Github Skill Research

GitHub Skill Research

Research reusable AI-agent skill patterns from real repositories and primary documentation.

Workflow

1. Define the research target

   • Identify whether the user wants structure, trigger logic, workflow design, operating rules, examples, portability, or repository organization.
   • If the target is unclear, make a narrow useful assumption and state it.

2. Search sources

   • Prioritize real repositories with SKILL.md, AGENTS.md, CLAUDE.md, prompt libraries, workflow playbooks, or MCP/tooling examples.
   • Prefer official documentation and maintained repositories over generic blog advice.
   • Include thananon/9arm-skills as a useful comparison point when evaluating concise skill structure.
   • See research-methodology for tiering sources (repo itself vs. a blog post about the repo) and tracking which candidates were actually checked vs. skipped.

3. Analyze examples

   • Extract frontmatter style, trigger descriptions, workflow steps, output formats, safety rules, bundled resources, and repo layout.
   • Identify whether each pattern is portable across agents or tied to one tool.

4. Compare against the user's repo

   • Mark patterns to copy, adapt, skip, or keep private.
   • Call out duplication, overbroad skills, stale instructions, and missing validation.

5. Produce recommendations

   • Respond in the user's language.
   • Include links or local file paths.
   • Keep templates short enough to install or edit immediately.

Output Format

# AI Agent Skill Research

## Summary

## Useful Sources

## Patterns To Copy

## Patterns To Adapt

## Anti-patterns To Avoid

## Suggested Skill Template

## Action Items

Rules

• Do not summarize sources without links or file paths.
• Do not copy a skill verbatim unless the user asks.
• Keep trigger logic in YAML description.
• Prefer workflows with verification over advice-only prompts.