SkillsAdd

stvlynn/qclaw-skills · Archived

github-ai-trends

Generate GitHub AI trending project reports as formatted text leaderboards.

First seen Mar 21, 2026

Installation

$ npx skills add stvlynn/qclaw-skills --skill github-ai-trends
View on skills.sh ↗ GitHub repository ↗

Summary

  • Generate GitHub AI trending project reports as formatted text leaderboards.
  • Fetches top-starred AI/ML/LLM repos by daily, weekly, or monthly period and renders a styled leaderboard.
  • Use when the user asks for AI project trends, GitHub trending, AI leaderboard, or wants to see popular AI repos.

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Also in this package

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npx skills add stvlynn/qclaw-skills
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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

Claude Code Not declared
Cursor Not declared
Codex Not declared
GitHub Copilot Not declared
Windsurf Not declared
Gemini CLI Not declared
Cline Not declared
OpenCode Not declared

Repository health

Stars 4
Default branch main
Open issues 0
Status Archived

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 1,249 B
  • docs SUMMARY.md 318 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 4 installs

SKILL.md

GitHub AI Trends

Generate formatted leaderboard of trending AI projects on GitHub, output directly to chat.

Usage

Run the script and paste its stdout as the reply:

python3 scripts/fetch_trends.py --period weekly --limit 20

Parameters

  • --period: daily | weekly | monthly (default: weekly)
  • --limit: Number of repos (default: 20)
  • --token: GitHub token for higher rate limits (or set GITHUB_TOKEN env)
  • --json: Output raw JSON instead of formatted text

How It Works

  1. Searches GitHub API for AI-related repos (by keywords + topics) pushed within the period
  2. Deduplicates and sorts by star count
  3. Outputs a formatted markdown leaderboard ready for chat display

Notes

  • Without a GitHub token, API rate limit is 10 requests/minute. With token: 30/minute.
  • No pip dependencies, uses only stdlib.
  • Output is markdown formatted for direct chat display.