I used autoresearch to improve my AGENTS.md, measured against real tasks

I had a blast having all the major models figure out the most optimal strategy for itself inside of Cursor, with cursorrules, AGENTS.md, .cursor/rules/ mrd files or whatever and learned some interesting things, how it won’t guarantee every instruction even when it’s told to, for example

Seems like the progressive disclosure approach is the best for context efficiency; I wound up with a somewhat tight generic AGENTS.md, and the .cursor/rules individual files with glob matching for file names. Cursor honored those well.

I must have spent a couple hundred on the company dime having the models rephrase/rewrite or change where instructions were found, what made sense as a skill vs a rule, trying to keep things as portable as possible. At this point the Cursor-specific files would need to be ported to a different agent/framework if it needed to be. But the content should be pretty solid.

It was an interesting (and productive) exploration for me