autonomous-improve

You can automate code quality improvement by scoring your codebase against a rubric, targeting the highest-leverage axis, and iteratively re-scoring to detect regressions across test coverage, type safety, error handling, API design, and documentation.

A rubric-based scoring loop is a repeatable process that scores codebases from scratch, attacks the weakest quality area, applies a fixed iteration limit, and documents learnings after each cycle to drive measurable improvements and prevent regressions.

Target the weakest areas by scoring your codebase against a defined rubric covering test coverage, type safety, error handling, API design, and documentation, then attacking the highest-leverage axis with iterative re-scoring to verify improvements.

Yes, this autonomous code improvement process operates without dependencies, relying solely on a repeatable rubric scoring mechanism, a fixed iteration limit, and structured documentation of learnings after each cycle.

Limitations include the requirement for a repeatable process with re-scoring from scratch and a fixed iteration limit, meaning the loop stops after reaching the maximum cycles rather than running indefinitely to chase marginal gains.