remove-ai-slops

To remove AI slop without breaking behavior, you must pin existing functionality with regression tests first, then apply categorized cleanup to target comments, dead code, and complexity before re-verifying with tests and quality gates.

AI slop in refactoring refers to generated code smells like over-defensive checks, duplication, and unnecessary abstractions. Safe cleanup requires categorizing these patterns, stripping them from changed files, and verifying that public behavior remains unaltered.

Yes, you need regression tests before cleaning up AI generated code. Behavior-locked cleanup requires pinning existing functionality with tests prior to any edits, ensuring that readability improvements and safe refactoring do not alter public behavior.

Yes, you can apply automated code cleanup to a branch diff without failing type checks. The process requires verifying the refactored result through tests, type checks, and linting, ensuring the cleanup remains trustworthy and behavior preservation holds.

The best way to strip AI generated patterns from changed files is using a regression-locked cleanup approach. This involves targeting categorized slop like dead code and complexity, then validating the result through critical review, tests, and quality gates.

You should not use automated slop removal when your codebase lacks pre-change regression tests. Without tests to pin existing behavior first, applying refactoring, readability improvements, and dead code removal risks altering public behavior and failing verification.