> If a developer wanted to change X, would these keywords help them find this file?
I think the best way to generate these is with a sub-agent. Tell it to try and solve a problem that involves editing this file, and see what it starts grepping for.
This ties in with this idea that the tools and designs should be what comes naturally to the LLM, i.e. what it's already been trained on. And the most straightforward way to do that is to let it reach for it.
Like when you reach in the darkness for an object. Where your hand lands is exactly where it should be.
My solution has a natural self improvement loop. Once you have finished a task, you just ask the agent "If you had more information, how would you have finished the task sooner and/or better?" This was how I came about the rust blast radius brain.
I need to modify OpenAI's Codex agent to support slash commands that can help humans better guide agents, and I needed a solution with the least impact. They don't accept contributions so I need to plan for syncing with the upstream.