What problem does it solve?
It helps teams find why their agent-driven development environment underperforms by auditing the existing Harness setup and pinpointing concrete failure modes in memory, rules, skills, agents, hooks, tools, and documentation.
Core Features & Use Cases
- Seven-dimension health scoring: Produces a structured score (0–21) to show what’s missing or weak and what to fix first.
- Failure-mode diagnostics: Checks common issues like brittle or vague CLAUDE.md rules, missing/enforced hooks, weak validation gates, and inconsistent architecture documentation.
- Prioritized optimization plan: Converts findings into a frequency-by-severity remediation roadmap for immediate, monthly, and continuous improvements.
- Use case: When your team has been using Claude Code for a while but the agent repeatedly forgets tests, edits protected files like .env, or violates architectural boundaries, the audit generates a plan to correct the Harness so the agent follows reliably.
Quick Start
Ask an AI to run a harness health check by saying: “Audit this project’s Harness and give me a prioritized fix plan with scores and specific failure-mode recommendations.”