ai-slop-cleaner

AI slop cleanup removes redundant wrappers and duplicated logic safely by enforcing a plan-first, deletion-first workflow with regression tests and diffs to verify behavior is preserved.

The best way to refactor AI-generated code safely is using a bounded cleanup workflow that applies a formal cleanup plan alongside regression checks, ensuring changes are traceable and reversible via diffs.

Yes, regression tests are required before cleaning up AI slop. The workflow uses them to confirm stability and prevent unintended behavior changes, ensuring the cleanup remains strictly bounded and safe.

Yes, you can review AI code cleanup changes. The workflow supports an optional reviewer-only mode, allowing a separate review pass for quality assurance before any deletions are finalized.

A key limitation is scope: cleanup is strictly bounded to designated modules or changed files. It must follow a formal cleanup plan and cannot drift scope or alter intended behavior without triggering rollback.

AI slop cleanup requires a formal cleanup plan to enforce a deletion-first workflow that maintains safety and traceability. It guides the removal of weak abstractions within a controlled scope, preventing unintended regressions.