A zero-dependency Python tool to fetch and analyze trending GitHub repositories by stars gained over specific time periods.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install skill-github-trending
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 skill-github-trending 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 Trending?
The GitHub Trending skill is a high-performance utility designed to scrape the GitHub Trending page and deliver structured data about the fastest-growing repositories on the platform. As part of the Openclaw Skills ecosystem, it provides developers and AI agents with real-time access to what is popular in the software world without requiring a GitHub API key or any external library installations.
By leveraging the Python standard library, this skill ensures maximum compatibility and speed. It allows users to filter results by programming language and time period, making it an invaluable resource for staying ahead of technological shifts and discovering new tools or frameworks.
GitHub Trending Use Cases
- Tracking daily, weekly, or monthly shifts in repository popularity to identify emerging tech trends.
- Filtering trending projects by specific programming languages like Python, Rust, or TypeScript.
- Generating automated reports or JSON feeds of popular projects for research and development purposes.
- Discovering high-quality open source projects for inspiration or contribution within Openclaw Skills workflows.
How GitHub Trending Works
- The user specifies a time period (daily, weekly, or monthly) and optional filters such as language or result limits.
- The skill constructs a target URL pointing to GitHub's trending section.
- It performs an HTTP request using the Python standard library's urllib to fetch the raw HTML content.
- An internal HTML parser extracts repository details including names, descriptions, total stars, and stars gained during the period.
- The data is formatted into either a human-readable list or a structured JSON object for further processing.
GitHub Trending Setup
To use this within the Openclaw Skills framework, ensure you have Python installed. No external pip packages are required.
Navigate to the skill directory and run the script:
# Basic usage for weekly trends
python scripts/github_trending.py weekly
# Filter by language with a result limit
python scripts/github_trending.py daily --language python --limit 10
GitHub Trending Data Schema & Taxonomy
The skill organizes data dynamically and can output in a structured format. The metadata includes the collection period and a timestamp (UTC+8).
| Field | Type | Description |
|---|---|---|
rank |
Integer | Position on the trending list |
full_name |
String | Owner and repository name (owner/repo) |
url |
String | Direct link to the repository |
stars_total |
String | Total stars accumulated by the project |
stars_gained |
Integer | Stars earned specifically during the requested period |
GitHub Trending Advanced Features
- Zero-dependency architecture using only Python built-ins like html.parser and urllib.
- Support for language aliases (e.g., py for python, rs for rust) to speed up CLI interactions.
- Native JSON output flag (
--json) for seamless integration with other Openclaw Skills and automated pipelines. - Automated UTF-8 handling for repository descriptions and emojis.
SKILL.md
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