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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/:

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​

---
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:

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.

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
FieldBehavior
requires_toolsetsSkill is hidden when ANY listed toolset is not available
requires_toolsSkill is hidden when ANY listed tool is not available
fallback_for_toolsetsSkill is hidden when ANY listed toolset is available
fallback_for_toolsSkill 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).

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:

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.

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.

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 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.

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>:

    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:

    hermes config set skills.config.wiki.path ~/my-wiki
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.

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
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:

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​

hermes skills publish skills/my-skill --to github --repo owner/repo

To a Custom Repository​

Add your repo as a tap:

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.