Agent-powered iterative optimization: put an AI agent in a verified improvement loop.
AutoHelix is a harness that lets an AI agent repeatedly propose changes toward a measurable goal while checks decide which changes are accepted. It is for tasks such as code optimization or model training where constraints, metrics, file scope, isolation, and budgets need to be controlled. Its catalogue contains instructions and a skill for running the improvement loop.
These files are awslabs/AutoHelix's own configuration. They tell Codex, OpenCode and Claude Code how to work on this repository, so they are not mods to install elsewhere. Copy one as a starting point and replace the parts that are about this project.
AGENTS.md A 286 tok CLAUDE.md A 1,370 tok