github-trends

name	github-trends
description	Analyze GitHub trending repositories and generate a visual dashboard. Use this skill when the user wants to know what's hot on GitHub, analyze technology trends, or create a trending report.

GitHub Trends Analyst

This skill enables Gemini CLI to fetch, analyze, and visualize GitHub trending repositories. It provides a complete workflow from data collection to insight generation and dashboard creation.

Capabilities

1. Fetch Trending Repos: Retrieve trending repositories by language and timeframe (daily, weekly, monthly).
2. Trend Analysis: Use AI to identify emerging patterns, popular technologies (e.g., AI/LLM, Web3, DevTools), and shifts in the developer ecosystem.
3. Visual Dashboard: Generate a clean, modern HTML dashboard to present the findings.

Workflow

To perform a complete analysis, follow these steps:

1. Data Collection

Use the fetch_trends.py script to get raw data in JSON format.

python scripts/fetch_trends.py --lang [language] --since [daily|weekly|monthly] --format json > trends.json

2. AI Analysis

Read the trends.json file and analyze the content. Look for:

• Common themes among the top repos.
• Sudden spikes in specific frameworks or libraries.
• Innovative use cases for existing technologies.

3. Dashboard Generation

Generate the final HTML report using generate_dashboard.py.

python scripts/generate_dashboard.py --input trends.json --analysis "[AI_ANALYSIS_TEXT]" --template assets/dashboard_template.html --output github_dashboard.html

Resources

scripts/

• fetch_trends.py: Scrapes GitHub Trending page. Supports --lang, --since, and --format.
• generate_dashboard.py: Combines JSON data and AI analysis into an HTML dashboard.

assets/

• dashboard_template.html: A modern Vanilla CSS template for the dashboard.

Examples

User: "Analyze Python trends for this week"

1. Run fetch_trends.py --lang python --since weekly --format json.
2. Analyze the results (e.g., identifying a lot of agentic AI frameworks).
3. Run generate_dashboard.py with the analysis.
4. Provide the link to the generated github_dashboard.html to the user.