A transparent, serverless pipeline that transforms raw GitHub data into meaningful intelligence. Every score, insight, and recommendation is calculated with documented logic.
RepoPulse processes GitHub data through a clean, layered architecture designed for performance, transparency, and maintainability.
User requests repository analysis via web interface or API endpoint
Fetch repository metadata, commits, issues, PRs, and contributors from GitHub REST API
Check Redis cache for existing data to avoid unnecessary API calls
Process raw GitHub data into quantitative metrics and derived measurements
Apply rule-based intelligence engine to identify patterns and generate recommendations
Calculate transparent health score using weighted component scores
Return JSON data, SVG cards, or rendered web pages
RepoPulse uses GitHub's official REST API to gather data while respecting rate limits and providing optional authentication for enhanced access.
GitHub REST API v3 with JSON responses
5,000 requests/hour with authentication, 60/hour without
Optional GitHub token for higher rate limits and private repo access
Repository info, commits, issues, PRs, contributors, user profiles
Intelligent caching reduces API calls, improves performance, and ensures consistent results for repeated requests while staying fresh enough for meaningful analysis.
Upstash Redis for serverless, global caching
Repository data cached for 1 hour, user data for 6 hours
Namespaced by owner/repo and analysis window
Graceful degradation to fresh data if cache unavailable
Rule-based intelligence identifies patterns in repository data and generates actionable insights with confidence scores to help maintainers understand their project's health.
Each insight triggered by specific metric thresholds
0-1 confidence rating for each insight based on data quality
Activity, Responsiveness, Growth, Maintenance, Diversity
Error (critical), Warning (concerning), Info (positive/interesting)
Low Activity: If commits in last 90 days < 9 (0.1/day), confidence 0.9
Slow Response: If average issue response time > 7 days, confidence 0.85
High Diversity: If contributor diversity > 0.5 with >10 contributors, confidence 0.85
Health scores are calculated using weighted components, with transparent formulas and explanations for every point awarded or deducted.
Calculation: Based on commit frequency and recency of last commit
Example: Daily commits = +10, no commits in 30 days = -40
Calculation: Issue response time and PR merge velocity
Example: Response within 24h = +0, 7+ days = -40
Calculation: Stars, forks, and community adoption metrics
Example: 1000+ stars = +40, <10 stars on old repo = -30
Calculation: Issue resolution rate and backlog management
Example: 70%+ resolution rate = +0, <50% = -50
Calculation: Contributor diversity and community breadth
Example: High diversity ratio = +30, single contributor = +0
overall = (activity × 0.25) + (responsiveness × 0.25) + (growth × 0.2) + (maintenance × 0.2) + (diversity × 0.1)See RepoPulse in action with real repository analysis. Every score and insight is calculated using the transparent logic explained above.
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