First, I implemented `repogather --all` , which unintelligently copies all sources files in your repository to the clipboard (delimited by their relative filepaths). To my surprise, for less complex repositories, this alone is often completely workable for Claude — much better than pasting in the just the few files you are looking to update. But I never would have done it if I had to copy/paste everything individually. 200k is quite a lot of tokens!

But as soon as the repository grows to a certain complexity level (even if it is under the input token limit), I’ve found that Claude can get confused by different unrelated parts / concepts across the code. It performs much better if you make an attempt to exclude logic that is irrelevant to your current change. So I implemented `repogather "<query here>"` , e.g. `repogather "only files related to authentication"` . This uses gpt-4o-mini with structured outputs to provide a relevance score for each source file (with automatic exclusions for .gitignore patterns, tests, configuration, and other manual exclusions with `--exclude <pattern>` ).

gpt-4o-mini is so cheap and fast, that for my ~8 dev startup’s repo, it takes under 5 seconds and costs 3-4 cents (with appropriate exclusions). Plus, you get to watch the output stream while you wait which always feels fun.

The retrieval isn’t always perfect the first time — but it is fast, which allows you to see what files it returned, and iterate quickly on your command. I’ve found this to be much more satisfying than embedding-search based solutions I’ve used, which seem to fail in pretty opaque ways.

https://github.com/gr-b/repogather

Let me know if it is useful to you! Always love to talk about how to better integrate LLMs into coding workflows.