A high-performance CLI tool for deep GitHub repository exploration, multi-dimensional filtering, and automated technical trend analysis.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install github-search
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-search 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 Research?
GitHub Research is a specialized utility designed for deep-dive technical investigations and ecosystem monitoring. It empowers developers and researchers to navigate the massive GitHub landscape with precision, allowing for granular filtering by keywords, programming languages, star counts, and recent activity.
This tool is specifically engineered to identify emerging open-source trends and high-impact projects, providing a structured way to gather intelligence. As a core component of your technical toolkit, it enhances the efficiency of competitive analysis and technology selection within the Openclaw Skills ecosystem.
GitHub Research Use Cases
- Identifying niche open-source projects for specific technical research.
- Benchmarking libraries by comparing star growth, forks, and commit frequency.
- Tracking emerging trends in fields like AI agents, RAG, and vector databases.
- Automating the collection of project metadata for technical documentation or reports.
- Monitoring ecosystem activity through filtered repository scans and batch analysis.
How GitHub Research Works
- The user provides a search query and optional parameters like --language or --min-stars via the command line.
- The skill connects to the GitHub Search API v3 and REST API to fetch relevant repository metadata.
- The system processes the raw API data to calculate statistical summaries, such as average stars and language distribution.
- Structured output is generated in the user's preferred format (Markdown Table, JSON, or CSV).
- For deeper insights, users can trigger secondary scripts to fetch detailed repository profiles, including contributor activity and code metrics.
GitHub Research Setup
To get started with this skill, ensure you have Node.js installed and follow these steps:
# Basic search for repositories
node scripts/github-search.mjs "agent memory"
# Filter by language and star count
node scripts/github-search.mjs "rag" --language python --min-stars 1000
# (Optional) Configure GitHub Token for higher rate limits
export GITHUB_TOKEN="ghp_your_token_here"
GitHub Research Data Schema & Taxonomy
The skill organizes repository data into structured formats. Below is the primary schema used for search results:
| Field | Description | Example |
|---|---|---|
| Project | The owner and repository name | microsoft/autogen |
| Stars | Total number of stars | 32.5k |
| Forks | Total number of forks | 4.8k |
| Language | Primary programming language | Python |
| Updated | Time since the last commit | 2 days ago |
| Link | Direct URL to the repository | View |
Statistical summaries include project counts, average star metrics, and percentage-based language breakdowns.
GitHub Research Advanced Features
- Multi-dimensional filtering across stars, forks, languages, and specific timeframes.
- Batch processing capabilities to extract detailed metadata for multiple repositories simultaneously.
- Native support for structured data export (JSON/CSV) for integration with other Openclaw Skills.
- Automated trend analysis to identify active vs. stale projects.
- Seamless integration with multi-agent workflows for autonomous technical intelligence gathering.
SKILL.md
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