hermes-agent/website/docs/developer-guide/creating-skills.md

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3	Creating Skills	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/:

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]
---

# 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).

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.

:::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. 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.

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.