So, I have a pro@coder/.cache/code-map/context-code-map.json.

I also have a `.tmpl-code-map.jsonl` in the same folder so all of my tasks can add to it, and then it gets merged into context-code-map.json.

I keep mtime, but I also compute a blake3 hash, so if mtime does not match, but it is just a "git restore," I do not redo the code map for that file. So it is very incremental.

Then the trick is, when sending the code map to AI, I serialize it in a nice, simple markdown format.

- path/to/file.rs - summary: ... - when to use: ... - public types: .., .., .. - public functions: .., .., ..

- ...

So the AI does not have to interpret JSON, just clean, structured markdown.

Funny, I worked on this addition to my tool for a week, planning everything, but even today, I am surprised by how well it works.

I have zero sed/grep in my workflow. Just this.

My prompt is pro@coder/coder-prompt.md, the first part is YAML for the globs, and the second part is my prompt.

There is a TUI, but all input and output are files, and the TUI is just there to run it and see the status.