improve-codebase-architecture

Surface architectural friction by exploring your large codebase to identify shallow modules and cross-module coupling signals. You can then propose module-deepening refactors to boost testability, maintainability, and boundary clarity across the system.

A shallow module in codebase architecture is a component that hides little implementation detail, creating cross-module coupling and friction. Deepening these modules improves testability, AI-navigability, and overall architectural clarity.

Plan a codebase refactor by generating module-deepening candidates and framing interfaces to resolve cross-module dependencies. This approach prioritizes changes that improve testability and boundary clarity, culminating in RFC-driven governance via GitHub Issues.

Yes, you can use GitHub Issues for RFC-driven governance by proposing module-deepening RFCs using provided templates. This allows you to track architectural changes, prioritize testability improvements, and manage boundary design decisions directly in your repository.

Yes, analyzing AI-navigability in large codebases is a core focus of this approach. By deepening shallow modules and clarifying architectural boundaries, the system becomes significantly easier for AI to navigate and understand.

The best way to surface coupling signals across modules is to analyze the codebase to identify friction points and shallow modules. This reveals cross-module dependencies and informs interface framing to improve architectural clarity.