issues, and CI/CD pipelines using the gh CLI and git via terminal.
|
||||
GitHub workflow skills for managing repositories, pull requests, code reviews, issues, and CI/CD pipelines.
|
||||
|
||||
| Skill | Description | Path |
|
||||
|-------|-------------|------|
|
||||
|
|
@ -94,23 +100,17 @@ GitHub workflow skills for managing repositories, pull requests, code reviews, i
|
|||
| `github-pr-workflow` | Full pull request lifecycle — create branches, commit changes, open PRs, monitor CI status, auto-fix failures, and merge. Works with gh CLI or falls back to git + GitHub REST API via curl. | `github/github-pr-workflow` |
|
||||
| `github-repo-management` | Clone, create, fork, configure, and manage GitHub repositories. Manage remotes, secrets, releases, and workflows. Works with gh CLI or falls back to git + GitHub REST API via curl. | `github/github-repo-management` |
|
||||
|
||||
## inference-sh
|
||||
|
||||
Skills for AI app execution via inference.sh cloud platform.
|
||||
|
||||
| Skill | Description | Path |
|
||||
|-------|-------------|------|
|
||||
| `inference-sh-cli` | Run 150+ AI apps via inference.sh CLI (infsh) — image generation, video creation, LLMs, search, 3D, social automation. | `inference-sh/cli` |
|
||||
|
||||
## leisure
|
||||
|
||||
Skills for discovery and everyday tasks.
|
||||
|
||||
| Skill | Description | Path |
|
||||
|-------|-------------|------|
|
||||
| `find-nearby` | Find nearby places (restaurants, cafes, bars, pharmacies, etc.) using OpenStreetMap. Works with coordinates, addresses, cities, zip codes, or Telegram location pins. No API keys needed. | `leisure/find-nearby` |
|
||||
|
||||
## mcp
|
||||
|
||||
Skills for working with MCP (Model Context Protocol) servers, tools, and integrations. Includes the built-in native MCP client (configure servers in config.yaml for automatic tool discovery) and the mcporter CLI bridge for ad-hoc server interaction.
|
||||
Skills for working with MCP (Model Context Protocol) servers, tools, and integrations.
|
||||
|
||||
| Skill | Description | Path |
|
||||
|-------|-------------|------|
|
||||
|
|
@ -126,7 +126,7 @@ Skills for working with media content — YouTube transcripts, GIF search, music
|
|||
| `gif-search` | Search and download GIFs from Tenor using curl. No dependencies beyond curl and jq. Useful for finding reaction GIFs, creating visual content, and sending GIFs in chat. | `media/gif-search` |
|
||||
| `heartmula` | Set up and run HeartMuLa, the open-source music generation model family (Suno-like). Generates full songs from lyrics + tags with multilingual support. | `media/heartmula` |
|
||||
| `songsee` | Generate spectrograms and audio feature visualizations (mel, chroma, MFCC, tempogram, etc.) from audio files via CLI. Useful for audio analysis, music production debugging, and visual documentation. | `media/songsee` |
|
||||
| `youtube-content` | Fetch YouTube video transcripts and transform them into structured content (chapters, summaries, threads, blog posts). | `media/youtube-content` |
|
||||
| `youtube-content` | Fetch YouTube video transcripts and transform them into structured content (chapters, summaries, threads, blog posts). Use when the user shares a YouTube URL or video link, asks to summarize a video, requests a transcript, or wants to extract and reformat content from any YouT… | `media/youtube-content` |
|
||||
|
||||
## mlops
|
||||
|
||||
|
|
@ -134,7 +134,7 @@ General-purpose ML operations tools — model hub management, dataset operations
|
|||
|
||||
| Skill | Description | Path |
|
||||
|-------|-------------|------|
|
||||
| `huggingface-hub` | Hugging Face Hub CLI (hf) — search, download, and upload models and datasets, manage repos, deploy inference endpoints. | `mlops/huggingface-hub` |
|
||||
| `huggingface-hub` | Hugging Face Hub CLI (hf) — search, download, and upload models and datasets, manage repos, query datasets with SQL, deploy inference endpoints, manage Spaces and buckets. | `mlops/huggingface-hub` |
|
||||
|
||||
## mlops/cloud
|
||||
|
||||
|
|
@ -142,19 +142,15 @@ GPU cloud providers and serverless compute platforms for ML workloads.
|
|||
|
||||
| Skill | Description | Path |
|
||||
|-------|-------------|------|
|
||||
| `lambda-labs-gpu-cloud` | Reserved and on-demand GPU cloud instances for ML training and inference. Use when you need dedicated GPU instances with simple SSH access, persistent filesystems, or high-performance multi-node clusters for large-scale training. | `mlops/cloud/lambda-labs` |
|
||||
| `modal-serverless-gpu` | 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. | `mlops/cloud/modal` |
|
||||
|
||||
## mlops/evaluation
|
||||
|
||||
Model evaluation benchmarks, experiment tracking, data curation, tokenizers, and interpretability tools.
|
||||
Model evaluation benchmarks, experiment tracking, and interpretability tools.
|
||||
|
||||
| Skill | Description | Path |
|
||||
|-------|-------------|------|
|
||||
| `evaluating-llms-harness` | Evaluates LLMs across 60+ academic benchmarks (MMLU, HumanEval, GSM8K, TruthfulQA, HellaSwag). Use when benchmarking model quality, comparing models, reporting academic results, or tracking training progress. Industry standard used by EleutherAI, HuggingFace, and major labs. Sup… | `mlops/evaluation/lm-evaluation-harness` |
|
||||
| `huggingface-tokenizers` | Fast tokenizers optimized for research and production. Rust-based implementation tokenizes 1GB in <20 seconds. Supports BPE, WordPiece, and Unigram algorithms. Train custom vocabularies, track alignments, handle padding/truncation. Integrates seamlessly with transformers. Use… | `mlops/evaluation/huggingface-tokenizers` |
|
||||
| `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 with RAPIDS. Use for preparing high-quality t… | `mlops/evaluation/nemo-curator` |
|
||||
| `sparse-autoencoder-training` | Provides guidance for training and analyzing Sparse Autoencoders (SAEs) using SAELens to decompose neural network activations into interpretable features. Use when discovering interpretable features, analyzing superposition, or studying monosemantic representations in language m… | `mlops/evaluation/saelens` |
|
||||
| `evaluating-llms-harness` | Evaluates LLMs across 60+ academic benchmarks (MMLU, HumanEval, GSM8K, TruthfulQA, HellaSwag). Use when benchmarking model quality, comparing models, reporting academic results, or tracking training progress. Industry standard used by EleutherAI, HuggingFace, and major labs. S… | `mlops/evaluation/lm-evaluation-harness` |
|
||||
| `weights-and-biases` | Track ML experiments with automatic logging, visualize training in real-time, optimize hyperparameters with sweeps, and manage model registry with W&B - collaborative MLOps platform | `mlops/evaluation/weights-and-biases` |
|
||||
|
||||
## mlops/inference
|
||||
|
|
@ -163,25 +159,22 @@ Model serving, quantization (GGUF/GPTQ), structured output, inference optimizati
|
|||
|
||||
| Skill | Description | Path |
|
||||
|-------|-------------|------|
|
||||
| `instructor` | Extract structured data from LLM responses with Pydantic validation, retry failed extractions automatically, parse complex JSON with type safety, and stream partial results with Instructor - battle-tested structured output library | `mlops/inference/instructor` |
|
||||
| `llama-cpp` | Run LLM inference with llama.cpp on CPU, Apple Silicon, AMD/Intel GPUs, or NVIDIA — plus GGUF model conversion and quantization (2–8 bit with K-quants and imatrix). Covers CLI, Python bindings, OpenAI-compatible server, and Ollama/LM Studio integration. Use for edge deployment, M1/M2/M3/M4 Macs, CUDA-less environments, or flexible local quantization. | `mlops/inference/llama-cpp` |
|
||||
| `obliteratus` | Remove refusal behaviors from open-weight LLMs using OBLITERATUS — mechanistic interpretability techniques (diff-in-means, SVD, whitened SVD, LEACE, SAE decomposition, etc.) to excise guardrails while preserving reasoning. 9 CLI methods, 28 analysis modules, 116 model presets ac… | `mlops/inference/obliteratus` |
|
||||
| `llama-cpp` | Run LLM inference with llama.cpp on CPU, Apple Silicon, AMD/Intel GPUs, or NVIDIA — plus GGUF model conversion and quantization (2–8 bit with K-quants and imatrix). Covers CLI, Python bindings, OpenAI-compatible server, and Ollama/LM Studio integration. Use for edge deployment… | `mlops/inference/llama-cpp` |
|
||||
| `obliteratus` | Remove refusal behaviors from open-weight LLMs using OBLITERATUS — mechanistic interpretability techniques (diff-in-means, SVD, whitened SVD, LEACE, SAE decomposition, etc.) to excise guardrails while preserving reasoning. 9 CLI methods, 28 analysis modules, 116 model presets … | `mlops/inference/obliteratus` |
|
||||
| `outlines` | Guarantee valid JSON/XML/code structure during generation, use Pydantic models for type-safe outputs, support local models (Transformers, vLLM), and maximize inference speed with Outlines - dottxt.ai's structured generation library | `mlops/inference/outlines` |
|
||||
| `serving-llms-vllm` | Serves LLMs with high throughput using vLLM's PagedAttention and continuous batching. Use when deploying production LLM APIs, optimizing inference latency/throughput, or serving models with limited GPU memory. Supports OpenAI-compatible endpoints, quantization (GPTQ/AWQ/FP8), an… | `mlops/inference/vllm` |
|
||||
| `tensorrt-llm` | Optimizes LLM inference with NVIDIA TensorRT for maximum throughput and lowest latency. Use for production deployment on NVIDIA GPUs (A100/H100), when you need 10-100x faster inference than PyTorch, or for serving models with quantization (FP8/INT4), in-flight batching, and mult… | `mlops/inference/tensorrt-llm` |
|
||||
| `serving-llms-vllm` | Serves LLMs with high throughput using vLLM's PagedAttention and continuous batching. Use when deploying production LLM APIs, optimizing inference latency/throughput, or serving models with limited GPU memory. Supports OpenAI-compatible endpoints, quantization (GPTQ/AWQ/FP8), … | `mlops/inference/vllm` |
|
||||
|
||||
## mlops/models
|
||||
|
||||
Specific model architectures and tools — computer vision (CLIP, SAM, Stable Diffusion), speech (Whisper), audio generation (AudioCraft), and multimodal models (LLaVA).
|
||||
Specific model architectures — computer vision (CLIP, SAM, Stable Diffusion), speech (Whisper), and audio generation (AudioCraft).
|
||||
|
||||
| Skill | Description | Path |
|
||||
|-------|-------------|------|
|
||||
| `audiocraft-audio-generation` | PyTorch library for audio generation including text-to-music (MusicGen) and text-to-sound (AudioGen). Use when you need to generate music from text descriptions, create sound effects, or perform melody-conditioned music generation. | `mlops/models/audiocraft` |
|
||||
| `clip` | OpenAI's model connecting vision and language. Enables zero-shot image classification, image-text matching, and cross-modal retrieval. Trained on 400M image-text pairs. Use for image search, content moderation, or vision-language tasks without fine-tuning. Best for general-purpo… | `mlops/models/clip` |
|
||||
| `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 instruction following. Use for vision-language cha… | `mlops/models/llava` |
|
||||
| `clip` | OpenAI's model connecting vision and language. Enables zero-shot image classification, image-text matching, and cross-modal retrieval. Trained on 400M image-text pairs. Use for image search, content moderation, or vision-language tasks without fine-tuning. Best for general-pur… | `mlops/models/clip` |
|
||||
| `segment-anything-model` | Foundation model for image segmentation with zero-shot transfer. Use when you need to segment any object in images using points, boxes, or masks as prompts, or automatically generate all object masks in an image. | `mlops/models/segment-anything` |
|
||||
| `stable-diffusion-image-generation` | State-of-the-art text-to-image generation with Stable Diffusion models via HuggingFace Diffusers. Use when generating images from text prompts, performing image-to-image translation, inpainting, or building custom diffusion pipelines. | `mlops/models/stable-diffusion` |
|
||||
| `whisper` | OpenAI's general-purpose speech recognition model. Supports 99 languages, transcription, translation to English, and language identification. Six model sizes from tiny (39M params) to large (1550M params). Use for speech-to-text, podcast transcription, or multilingual audio proc… | `mlops/models/whisper` |
|
||||
| `whisper` | OpenAI's general-purpose speech recognition model. Supports 99 languages, transcription, translation to English, and language identification. Six model sizes from tiny (39M params) to large (1550M params). Use for speech-to-text, podcast transcription, or multilingual audio pr… | `mlops/models/whisper` |
|
||||
|
||||
## mlops/research
|
||||
|
||||
|
|
@ -193,37 +186,19 @@ ML research frameworks for building and optimizing AI systems with declarative p
|
|||
|
||||
## mlops/training
|
||||
|
||||
Fine-tuning, RLHF/DPO/GRPO training, distributed training frameworks, and optimization tools for training LLMs and other models.
|
||||
Fine-tuning, RLHF/DPO/GRPO training, distributed training frameworks, and optimization tools.
|
||||
|
||||
| Skill | Description | Path |
|
||||
|-------|-------------|------|
|
||||
| `axolotl` | Expert guidance for fine-tuning LLMs with Axolotl - YAML configs, 100+ models, LoRA/QLoRA, DPO/KTO/ORPO/GRPO, multimodal support | `mlops/training/axolotl` |
|
||||
| `distributed-llm-pretraining-torchtitan` | Provides PyTorch-native distributed LLM pretraining using torchtitan with 4D parallelism (FSDP2, TP, PP, CP). Use when pretraining Llama 3.1, DeepSeek V3, or custom models at scale from 8 to 512+ GPUs with Float8, torch.compile, and distributed checkpointing. | `mlops/training/torchtitan` |
|
||||
| `fine-tuning-with-trl` | Fine-tune LLMs using reinforcement learning with TRL - SFT for instruction tuning, DPO for preference alignment, PPO/GRPO for reward optimization, and reward model training. Use when need RLHF, align model with preferences, or train from human feedback. Works with HuggingFace Tr… | `mlops/training/trl-fine-tuning` |
|
||||
| `hermes-atropos-environments` | Build, test, and debug Hermes Agent RL environments for Atropos training. Covers the HermesAgentBaseEnv interface, reward functions, agent loop integration, evaluation with tools, wandb logging, and the three CLI modes (serve/process/evaluate). Use when creating, reviewing, or f… | `mlops/training/hermes-atropos-environments` |
|
||||
| `huggingface-accelerate` | Simplest distributed training API. 4 lines to add distributed support to any PyTorch script. Unified API for DeepSpeed/FSDP/Megatron/DDP. Automatic device placement, mixed precision (FP16/BF16/FP8). Interactive config, single launch command. HuggingFace ecosystem standard. | `mlops/training/accelerate` |
|
||||
| `optimizing-attention-flash` | Optimizes transformer attention with Flash Attention for 2-4x speedup and 10-20x memory reduction. Use when training/running transformers with long sequences (>512 tokens), encountering GPU memory issues with attention, or need faster inference. Supports PyTorch native SDPA,… | `mlops/training/flash-attention` |
|
||||
| `peft-fine-tuning` | 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 <1% of parameters with minimal accuracy loss, or for multi-adapter serving. HuggingFace's official library i… | `mlops/training/peft` |
|
||||
| `fine-tuning-with-trl` | Fine-tune LLMs using reinforcement learning with TRL - SFT for instruction tuning, DPO for preference alignment, PPO/GRPO for reward optimization, and reward model training. Use when need RLHF, align model with preferences, or train from human feedback. Works with HuggingFace … | `mlops/training/trl-fine-tuning` |
|
||||
| `peft-fine-tuning` | 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 <1% of parameters with minimal accuracy loss, or for multi-adapter serving. HuggingFace's official library… | `mlops/training/peft` |
|
||||
| `pytorch-fsdp` | Expert guidance for Fully Sharded Data Parallel training with PyTorch FSDP - parameter sharding, mixed precision, CPU offloading, FSDP2 | `mlops/training/pytorch-fsdp` |
|
||||
| `pytorch-lightning` | High-level PyTorch framework with Trainer class, automatic distributed training (DDP/FSDP/DeepSpeed), callbacks system, and minimal boilerplate. Scales from laptop to supercomputer with same code. Use when you want clean training loops with built-in best practices. | `mlops/training/pytorch-lightning` |
|
||||
| `simpo-training` | Simple Preference Optimization for LLM alignment. Reference-free alternative to DPO with better performance (+6.4 points on AlpacaEval 2.0). No reference model needed, more efficient than DPO. Use for preference alignment when want simpler, faster training than DPO/PPO. | `mlops/training/simpo` |
|
||||
| `slime-rl-training` | Provides guidance for LLM post-training with RL using slime, a Megatron+SGLang framework. Use when training GLM models, implementing custom data generation workflows, or needing tight Megatron-LM integration for RL scaling. | `mlops/training/slime` |
|
||||
| `unsloth` | Expert guidance for fast fine-tuning with Unsloth - 2-5x faster training, 50-80% less memory, LoRA/QLoRA optimization | `mlops/training/unsloth` |
|
||||
|
||||
## mlops/vector-databases
|
||||
|
||||
Vector similarity search and embedding databases for RAG, semantic search, and AI application backends.
|
||||
|
||||
| Skill | Description | Path |
|
||||
|-------|-------------|------|
|
||||
| `chroma` | Open-source embedding database for AI applications. Store embeddings and metadata, perform vector and full-text search, filter by metadata. Simple 4-function API. Scales from notebooks to production clusters. Use for semantic search, RAG applications, or document retrieval. Best… | `mlops/vector-databases/chroma` |
|
||||
| `faiss` | Facebook's library for efficient similarity search and clustering of dense vectors. Supports billions of vectors, GPU acceleration, and various index types (Flat, IVF, HNSW). Use for fast k-NN search, large-scale vector retrieval, or when you need pure similarity search without… | `mlops/vector-databases/faiss` |
|
||||
| `pinecone` | Managed vector database for production AI applications. Fully managed, auto-scaling, with hybrid search (dense + sparse), metadata filtering, and namespaces. Low latency (<100ms p95). Use for production RAG, recommendation systems, or semantic search at scale. Best for server… | `mlops/vector-databases/pinecone` |
|
||||
| `qdrant-vector-search` | High-performance vector similarity search engine for RAG and semantic search. Use when building production RAG systems requiring fast nearest neighbor search, hybrid search with filtering, or scalable vector storage with Rust-powered performance. | `mlops/vector-databases/qdrant` |
|
||||
|
||||
## note-taking
|
||||
|
||||
Note taking skills, to save information, assist with research, and collab on multi-session planning and information sharing.
|
||||
Note taking skills, to save information, assist with research, and collaborate on multi-session planning.
|
||||
|
||||
| Skill | Description | Path |
|
||||
|-------|-------------|------|
|
||||
|
|
@ -235,26 +210,12 @@ Skills for document creation, presentations, spreadsheets, and other productivit
|
|||
|
||||
| Skill | Description | Path |
|
||||
|-------|-------------|------|
|
||||
| `google-workspace` | Gmail, Calendar, Drive, Contacts, Sheets, and Docs integration via Python. Uses OAuth2 with automatic token refresh. No external binaries needed — runs entirely with Google's Python client libraries in the Hermes venv. | `productivity/google-workspace` |
|
||||
| `linear` | Manage Linear issues, projects, and teams via the GraphQL API. Create, update, search, and organize issues. | `productivity/linear` |
|
||||
| `google-workspace` | Gmail, Calendar, Drive, Contacts, Sheets, and Docs integration for Hermes. Uses Hermes-managed OAuth2 setup, prefers the Google Workspace CLI (`gws`) when available for broader API coverage, and falls back to the Python client libraries otherwise. | `productivity/google-workspace` |
|
||||
| `linear` | Manage Linear issues, projects, and teams via the GraphQL API. Create, update, search, and organize issues. Uses API key auth (no OAuth needed). All operations via curl — no dependencies. | `productivity/linear` |
|
||||
| `nano-pdf` | Edit PDFs with natural-language instructions using the nano-pdf CLI. Modify text, fix typos, update titles, and make content changes to specific pages without manual editing. | `productivity/nano-pdf` |
|
||||
| `notion` | Notion API for creating and managing pages, databases, and blocks via curl. Search, create, update, and query Notion workspaces directly from the terminal. | `productivity/notion` |
|
||||
| `ocr-and-documents` | Extract text from PDFs and scanned documents. Use web_extract for remote URLs, pymupdf for local text-based PDFs, marker-pdf for OCR/scanned docs. For DOCX use python-docx, for PPTX see the powerpoint skill. | `productivity/ocr-and-documents` |
|
||||
| `powerpoint` | "Use this skill any time a .pptx file is involved in any way — as input, output, or both. This includes: creating slide decks, pitch decks, or presentations; reading, parsing, or extracting text from any .pptx file (even if the extracted content will be used elsewhere, like in a… | `productivity/powerpoint` |
|
||||
|
||||
## research
|
||||
|
||||
Skills for academic research, paper discovery, literature review, domain reconnaissance, market data, content monitoring, and scientific knowledge retrieval.
|
||||
|
||||
| Skill | Description | Path |
|
||||
|-------|-------------|------|
|
||||
| `arxiv` | Search and retrieve academic papers from arXiv using their free REST API. No API key needed. Search by keyword, author, category, or ID. Combine with web_extract or the ocr-and-documents skill to read full paper content. | `research/arxiv` |
|
||||
| `blogwatcher` | Monitor blogs and RSS/Atom feeds for updates using the blogwatcher CLI. Add blogs, scan for new articles, and track what you've read. | `research/blogwatcher` |
|
||||
| `llm-wiki` | Karpathy's LLM Wiki — build and maintain a persistent, interlinked markdown knowledge base. Ingest sources, query compiled knowledge, and lint for consistency. Unlike RAG, the wiki compiles knowledge once and keeps it current. Works as an Obsidian vault. Wiki path is controlled by the `WIKI_PATH` env var (defaults to `~/wiki`). | `research/llm-wiki` |
|
||||
| `domain-intel` | Passive domain reconnaissance using Python stdlib. Subdomain discovery, SSL certificate inspection, WHOIS lookups, DNS records, domain availability checks, and bulk multi-domain analysis. No API keys required. | `research/domain-intel` |
|
||||
| `duckduckgo-search` | Free web search via DuckDuckGo — text, news, images, videos. No API key needed. Prefer the `ddgs` CLI when installed; use the Python DDGS library only after verifying that `ddgs` is available in the current runtime. | `research/duckduckgo-search` |
|
||||
| `ml-paper-writing` | Write publication-ready ML/AI papers for NeurIPS, ICML, ICLR, ACL, AAAI, COLM. Use when drafting papers from research repos, structuring arguments, verifying citations, or preparing camera-ready submissions. Includes LaTeX templates, reviewer guidelines, and citation verificatio… | `research/ml-paper-writing` |
|
||||
| `polymarket` | Query Polymarket prediction market data — search markets, get prices, orderbooks, and price history. Read-only via public REST APIs, no API key needed. | `research/polymarket` |
|
||||
| `powerpoint` | Use this skill any time a .pptx file is involved in any way — as input, output, or both. This includes: creating slide decks, pitch decks, or presentations; reading, parsing, or extracting text from any .pptx file (even if the extracted content will be used elsewhere, like in … | `productivity/powerpoint` |
|
||||
|
||||
## red-teaming
|
||||
|
||||
|
|
@ -262,7 +223,19 @@ Skills for LLM red-teaming, jailbreaking, and safety filter bypass research.
|
|||
|
||||
| Skill | Description | Path |
|
||||
|-------|-------------|------|
|
||||
| `godmode` | Jailbreak API-served LLMs using G0DM0D3 techniques — Parseltongue input obfuscation (33 techniques), GODMODE CLASSIC system prompt templates, ULTRAPLINIAN multi-model racing, encoding escalation, and Hermes-native prefill/system prompt integration. Works on any model accessible via API including closed-source models. | `red-teaming/godmode` |
|
||||
| `godmode` | Jailbreak API-served LLMs using G0DM0D3 techniques — Parseltongue input obfuscation (33 techniques), GODMODE CLASSIC system prompt templates, ULTRAPLINIAN multi-model racing, encoding escalation, and Hermes-native prefill/system prompt integration. Use when a user wants to byp… | `red-teaming/godmode` |
|
||||
|
||||
## research
|
||||
|
||||
Skills for academic research, paper discovery, literature review, market data, content monitoring, and scientific knowledge retrieval.
|
||||
|
||||
| Skill | Description | Path |
|
||||
|-------|-------------|------|
|
||||
| `arxiv` | Search and retrieve academic papers from arXiv using their free REST API. No API key needed. Search by keyword, author, category, or ID. Combine with web_extract or the ocr-and-documents skill to read full paper content. | `research/arxiv` |
|
||||
| `blogwatcher` | Monitor blogs and RSS/Atom feeds for updates using the blogwatcher-cli tool. Add blogs, scan for new articles, track read status, and filter by category. | `research/blogwatcher` |
|
||||
| `llm-wiki` | Karpathy's LLM Wiki — build and maintain a persistent, interlinked markdown knowledge base. Ingest sources, query compiled knowledge, and lint for consistency. | `research/llm-wiki` |
|
||||
| `polymarket` | Query Polymarket prediction market data — search markets, get prices, orderbooks, and price history. Read-only via public REST APIs, no API key needed. | `research/polymarket` |
|
||||
| `research-paper-writing` | End-to-end pipeline for writing ML/AI research papers — from experiment design through analysis, drafting, revision, and submission. Covers NeurIPS, ICML, ICLR, ACL, AAAI, COLM. Integrates automated experiment monitoring, statistical analysis, iterative writing, and citation v… | `research/research-paper-writing` |
|
||||
|
||||
## smart-home
|
||||
|
||||
|
|
@ -278,20 +251,22 @@ Skills for interacting with social platforms — posting, reading, monitoring, a
|
|||
|
||||
| Skill | Description | Path |
|
||||
|-------|-------------|------|
|
||||
| `xitter` | Interact with X/Twitter via the x-cli terminal client using official X API credentials. | `social-media/xitter` |
|
||||
| `xitter` | Interact with X/Twitter via the x-cli terminal client using official X API credentials. Use for posting, reading timelines, searching tweets, liking, retweeting, bookmarks, mentions, and user lookups. | `social-media/xitter` |
|
||||
|
||||
## software-development
|
||||
|
||||
General software-engineering skills — planning, reviewing, debugging, and test-driven development.
|
||||
|
||||
| Skill | Description | Path |
|
||||
|-------|-------------|------|
|
||||
| `code-review` | Guidelines for performing thorough code reviews with security and quality focus | `software-development/code-review` |
|
||||
| `plan` | Plan mode for Hermes — inspect context, write a markdown plan into `.hermes/plans/` in the active workspace/backend working directory, and do not execute the work. | `software-development/plan` |
|
||||
| `requesting-code-review` | Use when completing tasks, implementing major features, or before merging. Validates work meets requirements through systematic review process. | `software-development/requesting-code-review` |
|
||||
| `plan` | Plan mode for Hermes — inspect context, write a markdown plan into the active workspace's `.hermes/plans/` directory, and do not execute the work. | `software-development/plan` |
|
||||
| `requesting-code-review` | Pre-commit verification pipeline — static security scan, baseline-aware quality gates, independent reviewer subagent, and auto-fix loop. Use after code changes and before committing, pushing, or opening a PR. | `software-development/requesting-code-review` |
|
||||
| `subagent-driven-development` | Use when executing implementation plans with independent tasks. Dispatches fresh delegate_task per task with two-stage review (spec compliance then code quality). | `software-development/subagent-driven-development` |
|
||||
| `systematic-debugging` | Use when encountering any bug, test failure, or unexpected behavior. 4-phase root cause investigation — NO fixes without understanding the problem first. | `software-development/systematic-debugging` |
|
||||
| `test-driven-development` | Use when implementing any feature or bugfix, before writing implementation code. Enforces RED-GREEN-REFACTOR cycle with test-first approach. | `software-development/test-driven-development` |
|
||||
| `writing-plans` | Use when you have a spec or requirements for a multi-step task. Creates comprehensive implementation plans with bite-sized tasks, exact file paths, and complete code examples. | `software-development/writing-plans` |
|
||||
|
||||
|
||||
---
|
||||
|
||||
# Optional Skills
|
||||
|
|
|
|||
|
|
@ -35,7 +35,7 @@ Type `/` in the CLI to open the autocomplete menu. Built-in commands are case-in
|
|||
| `/queue <prompt>` (alias: `/q`) | Queue a prompt for the next turn (doesn't interrupt the current agent response). **Note:** `/q` is claimed by both `/queue` and `/quit`; the last registration wins, so `/q` resolves to `/quit` in practice. Use `/queue` explicitly. |
|
||||
| `/resume [name]` | Resume a previously-named session |
|
||||
| `/status` | Show session info |
|
||||
| `/snapshot` (alias: `/snap`) | Create or restore state snapshots of Hermes config/state (usage: /snapshot [create\|restore \<id\>\|prune]) |
|
||||
| `/agents` (alias: `/tasks`) | Show active agents and running tasks across the current session. |
|
||||
| `/background <prompt>` (alias: `/bg`) | Run a prompt in a separate background session. The agent processes your prompt independently — your current session stays free for other work. Results appear as a panel when the task finishes. See [CLI Background Sessions](/docs/user-guide/cli#background-sessions). |
|
||||
| `/btw <question>` | Ephemeral side question using session context (no tools, not persisted). Useful for quick clarifications without affecting the conversation history. |
|
||||
| `/plan [request]` | Load the bundled `plan` skill to write a markdown plan instead of executing the work. Plans are saved under `.hermes/plans/` relative to the active workspace/backend working directory. |
|
||||
|
|
@ -50,9 +50,8 @@ Type `/` in the CLI to open the autocomplete menu. Built-in commands are case-in
|
|||
| `/provider` | Show available providers and current provider |
|
||||
| `/personality` | Set a predefined personality |
|
||||
| `/verbose` | Cycle tool progress display: off → new → all → verbose. Can be [enabled for messaging](#notes) via config. |
|
||||
| `/fast` | Toggle fast mode — OpenAI Priority Processing / Anthropic Fast Mode (usage: /fast [normal\|fast\|status]) |
|
||||
| `/fast [normal\|fast\|status]` | Toggle fast mode — OpenAI Priority Processing / Anthropic Fast Mode. Options: `normal`, `fast`, `status`. |
|
||||
| `/reasoning` | Manage reasoning effort and display (usage: /reasoning [level\|show\|hide]) |
|
||||
| `/fast [normal\|fast\|status]` | Toggle fast mode — OpenAI Priority Processing / Anthropic Fast Mode. Options: `normal`, `fast`, `status`, `on`, `off`. |
|
||||
| `/skin` | Show or change the display skin/theme |
|
||||
| `/statusbar` (alias: `/sb`) | Toggle the context/model status bar on or off |
|
||||
| `/voice [on\|off\|tts\|status]` | Toggle CLI voice mode and spoken playback. Recording uses `voice.record_key` (default: `Ctrl+B`). |
|
||||
|
|
@ -80,6 +79,7 @@ Type `/` in the CLI to open the autocomplete menu. Built-in commands are case-in
|
|||
| `/insights` | Show usage insights and analytics (last 30 days) |
|
||||
| `/platforms` (alias: `/gateway`) | Show gateway/messaging platform status |
|
||||
| `/paste` | Check clipboard for an image and attach it |
|
||||
| `/copy [number]` | Copy the last assistant response to clipboard (or the Nth-from-last with a number). CLI-only. |
|
||||
| `/image <path>` | Attach a local image file for your next prompt. |
|
||||
| `/debug` | Upload debug report (system info + logs) and get shareable links. Also available in messaging. |
|
||||
| `/profile` | Show active profile name and home directory |
|
||||
|
|
@ -151,8 +151,6 @@ The messaging gateway supports the following built-in commands inside Telegram,
|
|||
| `/deny` | Reject a pending dangerous command. |
|
||||
| `/update` | Update Hermes Agent to the latest version. |
|
||||
| `/restart` | Gracefully restart the gateway after draining active runs. When the gateway comes back online, it sends a confirmation to the requester's chat/thread. |
|
||||
| `/fast [normal\|fast\|status]` | Toggle fast mode — OpenAI Priority Processing / Anthropic Fast Mode. |
|
||||
| `/debug` | Upload debug report (system info + logs) and get shareable links. |
|
||||
| `/debug` | Upload debug report (system info + logs) and get shareable links. |
|
||||
| `/help` | Show messaging help. |
|
||||
| `/<skill-name>` | Invoke any installed skill by name. |
|
||||
|
|
|
|||
|
|
@ -6,9 +6,9 @@ description: "Authoritative reference for Hermes built-in tools, grouped by tool
|
|||
|
||||
# Built-in Tools Reference
|
||||
|
||||
This page documents all 47 built-in tools in the Hermes tool registry, grouped by toolset. Availability varies by platform, credentials, and enabled toolsets.
|
||||
This page documents all 52 built-in tools in the Hermes tool registry, grouped by toolset. Availability varies by platform, credentials, and enabled toolsets.
|
||||
|
||||
**Quick counts:** 10 browser tools, 4 file tools, 10 RL tools, 4 Home Assistant tools, 2 terminal tools, 2 web tools, and 15 standalone tools across other toolsets.
|
||||
**Quick counts:** 10 browser tools, 4 file tools, 10 RL tools, 4 Home Assistant tools, 2 terminal tools, 2 web tools, 5 Feishu tools, and 15 standalone tools across other toolsets.
|
||||
|
||||
:::tip MCP Tools
|
||||
In addition to built-in tools, Hermes can load tools dynamically from MCP servers. MCP tools appear with a server-name prefix (e.g., `github_create_issue` for the `github` MCP server). See [MCP Integration](/docs/user-guide/features/mcp) for configuration.
|
||||
|
|
@ -53,6 +53,25 @@ In addition to built-in tools, Hermes can load tools dynamically from MCP server
|
|||
|------|-------------|----------------------|
|
||||
| `delegate_task` | Spawn one or more subagents to work on tasks in isolated contexts. Each subagent gets its own conversation, terminal session, and toolset. Only the final summary is returned -- intermediate tool results never enter your context window. TWO… | — |
|
||||
|
||||
## `feishu_doc` toolset
|
||||
|
||||
Scoped to the Feishu document-comment intelligent-reply handler (`gateway/platforms/feishu_comment.py`). Not exposed on `hermes-cli` or the regular Feishu chat adapter.
|
||||
|
||||
| Tool | Description | Requires environment |
|
||||
|------|-------------|----------------------|
|
||||
| `feishu_doc_read` | Read the full text content of a Feishu/Lark document (Docx, Doc, or Sheet) given its file_type and token. | Feishu app credentials |
|
||||
|
||||
## `feishu_drive` toolset
|
||||
|
||||
Scoped to the Feishu document-comment handler. Drives comment read/write operations on drive files.
|
||||
|
||||
| Tool | Description | Requires environment |
|
||||
|------|-------------|----------------------|
|
||||
| `feishu_drive_add_comment` | Add a top-level comment on a Feishu/Lark document or file. | Feishu app credentials |
|
||||
| `feishu_drive_list_comments` | List whole-document comments on a Feishu/Lark file, most recent first. | Feishu app credentials |
|
||||
| `feishu_drive_list_comment_replies` | List replies on a specific Feishu comment thread (whole-doc or local-selection). | Feishu app credentials |
|
||||
| `feishu_drive_reply_comment` | Post a reply on a Feishu comment thread, with optional `@`-mention. | Feishu app credentials |
|
||||
|
||||
## `file` toolset
|
||||
|
||||
| Tool | Description | Requires environment |
|
||||
|
|
|
|||
|
|
@ -57,6 +57,8 @@ Or in-session:
|
|||
| `code_execution` | `execute_code` | Run Python scripts that call Hermes tools programmatically. |
|
||||
| `cronjob` | `cronjob` | Schedule and manage recurring tasks. |
|
||||
| `delegation` | `delegate_task` | Spawn isolated subagent instances for parallel work. |
|
||||
| `feishu_doc` | `feishu_doc_read` | Read Feishu/Lark document content. Used by the Feishu document-comment intelligent-reply handler. |
|
||||
| `feishu_drive` | `feishu_drive_add_comment`, `feishu_drive_list_comments`, `feishu_drive_list_comment_replies`, `feishu_drive_reply_comment` | Feishu/Lark drive comment operations. Scoped to the comment agent; not exposed on `hermes-cli` or other messaging toolsets. |
|
||||
| `file` | `patch`, `read_file`, `search_files`, `write_file` | File reading, writing, searching, and editing. |
|
||||
| `homeassistant` | `ha_call_service`, `ha_get_state`, `ha_list_entities`, `ha_list_services` | Smart home control via Home Assistant. Only available when `HASS_TOKEN` is set. |
|
||||
| `image_gen` | `image_generate` | Text-to-image generation via FAL.ai. |
|
||||
|
|
@ -79,7 +81,7 @@ These expand to multiple core toolsets, providing a convenient shorthand for com
|
|||
|
||||
| Toolset | Expands to | Use case |
|
||||
|---------|-----------|----------|
|
||||
| `debugging` | `patch`, `process`, `read_file`, `search_files`, `terminal`, `web_extract`, `web_search`, `write_file` | Debug sessions — file access, terminal, and web research without browser or delegation overhead. |
|
||||
| `debugging` | `web` + `file` + `process`, `terminal` (via `includes`) — effectively `patch`, `process`, `read_file`, `search_files`, `terminal`, `web_extract`, `web_search`, `write_file` | Debug sessions — file access, terminal, and web research without browser or delegation overhead. |
|
||||
| `safe` | `image_generate`, `vision_analyze`, `web_extract`, `web_search` | Read-only research and media generation. No file writes, no terminal access, no code execution. Good for untrusted or constrained environments. |
|
||||
|
||||
## Platform Toolsets
|
||||
|
|
@ -88,7 +90,7 @@ Platform toolsets define the complete tool configuration for a deployment target
|
|||
|
||||
| Toolset | Differences from `hermes-cli` |
|
||||
|---------|-------------------------------|
|
||||
| `hermes-cli` | Full toolset — all 36 tools including `clarify`. The default for interactive CLI sessions. |
|
||||
| `hermes-cli` | Full toolset — all 36 core tools including `clarify`. The default for interactive CLI sessions. |
|
||||
| `hermes-acp` | Drops `clarify`, `cronjob`, `image_generate`, `send_message`, `text_to_speech`, homeassistant tools. Focused on coding tasks in IDE context. |
|
||||
| `hermes-api-server` | Drops `clarify`, `send_message`, and `text_to_speech`. Adds everything else — suitable for programmatic access where user interaction isn't possible. |
|
||||
| `hermes-telegram` | Same as `hermes-cli`. |
|
||||
|
|
@ -100,16 +102,16 @@ Platform toolsets define the complete tool configuration for a deployment target
|
|||
| `hermes-mattermost` | Same as `hermes-cli`. |
|
||||
| `hermes-email` | Same as `hermes-cli`. |
|
||||
| `hermes-sms` | Same as `hermes-cli`. |
|
||||
| `hermes-dingtalk` | Same as `hermes-cli`. |
|
||||
| `hermes-feishu` | Same as `hermes-cli`. |
|
||||
| `hermes-wecom` | Same as `hermes-cli`. |
|
||||
| `hermes-wecom-callback` | WeCom callback toolset — enterprise self-built app messaging (full access). |
|
||||
| `hermes-weixin` | Same as `hermes-cli`. |
|
||||
| `hermes-bluebubbles` | Same as `hermes-cli`. |
|
||||
| `hermes-dingtalk` | Same as `hermes-cli`. |
|
||||
| `hermes-feishu` | Same as `hermes-cli`. Note: the `feishu_doc` / `feishu_drive` toolsets are used only by the document-comment handler, not by the regular Feishu chat adapter. |
|
||||
| `hermes-qqbot` | Same as `hermes-cli`. |
|
||||
| `hermes-homeassistant` | Same as `hermes-cli`. |
|
||||
| `hermes-wecom` | Same as `hermes-cli`. |
|
||||
| `hermes-wecom-callback` | Same as `hermes-cli`. |
|
||||
| `hermes-weixin` | Same as `hermes-cli`. |
|
||||
| `hermes-homeassistant` | Same as `hermes-cli` plus the `homeassistant` toolset always on. |
|
||||
| `hermes-webhook` | Same as `hermes-cli`. |
|
||||
| `hermes-gateway` | Union of all messaging platform toolsets. Used internally when the gateway needs the broadest possible tool set. |
|
||||
| `hermes-gateway` | Internal gateway orchestrator toolset — union of the broadest possible tool set when the gateway needs to accept any message source. |
|
||||
|
||||
## Dynamic Toolsets
|
||||
|
||||
|
|
@ -119,11 +121,10 @@ Each configured MCP server generates a `mcp-<server>` toolset at runtime. For ex
|
|||
|
||||
```yaml
|
||||
# config.yaml
|
||||
mcp:
|
||||
servers:
|
||||
github:
|
||||
command: npx
|
||||
args: ["-y", "@modelcontextprotocol/server-github"]
|
||||
mcp_servers:
|
||||
github:
|
||||
command: npx
|
||||
args: ["-y", "@modelcontextprotocol/server-github"]
|
||||
```
|
||||
|
||||
This creates a `mcp-github` toolset you can reference in `--toolsets` or platform configs.
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue