autoresearch

Run autonomous codebase improvement in clean-room isolation using three teams that operate on separate branches to find, fix, and simplify code. Strict revert procedures, version stamping, and branch-naming conventions keep your main branch untouched while per-track artifacts preserve experiment integrity.

Automate code fixes across languages by applying a three-team orchestration that detects repository stacks and runs tests automatically. It applies to target repositories regardless of language, logging per-cycle results to support reproducibility and auditing for your codebase experimentation.

Yes, you can scope automated refactoring to specific areas. Use the narrow mode for goal-directed improvements on a target path, or choose broad mode for hypothesis-divergent exploration and sweep mode for comprehensive quality sweeps across your codebase.

No, configuration is optional. Autonomous testing and experimentation runs by default with automated session management, but you can add an optional .autoresearch.yml file to customize team assignments and operating modes for your codebase improvement sessions.

Session management handles per-session version stamping, area scoping, branch tracking, and results logging. This automated process ensures reproducibility and auditing by keeping clean-room barriers between the Red, Green, and Refactor teams during codebase experimentation.

Autonomous refactoring operates safely within clean-room barriers using strict revert procedures and version stamping, but requires adequate test coverage to validate fixes. Per-cycle results logging and branch tracking help monitor limitations and ensure experiment integrity across isolated tracks.