Comment by starfezzy

Cramming thousands of tokens of potentially irrelevant context through unclear indexing paths isn't "proper".

The best results come from feeding precisely targeted context directly into the prompt, where you know exactly what the model sees and how it processes it. The prompt receives the most accurate use of attention—whereas god knows what the pipeline is for cursor or what extra layers and context restrictions they add on top of base Claude.

Giving the model a clean project hierarchy accomplishes a lot efficiently in terms of context tokens. The key is ensuring it only sees what's relevant, without diluting its attention.

Tools like reopmix and OP's version, feeding targeted context straight into models like Claude or Google's offerings, outperform Copilot and Cursor in my experience, even though they use the same base models. Use the highest-quality attention (the prompt context) directly, rather than layers of uncertainty and "proper indexing".