What problem does it solve?
This Skill solves the pain of working with codebases that have shallow, tightly coupled modules that are hard to test, maintain, and navigate, especially for AI tools working with the code. It eliminates the guesswork of identifying where architectural improvements will have the biggest impact on testability and long-term maintainability.
Core Features & Use Cases
- Organic Codebase Exploration: Navigates your codebase naturally to identify architectural friction points like shallow modules, tight coupling, and hard-to-test seams, without relying on rigid heuristics.
- Module-Deepening Refactor Proposals: Suggests concrete refactors to consolidate shallow modules into deep, testable modules with small interfaces and large implementations, following John Ousterhout's software design philosophy.
- Structured RFC Generation: Creates ready-to-use GitHub issue RFCs for proposed architectural changes, including dependency strategies, testing plans, and implementation guidance.
- Use Case Example: If your team is struggling to write tests for a set of tightly coupled utility modules, this Skill will surface refactoring opportunities to consolidate them into a single deep module with a clear interface, making testing straightforward.
Quick Start
Use the improve-codebase-architecture skill to analyze your project's codebase and identify high-impact refactoring opportunities to make your modules more testable and maintainable.
