What problem does it solve?
It helps you continuously reduce CLAUDE.md and Harness overhead as models improve, preventing documentation drift, architecture drift, and code entropy from wasting tokens and effort.
Core Features & Use Cases
- CLAUDE.md Slimming & Rule Pruning: Evaluate each rule for whether it’s still necessary, redundant with hooks/linters, and actually tied to real failure modes—aiming to keep CLAUDE.md under 60 lines.
- Garbage Collection for Drift: Detect documentation drift against docs/architecture.md and source code, then propose specific fixes for mismatches in rules and technology decisions.
- Harness Streamlining After Model Upgrades: Test model behavior across a standard task set and remove or adjust scaffolding that the upgraded model now handles natively.
- Proactive Improvement Roadmap: Upgrade from human-maintained improvements to PR-based self-healing Harness changes by logging harness-related friction and then converting it into concrete improvements.
Quick Start
Ask the AI: "Use harness:evolve to evaluate our CLAUDE.md and hooks for model-upgrade trimming, then produce a delete list with reasons and a plan to slim to 60 lines or less."