I wanted to contribute to open source, but I had no idea where to start. 🔍

When I first wanted to contribute to open source projects, I struggled to find a platform that could help me discover issues relevant to my interests. I knew I wanted to start contributing, but figuring out where to look, which issues to pick, and how to find projects that matched my skills was overwhelming.

Finding GitHub issues isn’t the hard part. There are thousands of them. The real challenge is finding the ones that actually interest you.

That’s why I built Issue Scout. 🚀

The idea is simple: instead of endlessly browsing repositories and scrolling through issues, you can filter opportunities based on what matters to you.

With Issue Scout, you can narrow down issues by:

• 💻 Programming language
• 🏷️ Labels like good first issue, bug, and documentation
• 🎯 Suggested skill level
• 📅 Creation date
• 🔓 Issue status
• 🔎 Keywords and topics you’re interested in

I’m also working on making the search experience more reliable, with automated tests for API behavior, combined filters, pagination, empty results, and GitHub rate limit handling.

This project started with a problem I faced myself, and I hope it can make the first step into open source a little less confusing for someone else.

🚀 Try Issue Scout: https://issue-scout-chi.vercel.app/

💻 Explore the code: https://github.com/sharmao07/issue-scout

There’s still plenty to improve. I’d love to hear what filters, search features, or quality of life improvements would make this more useful for people getting started with open source contributions.

🎬 Video credits: The demo video was edited using Antigravity.

Issue Scout is live! 🚀

The first version of Issue Scout is now complete and deployed!

The core features are in place:

• Search public GitHub issues by keyword.
• Filter by programming language, labels, suggested skill level, creation date, and issue status.
• Browse paginated results and open issues directly on GitHub.
• Get started with quick filters for beginner-friendly issues, documentation, bug fixes, and Python.

🌐 Live site: https://issue-scout-chi.vercel.app/

💻 GitHub repository: https://github.com/sharmao07/issue-scout

I’m happy to have the main functionality working, but I’ll keep improving the UI and making the experience easier and smoother to use.

I’d love some help and feedback! If you’d like to help improve the UI, suggest a feature, or contribute something new, leave a comment on this devlog or feel free to open an issue on GitHub. Ideas, suggestions, and contributions are welcome!

Thanks for checking out Issue Scout!

Making Issue Scout easier to use

I’ve been working on making Issue Scout more approachable for people looking for their first open source contribution.

I added quick start presets for beginner friendly issues, documentation, bug fixes, and Python. Rather than starting with an empty set of filters, users can pick a starting point, adjust the filters, and search for issues that interest them.

I’m also improving the README so new users and contributors can understand how the app works, how to run it locally, what the API supports, and what limitations to keep in mind. This includes explaining how skill levels are estimated and why they should be treated as suggestions rather than guarantees.

Next: Run the lint and production build checks, test the search presets and pagination, and verify the updated version on the live deployment.

Live app: https://issue-scout-chi.vercel.app/

Source code: https://github.com/sharmao07/issue-scout

Issue Scout: Improving Issue Discovery and Filtering

Since my previous update, I’ve continued developing Issue Scout by connecting the search experience to GitHub’s public issue search API and expanding the available filters.

It now supports searching for open source issues by keyword, programming language, issue labels, and suggested skill level. The skill level classifier also accounts for issues whose difficulty cannot be confidently inferred from their labels, rather than automatically assuming they are intermediate.

I’m also adding two important filtering options to make issue discovery more useful: filtering by when an issue was created and filtering by its status. The creation date filter covers several time ranges, from the last 12 hours to older issues created between three months and one year ago. The status filter allows users to choose open issues, closed issues, or both.

These changes are intended to help contributors discover relevant opportunities more efficiently and find issues that match their preferences. Issue Scout continues to use GitHub’s API for its initial release, with skill- evel suggestions treated as estimates rather than definitive difficulty assessments.

I’m keeping the project focused on making the core search experience reliable before introducing AI features or deploying a public demo.

Next steps: finish testing the new filters, improve the issue result cards and error handling, verify the complete search workflow, and prepare the project for its eventual deployment.

Issue Scout: Connecting the first search experience

Started development on Issue Scout, an open source application designed to assist developers in discovering issues on GitHub that fit their specific tastes and skill levels.

I established the GitHub repository for the project, along with creating the initial Next.js, TypeScript and Tailwind CSS project. The initial interface allows users to search using keywords, filter using issue labels, and filter by an estimated skill level.

The next step will be integrating the interface with the public issue search API provided by GitHub. This will involve displaying actual results, handling any errors and loading issues, and making each result link back to the original repository.

For now, I am delaying implementation of AI and remaining purely API based for my initial release of the product. This will allow me to develop and test the base functionality and determine where I could use more intelligence from an AI system.

Next steps include completing the integration with the API, optimizing the filter for results, deploying a demo version of the website, and continuing documentation.