Requesting a New Skill

We use a curated contribution model: community members request new skills via GitHub Issues, and maintainers build them.

Process

  1. Open an Issue using the New Skill Request template
  2. Fill in the details: repository URL, documentation paths, when-to-use triggers
  3. A maintainer reviews the request and clones the source repo to understand the tool
  4. The skill is built based on actual repository content (no assumptions)
  5. A PR is opened for review, and the skill is added to the installer

What Makes a Good Skill Request

  • Clear source repository — the Git URL and branch
  • Identified documentation — which files in the repo should be fetched
  • Use-case description — when should the AI assistant activate this skill?
  • Example interactions — what questions would a user ask?

Skill Structure

Each skill consists of:

skills/<name>/
  config.sh           # Repository URL, branch, doc paths
  SKILL.md            # Agent skill definition (YAML frontmatter + Markdown)
  references/
    REFERENCE.md      # Index of available documentation
  rules/
    <name>.mdc        # Optional Cursor-specific rules

Validation Checklist

Before a skill is merged, maintainers verify:

  • Source repository is accessible and public
  • Documentation paths exist in the repo
  • SKILL.md accurately describes the tool based on actual repo content
  • “When to Use” triggers are specific and useful
  • config.sh values are correct
  • Tests pass on RHEL and macOS