Codebase readiness
Codebase readiness is how well a codebase supports AI/agentic development — measured by module boundaries, tests, types, docs, and context files.
Codebase readiness scores how effectively coding agents can work in a repository. The dimensions that matter most are clear module boundaries, meaningful and fast tests, strict types, accurate documentation, the presence of a context/rules file, and the ability to reach external systems via MCP.
A ready codebase gives agents a tight feedback loop and the context to act correctly; an unready one leaves them editing the wrong files, missing context, and producing confidently broken changes.
Quantifying readiness turns “our codebase isn’t ready” from a feeling into a prioritized roadmap of the cheapest, highest-leverage fixes.