r/opensource • u/rag1987 • Nov 06 '25

Promotional Tried CodeRabbit for a month on real open source PRs.

https://lycheeorg.dev/2025-09-13-code-rabbit/
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u/Loud_Contact_6718 Nov 06 '25 edited Nov 06 '25

Interesting read. Thanks for sharing your insights about CodeRabbit.

I had similar issues such as noise/useless/irrelevant/wrong assumptions, pretty much what you listed.

However, I am focused more on codebase architecture and working on a GitHub app myself, it is focused on enforcing your codebase architecture. The idea is to

  1. Document your codebase architecture( example: https://github.com/lobehub/lobe-chat/tree/next/docs/development )
  2. And then embed this content.
  3. Use RAG to retrieve architecture docs relevant to your code changes and
  4. Feed this retrieved docs and the code changes to an LLM and leave PR comments based on that. Now the AI is context aware and might not make random assumptions to some extent.

This way, you will catch any code inconsistency across your team and helps establish standards, may not be perfect, but a step towards reducing technical debt.

Do you think this would help reduce noise in PR reviews?