By combining structured diagnostic reasoning with efficient repository exploration, SHERLOC helps coding agents spend less time searching for bugs and more time fixing them—improving fix success rates by ~6% while cutting token usage by a quarter.
SHERLOC is a framework that helps AI coding agents quickly find and diagnose bugs in large codebases. Instead of just pointing to buggy files, it provides the reasoning and context needed to actually fix them. The system uses reasoning-focused language models with repository tools and achieves state-of-the-art results while using 36% fewer tokens than competing approaches.