A GitHub profile visualizer that transforms raw data into developer intelligence
GitHub shows you the data. But it doesn't tell you the story.
When you land on a developer's profile, you're still left asking:
- What are they actually skilled at?
- How impactful are their contributions?
- What's their dominant tech stack?
- How do they stack up against others?
You're connecting dots manually. That's inefficient.
DevArchive gives you the answer in seconds. It transforms any GitHub profile into a clean, visual, insight-driven experience — revealing the developer behind the repositories. Think of it as a portfolio intelligence layer on top of GitHub.
- Instant lookup with full metadata
- Animated language distribution
- Top 6 repositories ranked by impact
- Account age, location, company, blog link
A custom algorithm grading across 5 weighted dimensions:
- Impact | Reach | Productivity | Quality | Maturity
- Visual score ring with S / A / B / C grades
Interactive D3.js force-directed graph showing:
- Repositories clustered by language
- Click-to-explore interaction
Head-to-head stats across multiple metrics:
- Animated progress bars with winner detection
- Language breakdown per developer
- Overall winner banner (with tie support)
Search GitHub with:
- Language filtering
- Sort by stars, forks, or last updated
- Paginated deep exploration
This wasn't a traditional build.
Claude orchestrated the core logic and architecture.
Google Stitch shaped the frontend into something clean and intuitive.
The result: a product that feels intentional from every angle — both code and design.
| Layer | Tool |
|---|---|
| Frontend | Google Stitch |
| Logic & Backend | Claude |
| IDE | Cursor |
| Polish & Debugging | ChatGPT |
| Visualization | D3.js |
✅ Working with real-world APIs (pagination, rate limits, async flows)
✅ Building interactive data visualizations with D3.js
✅ Full-stack architecture without framework dependencies
✅ Designing products that are both useful and beautiful
✅ Using AI as a thinking partner, not just a code generator
✅ Iterating faster: Build → Test → Break → Improve
GitHub shows what you've built.
DevArchive shows what that actually means.
Instead of asking AI to "write the app", I used it to:
- Break down complex features before touching code (score algorithm, D3 graph structure)
- Debug async flows and GitHub API rate limit handling
- Evaluate UI/UX tradeoffs before building
- Iterate 10× faster: build → test → break → refine → rebuild
The thinking was mine. The speed was AI's.
- AI summary and recommendations
- Exportable developer PDF report card
- Contribution activity heatmap
- Organization profile support
- Roast Me feature