Inspiration

Every developer knows the struggle: you want to contribute to open source, but finding the right project feels impossible. You scroll through thousands of repos, encounter issues that require months of context, or find "good first issues" that were claimed weeks ago.

We built Mr. Git because we believe open source contribution should be accessible to everyone—not just those with insider knowledge of which projects are welcoming to newcomers.

What it does

Mr. Git is a smart open source contribution discovery platform.

Developers enter their skills (languages, frameworks), experience level, and interests, and instantly receive a curated feed of real GitHub issues matched to their profile.

Each opportunity card shows:

• Repository details with stars, forks, and activity status
  
• The specific issue with labels and comment activity
  
• A difficulty estimate (Easy / Medium / Hard)
  
• Match reasons explaining why this opportunity fits their skills
  
• Direct links to contribute immediately
  

Powerful client-side filters let developers narrow results by:

• Language
  
• Difficulty
  
• Minimum stars
  
• Issue type (bug / docs / feature)
  
• Active repositories only
  

How we built it

• Built with Mocha: This project was organized and built using Mocha (https://getmocha.com), an AI-powered website builder that significantly accelerated development. Mocha made it easy to structure the project, iterate quickly, and focus on product logic instead of setup overhead. Its smooth workflow and intelligent tooling helped turn ideas into a polished experience much faster than traditional approaches.

Challenges we ran into

• GitHub API Rate Limits: Without authentication, the public API limits requests significantly. We optimized queries and implemented graceful error handling for rate-limited responses.
  
• Difficulty Estimation: Determining issue complexity without AI analysis required heuristics. We use label detection, issue body length, and comment count as proxies.
  
• Balancing Relevance: Popular mega-repos dominate search results but often have steep learning curves. We tuned scoring to favor mid-size, actively maintained projects where contributions have real impact.
  

Accomplishments that we're proud of

• Zero Mock Data: Every result comes from live GitHub data—real issues you can contribute to right now
  
• Premium Dark UI: The interface feels like a high-end developer tool, not a basic search page
  
• Instant Matching: Skill-to-language mapping and interest-to-topic translation make searches feel intelligent
  
• Mobile-Responsive: Full functionality on any device
  
• Fast Delivery with Mocha: Using Mocha allowed us to move from concept to a production-quality experience quickly, helping us focus on innovation rather than boilerplate setup
  

What we learned

• GitHub's Search API is powerful but has quirks. no:assignee filters and label queries require careful formatting.
  
• Good UX for developers means dense information without clutter—every pixel should earn its place.
  
• Scoring algorithms need tuning. Our first version over-weighted star counts, surfacing only massive projects.
  

What's next for Mr. Git

• AI-Powered Analysis: Use LLMs to analyze issue descriptions and estimate true difficulty, required context, and time-to-contribute
  
• Personalized Recommendations: Save user profiles and learn from which issues they click or contribute to
  
• GitHub OAuth: Let users star issues, track contributions, and receive notifications when new matches appear
  
• Community Rankings: Surface projects with the best contributor experience based on merge rates and maintainer responsiveness
  
• Browser Extension: Show Mr. Git recommendations directly on GitHub while browsing
  

Built With

• mocha