A zero-dependency Python toolkit that transforms complex GitHub repositories into AI-friendly markdown documents and visual architecture diagrams.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install github-intel
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install github-intel using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is GitHub Intelligence?
GitHub Intelligence is a specialized utility designed to bridge the gap between raw source code and AI understanding. It allows developers and AI agents to ingest entire repositories by converting them into structured, single-document markdown files. By focusing on static analysis and metadata extraction, it provides a comprehensive overview of any codebase without the need for complex local environments or code execution.
As part of the broader ecosystem of Openclaw Skills, this tool prioritizes security and efficiency. It uses the Python standard library exclusively, ensuring it can run in restricted environments while providing deep insights into repository structure, language distribution, and recent activity. Whether you are performing an open-source research task or preparing a codebase for an LLM audit, this skill simplifies the discovery process.
GitHub Intelligence Use Cases
- Converting a full GitHub repository into a single markdown file for LLM context windows.
- Generating Mermaid architecture diagrams to visualize system design and file relationships.
- Performing rapid codebase audits to understand language breakdowns and recent commit history.
- Researching open-source projects using advanced GitHub URL tricks and API shortcuts available in Openclaw Skills.
- Onboarding AI coding agents to new repositories by providing a structured file tree and README summary.
How GitHub Intelligence Works
- The user provides a public GitHub repository URL to the analyzer or markdown converter script.
- The skill communicates with the GitHub REST API to fetch the repository's file tree and metadata.
- Content is parsed and filtered based on user-defined constraints like directory depth and maximum file count.
- Architecture patterns are identified to generate valid Mermaid flowchart syntax.
- The final output is consolidated into a structured report or a markdown document optimized for AI ingestion.
GitHub Intelligence Setup
GitHub Intelligence requires Python 3.10+ and operates using the standard library. While it works without authentication, providing a token significantly increases your API rate limits. This is a standalone component within the Openclaw Skills library.
# Set your python path
PY=~/.openclaw/workspace/.venv/bin/python3
# Analyze a repository structure and generate diagrams
$PY skills/github-intel/scripts/repo_analyzer.py https://github.com/owner/repo
# Convert a repository to a single markdown file for AI agents
$PY skills/github-intel/scripts/repo_to_markdown.py https://github.com/owner/repo > codebase.md
# (Optional) Increase rate limits with a GitHub token
export GITHUB_TOKEN=your_token_here
GitHub Intelligence Data Schema & Taxonomy
The skill produces structured analysis reports and consolidated markdown files. It follows a predictable taxonomy to ensure Openclaw Skills can easily parse the results.
| Component | Description | Output Type |
|---|---|---|
| File Tree | A visual ASCII representation of the repository hierarchy. | Text/Markdown |
| Language Breakdown | Percentage-based distribution of programming languages. | List |
| Mermaid Diagram | Logic and architecture flowcharts derived from structure. | Mermaid.js Code |
| Activity Stream | A summary of recent commits, contributors, and releases. | Markdown |
| Full Context | A concatenation of all relevant source files. | Consolidated Markdown |
GitHub Intelligence Advanced Features
- Configurable recursion depth for directory traversal to handle massive repositories.
- File count capping to prevent token overflow during AI analysis.
- Read-only execution guarantee, ensuring no code from the analyzed repository is ever executed.
- Deep integration with GitHub search operators and hidden API shortcuts.
- Support for GITHUB_TOKEN environment variables to scale from 60 to 5,000 requests per hour.
SKILL.md
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