Repo Radar

Every week, developers face a decision that feels simple but is costly: which library should I use? With 300 million+ GitHub repositories, choosing wrong means weeks of technical debt. Stars alone are a popularity signal, not a health signal — a repo with 60K stars but 800 open issues and no commits in 6 months is worse than one with 8K stars and active weekly merges. Comparing two repos today means opening 4-6 browser tabs, copying stats into a spreadsheet, and spending 30-60 minutes on what should be a 5-minute decision. Junior developers and students have no synthesis layer — no tool that says 'given these two options, pick this one, here's why.'

Repo Radar compresses a 45-minute library evaluation into a 4-minute flow. Users search for repositories, select any two, and get a real-time side-by-side comparison of health metrics — stars, forks, open issues, contributors, commit velocity, license — augmented by a Groq LLaMA-3 AI recommendation that translates raw data into a plain-English verdict. Topic chips and curated handpicked comparison presets let first-time users reach their first insight in under 30 seconds without knowing what to search for. The entire app runs serverless on Vercel — no backend to manage.

I mapped three personas — an indie developer optimizing for speed, a tech lead needing data to justify decisions to stakeholders, and a CS student learning ecosystem norms without a senior mentor. Competitor analysis across GitHub native search, npm Trends, OSS Insight, and Snyk Advisor revealed the gap: no free tool combined real-time GitHub metrics, side-by-side layout, AND AI recommendation in one interface. I ran a funnel analysis of the user journey and identified Step 3 (selecting a second repo) as the highest drop-off risk — mitigated through auto-suggest of semantically related repos after the first selection. The PRD defined a 4-phase roadmap from core experience to a VS Code extension and multi-repo comparison.

Shipped a live product at repo-radar-peach.vercel.app with a full PRD, KPI framework, and go-to-market strategy. North star metric set as Comparison Completion Rate (target ≥35% by Month 3). Defined a freemium pricing model (Free / $5 Pro / $20 Team) with a TAM of $28B in the developer tools market and a 3-year SOM of $80M in AI-powered repo intelligence.