github-to-skills

name	github-to-skills
description	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.
license	MIT

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: "

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.

Skill Synergy Examples

Integration with skill-manager

# After creating a skill, register it with skill-manager
python github-to-skills/scripts/fetch_github_info.py https://github.com/username/repo.git
python skill-manager/scripts/scan_and_check.py .

Integration with skill-creator

# Use skill-creator patterns for standardization
python skill-creator/scripts/init_skill.py new-skill --path .
# Then enhance with github-to-skills metadata

Complete workflow example

# 1. Create skill from GitHub
python github-to-skills/scripts/fetch_github_info.py https://github.com/username/tool.git

# 2. Standardize with skill-creator
python skill-creator/scripts/init_skill.py tool-wrapper --path .

# 3. Register with skill-manager
python skill-manager/scripts/scan_and_check.py .

# 4. Update documentation
python update-readme/scripts/analyze_project.py .

使用示例

示例1：将GitHub工具转换为技能

# 获取GitHub仓库信息
python scripts/fetch_github_info.py https://github.com/yt-dlp/yt-dlp.git

# 输出示例：
# {
#   "name": "yt-dlp",
#   "url": "https://github.com/yt-dlp/yt-dlp.git",
#   "latest_hash": "abc123def456",
#   "readme": "# yt-dlp - A youtube-dl fork with additional features..."
# }

# 基于获取的信息创建技能目录结构
mkdir yt-dlp-skill
# 创建SKILL.md包含必要的元数据

示例2：创建Python库的技能包装器

# 获取Python库信息
python scripts/fetch_github_info.py https://github.com/psf/requests.git

# 创建技能包装器，包含：
# 1. SKILL.md - 技能描述和元数据
# 2. scripts/wrapper.py - 调用requests库的包装器
# 3. references/ - API文档和示例
# 4. assets/ - 示例请求模板

示例3：创建CLI工具的技能包装器

# 获取CLI工具信息
python scripts/fetch_github_info.py https://github.com/BurntSushi/ripgrep.git

# 创建技能包装器，包含：
# 1. SKILL.md - 技能描述和安装说明
# 2. scripts/wrapper.py - 封装rg命令的Python脚本
# 3. references/ - 模式示例和用例
# 4. assets/ - 常用搜索模式模板

示例4：验证技能创建结果

# 验证创建的技能结构
python skill-creator/scripts/quick_validate.py yt-dlp-skill

# 检查元数据完整性
grep -E "github_url|github_hash" yt-dlp-skill/SKILL.md

# 注册到技能管理器
python skill-manager/scripts/scan_and_check.py .

Overview

This skill is used when its description in frontmatter matches the user request. Prefer existing scripts under scripts/ over ad-hoc rewrites.

References

• scripts/: executable helpers for deterministic steps
• references/: additional docs loaded on demand
• assets/: templates or static files used by the skill

Trigger Conditions

• User explicitly names this skill
• User intent clearly matches this skill description
• The task needs this skill's scripts/resources

Applicable Scope

• Requests covered by this skill's frontmatter description
• Tasks that benefit from the bundled workflow and scripts

Out of Scope

• Requests that conflict with repository safety rules
• Tasks unrelated to this skill's declared purpose
• Destructive changes without explicit user permission