Run an anti-slop cleanup/refactor/deslop workflow
Reduce AI-generated slop with a regression-tests-first, smell-by-smell cleanup workflow that preserves behavior and raises signal quality.
Use this skill when:
Lock behavior with regression tests first
Create a cleanup plan before code
Categorize issues before editing
Execute passes one smell at a time
Run quality gates
Finish with an evidence-dense report
AI SLOP CLEANUP REPORT
======================
Scope: [files or feature area]
Behavior Lock: [targeted regression tests added/run]
Cleanup Plan: [bounded smells and order]
Passes Completed:
1. Pass 1: Dead code deletion - [concise fix]
2. Pass 2: Duplicate removal - [concise fix]
3. Pass 3: Naming/error handling cleanup - [concise fix]
4. Pass 4: Test reinforcement - [concise fix]
Quality Gates:
- Regression tests: PASS/FAIL
- Lint: PASS/FAIL
- Typecheck: PASS/FAIL
- Tests: PASS/FAIL
- Static/security scan: PASS/FAIL or N/A
Changed Files:
- [path] - [simplification]
Remaining Risks:
- [none or short deferred item]
Good: The user says continue after tests already lock behavior and the next smell pass is clear. Continue with the next bounded cleanup pass.
Good: The user narrows the scope to a specific file after planning. Keep the regression-tests-first workflow, but apply the new scope locally.
Bad: Start rewriting architecture before protecting behavior with tests.
Bad: Collapse multiple smell categories into one large refactor with no intermediate verification.