ai-slop-cleaner

Refactor AI-generated code by removing dead code, duplicates, and unnecessary abstractions. The Skill uses a regression-safe, deletion-first approach to simplify bloated logic while ensuring tests pass and intended behavior remains unchanged.

Remove dead code and unnecessary abstractions from AI code by applying a targeted refactoring strategy. A deletion-first workflow eliminates bloat and repetitive logic while preserving the original intended behavior through regression testing.

Yes, you need a clear regression testing strategy to refactor AI-generated code safely. A safe code cleanup plan requires tests to verify that removing duplicates and abstractions does not alter the intended behavior of the application.

Yes, you can target a specific directory for AI code cleanup by providing a bounded file list. This focuses the refactoring and dead code removal on specific modules, such as running the cleanup command on the 'src/auth' directory.

Avoid a deletion-first refactoring approach when you lack a clear regression testing strategy. Without tests to confirm intended behavior, removing dead code, duplicates, and unnecessary abstractions risks introducing new bugs into the AI-generated code.