Evaluating GitHub repos systematically with Claude Code

Here's a scenario that plays out constantly when you're building with generative AI: you search GitHub for a solution, get hundreds of results, and then face the real challenge of figuring out which repository actually fits your needs. You might create a scratchpad, jot down some interesting links, and then never get around to properly evaluating them. I built the Claude GitHub Shortlister to solve exactly this problem.

How it works

It's a template repository with a simple but effective workflow. You get two key files: repos.md where you dump all the GitHub repository links you want to evaluate, and spec.md where you define your requirements and why you're looking for a solution in the first place. Then you run the custom Claude Code slash command and let it do the heavy lifting.

The automated analysis reviews each repository against your specifications, organizes them by star count, last update date, and relevance to your requirements, and provides best-fit recommendations. Results get saved to an analysis folder for easy reference.

Use cases

I've been using this for evaluating libraries for new projects, finding the best tool for specific tasks, and comparing similar solutions before making technology decisions. It's especially useful when you're researching across multiple sessions and want to keep track of your evaluation progress.

The beauty of making it a template repository is that you can spin up a new instance for each evaluation project. Need to pick a database library? Create a repo from the template. Comparing CI/CD tools? Another instance. Each evaluation stays self-contained with its own requirements and analysis.

Grab the template on GitHub and bring some structure to your next tool evaluation.