Files
hermes-agent/website/docs/developer-guide/creating-skills.md
Teknium 150f70f821 feat(skills): add skill config interface + llm-wiki skill (#5635)
Skills can now declare config.yaml settings via metadata.hermes.config
in their SKILL.md frontmatter. Values are stored under skills.config.*
namespace, prompted during hermes config migrate, shown in hermes config
show, and injected into the skill context at load time.

Also adds the llm-wiki skill (Karpathy's LLM Wiki pattern) as the first
skill to use the new config interface, declaring wiki.path.

Skill config interface (new):
- agent/skill_utils.py: extract_skill_config_vars(), discover_all_skill_config_vars(),
  resolve_skill_config_values(), SKILL_CONFIG_PREFIX
- agent/skill_commands.py: _inject_skill_config() injects resolved values
  into skill messages as [Skill config: ...] block
- hermes_cli/config.py: get_missing_skill_config_vars(), skill config
  prompting in migrate_config(), Skill Settings in show_config()

LLM Wiki skill (skills/research/llm-wiki/SKILL.md):
- Three-layer architecture (raw sources, wiki pages, schema)
- Three operations (ingest, query, lint)
- Session orientation, page thresholds, tag taxonomy, update policy,
  scaling guidance, log rotation, archiving workflow

Docs: creating-skills.md, configuration.md, skills.md, skills-catalog.md

Closes #5100
2026-04-06 13:49:13 -07:00

333 lines
13 KiB
Markdown

---
sidebar_position: 3
title: "Creating Skills"
description: "How to create skills for Hermes Agent — SKILL.md format, guidelines, and publishing"
---
# Creating Skills
Skills are the preferred way to add new capabilities to Hermes Agent. They're easier to create than tools, require no code changes to the agent, and can be shared with the community.
## Should it be a Skill or a Tool?
Make it a **Skill** when:
- The capability can be expressed as instructions + shell commands + existing tools
- It wraps an external CLI or API that the agent can call via `terminal` or `web_extract`
- It doesn't need custom Python integration or API key management baked into the agent
- Examples: arXiv search, git workflows, Docker management, PDF processing, email via CLI tools
Make it a **Tool** when:
- It requires end-to-end integration with API keys, auth flows, or multi-component configuration
- It needs custom processing logic that must execute precisely every time
- It handles binary data, streaming, or real-time events
- Examples: browser automation, TTS, vision analysis
## Skill Directory Structure
Bundled skills live in `skills/` organized by category. Official optional skills use the same structure in `optional-skills/`:
```text
skills/
├── research/
│ └── arxiv/
│ ├── SKILL.md # Required: main instructions
│ └── scripts/ # Optional: helper scripts
│ └── search_arxiv.py
├── productivity/
│ └── ocr-and-documents/
│ ├── SKILL.md
│ ├── scripts/
│ └── references/
└── ...
```
## SKILL.md Format
```markdown
---
name: my-skill
description: Brief description (shown in skill search results)
version: 1.0.0
author: Your Name
license: MIT
platforms: [macos, linux] # Optional — restrict to specific OS platforms
# Valid: macos, linux, windows
# Omit to load on all platforms (default)
metadata:
hermes:
tags: [Category, Subcategory, Keywords]
related_skills: [other-skill-name]
requires_toolsets: [web] # Optional — only show when these toolsets are active
requires_tools: [web_search] # Optional — only show when these tools are available
fallback_for_toolsets: [browser] # Optional — hide when these toolsets are active
fallback_for_tools: [browser_navigate] # Optional — hide when these tools exist
config: # Optional — config.yaml settings the skill needs
- key: my.setting
description: "What this setting controls"
default: "sensible-default"
prompt: "Display prompt for setup"
required_environment_variables: # Optional — env vars the skill needs
- name: MY_API_KEY
prompt: "Enter your API key"
help: "Get one at https://example.com"
required_for: "API access"
---
# Skill Title
Brief intro.
## When to Use
Trigger conditions — when should the agent load this skill?
## Quick Reference
Table of common commands or API calls.
## Procedure
Step-by-step instructions the agent follows.
## Pitfalls
Known failure modes and how to handle them.
## Verification
How the agent confirms it worked.
```
### Platform-Specific Skills
Skills can restrict themselves to specific operating systems using the `platforms` field:
```yaml
platforms: [macos] # macOS only (e.g., iMessage, Apple Reminders)
platforms: [macos, linux] # macOS and Linux
platforms: [windows] # Windows only
```
When set, the skill is automatically hidden from the system prompt, `skills_list()`, and slash commands on incompatible platforms. If omitted or empty, the skill loads on all platforms (backward compatible).
### Conditional Skill Activation
Skills can declare dependencies on specific tools or toolsets. This controls whether the skill appears in the system prompt for a given session.
```yaml
metadata:
hermes:
requires_toolsets: [web] # Hide if the web toolset is NOT active
requires_tools: [web_search] # Hide if web_search tool is NOT available
fallback_for_toolsets: [browser] # Hide if the browser toolset IS active
fallback_for_tools: [browser_navigate] # Hide if browser_navigate IS available
```
| Field | Behavior |
|-------|----------|
| `requires_toolsets` | Skill is **hidden** when ANY listed toolset is **not** available |
| `requires_tools` | Skill is **hidden** when ANY listed tool is **not** available |
| `fallback_for_toolsets` | Skill is **hidden** when ANY listed toolset **is** available |
| `fallback_for_tools` | Skill is **hidden** when ANY listed tool **is** available |
**Use case for `fallback_for_*`:** Create a skill that serves as a workaround when a primary tool isn't available. For example, a `duckduckgo-search` skill with `fallback_for_tools: [web_search]` only shows when the web search tool (which requires an API key) is not configured.
**Use case for `requires_*`:** Create a skill that only makes sense when certain tools are present. For example, a web scraping workflow skill with `requires_toolsets: [web]` won't clutter the prompt when web tools are disabled.
### Environment Variable Requirements
Skills can declare environment variables they need. When a skill is loaded via `skill_view`, its required vars are automatically registered for passthrough into sandboxed execution environments (terminal, execute_code).
```yaml
required_environment_variables:
- name: TENOR_API_KEY
prompt: "Tenor API key" # Shown when prompting user
help: "Get your key at https://tenor.com" # Help text or URL
required_for: "GIF search functionality" # What needs this var
```
Each entry supports:
- `name` (required) — the environment variable name
- `prompt` (optional) — prompt text when asking the user for the value
- `help` (optional) — help text or URL for obtaining the value
- `required_for` (optional) — describes which feature needs this variable
Users can also manually configure passthrough variables in `config.yaml`:
```yaml
terminal:
env_passthrough:
- MY_CUSTOM_VAR
- ANOTHER_VAR
```
See `skills/apple/` for examples of macOS-only skills.
## Secure Setup on Load
Use `required_environment_variables` when a skill needs an API key or token. Missing values do **not** hide the skill from discovery. Instead, Hermes prompts for them securely when the skill is loaded in the local CLI.
```yaml
required_environment_variables:
- name: TENOR_API_KEY
prompt: Tenor API key
help: Get a key from https://developers.google.com/tenor
required_for: full functionality
```
The user can skip setup and keep loading the skill. Hermes never exposes the raw secret value to the model. Gateway and messaging sessions show local setup guidance instead of collecting secrets in-band.
:::tip Sandbox Passthrough
When your skill is loaded, any declared `required_environment_variables` that are set are **automatically passed through** to `execute_code` and `terminal` sandboxes — including remote backends like Docker and Modal. Your skill's scripts can access `$TENOR_API_KEY` (or `os.environ["TENOR_API_KEY"]` in Python) without the user needing to configure anything extra. See [Environment Variable Passthrough](/docs/user-guide/security#environment-variable-passthrough) for details.
:::
Legacy `prerequisites.env_vars` remains supported as a backward-compatible alias.
### Config Settings (config.yaml)
Skills can declare non-secret settings that are stored in `config.yaml` under the `skills.config` namespace. Unlike environment variables (which are secrets stored in `.env`), config settings are for paths, preferences, and other non-sensitive values.
```yaml
metadata:
hermes:
config:
- key: wiki.path
description: Path to the LLM Wiki knowledge base directory
default: "~/wiki"
prompt: Wiki directory path
- key: wiki.domain
description: Domain the wiki covers
default: ""
prompt: Wiki domain (e.g., AI/ML research)
```
Each entry supports:
- `key` (required) — dotpath for the setting (e.g., `wiki.path`)
- `description` (required) — explains what the setting controls
- `default` (optional) — default value if the user doesn't configure it
- `prompt` (optional) — prompt text shown during `hermes config migrate`; falls back to `description`
**How it works:**
1. **Storage:** Values are written to `config.yaml` under `skills.config.<key>`:
```yaml
skills:
config:
wiki:
path: ~/my-research
```
2. **Discovery:** `hermes config migrate` scans all enabled skills, finds unconfigured settings, and prompts the user. Settings also appear in `hermes config show` under "Skill Settings."
3. **Runtime injection:** When a skill loads, its config values are resolved and appended to the skill message:
```
[Skill config (from ~/.hermes/config.yaml):
wiki.path = /home/user/my-research
]
```
The agent sees the configured values without needing to read `config.yaml` itself.
4. **Manual setup:** Users can also set values directly:
```bash
hermes config set skills.config.wiki.path ~/my-wiki
```
:::tip When to use which
Use `required_environment_variables` for API keys, tokens, and other **secrets** (stored in `~/.hermes/.env`, never shown to the model). Use `config` for **paths, preferences, and non-sensitive settings** (stored in `config.yaml`, visible in config show).
:::
### Credential File Requirements (OAuth tokens, etc.)
Skills that use OAuth or file-based credentials can declare files that need to be mounted into remote sandboxes. This is for credentials stored as **files** (not env vars) — typically OAuth token files produced by a setup script.
```yaml
required_credential_files:
- path: google_token.json
description: Google OAuth2 token (created by setup script)
- path: google_client_secret.json
description: Google OAuth2 client credentials
```
Each entry supports:
- `path` (required) — file path relative to `~/.hermes/`
- `description` (optional) — explains what the file is and how it's created
When loaded, Hermes checks if these files exist. Missing files trigger `setup_needed`. Existing files are automatically:
- **Mounted into Docker** containers as read-only bind mounts
- **Synced into Modal** sandboxes (at creation + before each command, so mid-session OAuth works)
- Available on **local** backend without any special handling
:::tip When to use which
Use `required_environment_variables` for simple API keys and tokens (strings stored in `~/.hermes/.env`). Use `required_credential_files` for OAuth token files, client secrets, service account JSON, certificates, or any credential that's a file on disk.
:::
See the `skills/productivity/google-workspace/SKILL.md` for a complete example using both.
## Skill Guidelines
### No External Dependencies
Prefer stdlib Python, curl, and existing Hermes tools (`web_extract`, `terminal`, `read_file`). If a dependency is needed, document installation steps in the skill.
### Progressive Disclosure
Put the most common workflow first. Edge cases and advanced usage go at the bottom. This keeps token usage low for common tasks.
### Include Helper Scripts
For XML/JSON parsing or complex logic, include helper scripts in `scripts/` — don't expect the LLM to write parsers inline every time.
### Test It
Run the skill and verify the agent follows the instructions correctly:
```bash
hermes chat --toolsets skills -q "Use the X skill to do Y"
```
## Where Should the Skill Live?
Bundled skills (in `skills/`) ship with every Hermes install. They should be **broadly useful to most users**:
- Document handling, web research, common dev workflows, system administration
- Used regularly by a wide range of people
If your skill is official and useful but not universally needed (e.g., a paid service integration, a heavyweight dependency), put it in **`optional-skills/`** — it ships with the repo, is discoverable via `hermes skills browse` (labeled "official"), and installs with builtin trust.
If your skill is specialized, community-contributed, or niche, it's better suited for a **Skills Hub** — upload it to a registry and share it via `hermes skills install`.
## Publishing Skills
### To the Skills Hub
```bash
hermes skills publish skills/my-skill --to github --repo owner/repo
```
### To a Custom Repository
Add your repo as a tap:
```bash
hermes skills tap add owner/repo
```
Users can then search and install from your repository.
## Security Scanning
All hub-installed skills go through a security scanner that checks for:
- Data exfiltration patterns
- Prompt injection attempts
- Destructive commands
- Shell injection
Trust levels:
- `builtin` — ships with Hermes (always trusted)
- `official` — from `optional-skills/` in the repo (builtin trust, no third-party warning)
- `trusted` — from openai/skills, anthropics/skills
- `community` — non-dangerous findings can be overridden with `--force`; `dangerous` verdicts remain blocked
Hermes can now consume third-party skills from multiple external discovery models:
- direct GitHub identifiers (for example `openai/skills/k8s`)
- `skills.sh` identifiers (for example `skills-sh/vercel-labs/json-render/json-render-react`)
- well-known endpoints served from `/.well-known/skills/index.json`
If you want your skills to be discoverable without a GitHub-specific installer, consider serving them from a well-known endpoint in addition to publishing them in a repo or marketplace.