github-to-skills

Automated factory for converting GitHub repositories into specialized AI skills. Use this skill when the user provides a GitHub URL and wants to "package", "wrap", or "create a skill" from it. It automatically fetches repository details, latest commit hashes, and generates a standardized skill structure with enhanced metadata suitable for lifecycle management.

Safety Notice

This listing is imported from skills.sh public index metadata. Review upstream SKILL.md and repository scripts before running.

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Install skill "github-to-skills" with this command: npx skills add kkkkhazix/khazix-skills/kkkkhazix-khazix-skills-github-to-skills

GitHub to Skills Factory

This skill automates the conversion of GitHub repositories into fully functional AI skills.

Core Functionality

  1. Analysis: Fetches repository metadata (Description, README, Latest Commit Hash).
  2. Scaffolding: Creates a standardized skill directory structure.
  3. Metadata Injection: Generates SKILL.md with extended frontmatter (tracking source, version, hash) for future automated management.
  4. Wrapper Generation: Creates a scripts/wrapper.py (or similar) to interface with the tool.

Usage

Trigger: /GitHub-to-skills <github_url> or "Package this repo into a skill: <url>"

Required Metadata Schema

Every skill created by this factory MUST include the following extended YAML frontmatter in its SKILL.md. This is critical for the skill-manager to function later.

---
name: <kebab-case-repo-name>
description: <concise-description-for-agent-triggering>
# EXTENDED METADATA (MANDATORY)
github_url: <original-repo-url>
github_hash: <latest-commit-hash-at-time-of-creation>
version: <tag-or-0.1.0>
created_at: <ISO-8601-date>
entry_point: scripts/wrapper.py # or main script
dependencies: # List main dependencies if known, e.g., ["yt-dlp", "ffmpeg"]
---

Workflow

  1. Fetch Info: The agent first runs scripts/fetch_github_info.py to get the raw data from the repo.
  2. Plan: The agent analyzes the README to understand how to invoke the tool (CLI args, Python API, etc.).
  3. Generate: The agent uses the skill-creator patterns to write the SKILL.md and wrapper scripts, ensuring the extended metadata is present.
  4. Verify: Checks if the commit hash was correctly captured.

Resources

  • scripts/fetch_github_info.py: Utility to scrape/API fetch repo details (README, Hash, Tags).
  • scripts/create_github_skill.py: Orchestrator to scaffold the folder and write the initial files.

Best Practices for Generated Skills

  • Isolation: The generated skill should install its own dependencies (e.g., in a venv or via uv/pip) if possible, or clearly state them.
  • Progressive Disclosure: Do not dump the entire repo into the skill. Only include the necessary wrapper code and reference the original repo for deep dives.
  • Idempotency: The github_hash field allows the future skill-manager to check if remote_hash != local_hash to trigger updates.

Source Transparency

This detail page is rendered from real SKILL.md content. Trust labels are metadata-based hints, not a safety guarantee.

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