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github-ai-trends skill

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This skill generates a formatted GitHub AI trends leaderboard for daily, weekly, or monthly periods, presenting top AI repos for quick insights.

npx playbooks add skill openclaw/skills --skill github-ai-trends

Review the files below or copy the command above to add this skill to your agents.

Files (3)

SKILL.md

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---
name: github-ai-trends
description: 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.
---

# 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:

```bash
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.

Overview

This skill generates formatted leaderboard reports of trending AI projects on GitHub. It fetches top-starred AI/ML/LLM repositories for a chosen period and renders a compact, chat-ready leaderboard. Use it to quickly see which AI repos are gaining traction daily, weekly, or monthly.

How this skill works

The tool queries the GitHub API for AI-related repositories using keywords and topics, restricted to activity within the selected period. It deduplicates results, sorts them by star count, and outputs a styled markdown leaderboard or raw JSON when requested. It supports a configurable limit on the number of repos and can use a GitHub token to increase rate limits.

When to use it

You want a quick leaderboard of rising AI/ML/LLM projects on GitHub.
Preparing a newsletter or report about recent AI open-source trends.
Evaluating which AI libraries and tools are gaining community interest.
Curating a list of popular AI repos for research or hiring decisions.
Monitoring weekly or monthly momentum for AI initiatives.

Best practices

Run with a GitHub token (or set GITHUB_TOKEN) to reduce rate limiting on frequent queries.
Use --period (daily/weekly/monthly) to match the cadence you need for reports.
Increase --limit only when you need broader coverage; larger results take longer and consume API quota.
Prefer formatted markdown output for chat display and --json when you need machine-readable data.
Re-run periodically to capture trends rather than a single snapshot.

Example use cases

Generate a weekly leaderboard to include in an AI community newsletter.
Compare monthly trend snapshots to spot projects with sustained growth.
Create a curated set of top AI repos for onboarding new engineers.
Monitor trending LLM tools before choosing dependencies for a new project.
Export raw JSON to feed a dashboard that visualizes repo momentum over time.

FAQ

What periods can I query?

You can request daily, weekly, or monthly trends using the --period flag.

Do I need a GitHub token?

No, but providing a token (or GITHUB_TOKEN) raises the API rate limits and is recommended for frequent use.