Skill Name

Overview

A short description of what this skill does.

Example:

This skill allows the agent to search GitHub repositories, fetch code snippets, and summarize project structures.

---

Metadata

name: github-integration
version: 1.0.0
category: developer-tools
description: GitHub integration skill for repositories and code analysis
author: Your Name
license: MIT

---

Purpose

Explain:

• Why this skill exists
• What problem it solves
• Which workflows it supports

Example:

• Repository analysis
• Pull request summaries
• File search
• Commit history lookup

---

Capabilities

List the major capabilities of the skill.

Features

• Search repositories
• Read repository files
• Fetch pull requests
• Analyze commits
• Generate summaries
• Semantic search support

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Inputs

Describe what input the skill expects.

Input Name	Type	Required	Description
repository	string	Yes	GitHub repository name
branch	string	No	Branch name
query	string	No	Search query

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Outputs

Describe the response structure.

Field	Type	Description
summary	string	Generated summary
files	array	Matching files
commits	array	Commit information

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Environment Variables

GITHUB_TOKEN=your_token_here
API_BASE_URL=https://api.github.com

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Installation

Clone Repository

git clone https://github.com/example/skill.git
cd skill

Install Dependencies

npm install

---

Usage

Example Request

{
  "repository": "openai/openai-python",
  "query": "embedding implementation"
}

Example Response

{
  "summary": "Found embedding-related files and utilities.",
  "files": [
    "embeddings.py",
    "vector_store.py"
  ]
}

---

Architecture

Explain how the skill works internally.

Example Flow:

User Request
    ↓
Skill Router
    ↓
Authentication Layer
    ↓
GitHub API Client
    ↓
Processing Layer
    ↓
Formatted Response

---

Error Handling

Common errors and solutions.

Error	Cause	Solution
Unauthorized	Invalid token	Update API token
Rate Limited	Too many requests	Retry later
Repository Not Found	Wrong repo name	Verify repository

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Security

Describe security considerations.

• Store tokens securely
• Never expose secrets in logs
• Use HTTPS requests only
• Apply permission checks

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Best Practices

• Cache frequent API responses
• Use pagination for large repositories
• Validate user inputs
• Handle API rate limits

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Dependencies

{
  "axios": "^1.0.0",
  "dotenv": "^16.0.0"
}

---

Future Improvements

• Add vector search
• Add webhook support
• Add multi-repository analysis
• Improve semantic ranking

---

Maintainers

Name	Role
Your Name	Developer

---

License

MIT License