| name | github-stars-analyzer |
| description | Analyzes GitHub repository data to generate comprehensive research reports about stars, popularity trends, and comparative insights |
GitHub Stars Research Analyzer
This skill provides in-depth analysis of GitHub repositories, tracking star growth, comparing popularity metrics, and generating research reports for open source projects and developer tools.
Capabilities
- Repository Analysis: Extract and analyze key metrics (stars, forks, issues, contributors, activity)
- Star Growth Tracking: Calculate daily, weekly, and monthly star growth rates and trends
- Comparative Analysis: Compare multiple repositories across various metrics
- Research Report Generation: Create comprehensive reports with insights and recommendations
- Data Visualization: Generate charts and graphs for trend analysis
- Export Formats: Output reports in Markdown, PDF, and JSON formats
Input Requirements
GitHub repository data can be provided in multiple formats:
- Repository URLs: Direct GitHub repository links
- Owner/Repo Names: GitHub owner and repository names
- JSON Input: Structured data with repository information
- CSV Lists: Multiple repositories in CSV format
Required fields:
- Repository owner (username or organization)
- Repository name
- Optional: Time period for analysis (default: last 30 days)
Output Formats
Results include:
- Metrics Summary: Key statistics and calculations
- Growth Analysis: Star growth rates and trends
- Comparative Insights: Multi-repository comparisons
- Visualizations: Charts and graphs (when applicable)
- Recommendations: Actionable insights for project maintainers
- Export Options: Markdown, PDF, and JSON reports
How to Use
"Analyze the GitHub repository claude-code-skills-factory and generate a star growth report"
"Compare the popularity of these three repositories over the last 90 days"
"Track star growth trends for the Anthropic organization's repositories"
"Generate a comprehensive research report on React's star growth patterns"
Scripts
github_api.py: Handles GitHub API interactions and data fetchinganalyze_repository.py: Core analysis engine for repository metricsgenerate_reports.py: Creates research reports in multiple formatsvisualize_data.py: Generates charts and visualizations
Best Practices
- Respect Rate Limits: Always handle GitHub API rate limits gracefully
- Data Validation: Verify repository existence and accessibility
- Time Period Selection: Use appropriate time windows for meaningful analysis
- Comparative Context: Always provide industry/ecosystem context for metrics
- Privacy Considerations: Respect private repositories and user privacy
Limitations
- API Rate Limits: GitHub API has strict rate limits (60 requests/hour unauthenticated)
- Historical Data: Limited historical data availability through API
- Private Repositories: Cannot access private repositories without proper authentication
- Data Freshness: Real-time data depends on GitHub API updates
- Repository Age: New repositories may not have sufficient historical data
