ai-slop-cleaner

SKILL.md

AI Slop Cleaner

Use this skill to clean AI-generated code slop without drifting scope or changing intended behavior. In OMC, this is the bounded cleanup workflow for code that works but feels bloated, repetitive, weakly tested, or over-abstracted.

When to Use

Use this skill when:

  • the user explicitly says deslop, anti-slop, or AI slop
  • the request is to clean up or refactor code that feels noisy, repetitive, or overly abstract
  • follow-up implementation left duplicate logic, dead code, wrapper layers, boundary leaks, or weak regression coverage
  • the user wants a reviewer-only anti-slop pass via --review
  • the goal is simplification and cleanup, not new feature delivery

When Not to Use

Do not use this skill when:

  • the task is mainly a new feature build or product change
  • the user wants a broad redesign instead of an incremental cleanup pass
  • the request is a generic refactor with no simplification or anti-slop intent
  • behavior is too unclear to protect with tests or a concrete verification plan

OMC Execution Posture

  • Preserve behavior unless the user explicitly asks for behavior changes.
  • Lock behavior with focused regression tests first whenever practical.
  • Write a cleanup plan before editing code.
  • Prefer deletion over addition.
  • Reuse existing utilities and patterns before introducing new ones.
  • Avoid new dependencies unless the user explicitly requests them.
  • Keep diffs small, reversible, and smell-focused.
  • Stay concise and evidence-dense: inspect, edit, verify, and report.
  • Treat new user instructions as local scope updates without dropping earlier non-conflicting constraints.

Review Mode (--review)

--review is a reviewer-only pass after cleanup work is drafted. It exists to preserve explicit writer/reviewer separation for anti-slop work.

  • Writer pass: make the cleanup changes with behavior locked by tests.
  • Reviewer pass: inspect the cleanup plan, changed files, and verification evidence.
  • The same pass must not both write and self-approve high-impact cleanup without a separate review step.

In review mode:

  1. Do not start by editing files.
  2. Review the cleanup plan, changed files, and regression coverage.
  3. Check specifically for:
    • leftover dead code or unused exports
    • duplicate logic that should have been consolidated
    • needless wrappers or abstractions that still blur boundaries
    • missing tests or weak verification for preserved behavior
    • cleanup that appears to have changed behavior without intent
  4. Produce a reviewer verdict with required follow-ups.
  5. Hand needed changes back to a separate writer pass instead of fixing and approving in one step.

Workflow

  1. Protect current behavior first

    • Identify what must stay the same.
    • Add or run the narrowest regression tests needed before editing.
    • If tests cannot come first, record the verification plan explicitly before touching code.
  2. Write a cleanup plan before code

    • Bound the pass to the requested files or feature area.
    • List the concrete smells to remove.
    • Order the work from safest deletion to riskier consolidation.
  3. Classify the slop before editing

    • Duplication — repeated logic, copy-paste branches, redundant helpers
    • Dead code — unused code, unreachable branches, stale flags, debug leftovers
    • Needless abstraction — pass-through wrappers, speculative indirection, single-use helper layers
    • Boundary violations — hidden coupling, misplaced responsibilities, wrong-layer imports or side effects
    • Missing tests — behavior not locked, weak regression coverage, edge-case gaps
  4. Run one smell-focused pass at a time

    • Pass 1: Dead code deletion
    • Pass 2: Duplicate removal
    • Pass 3: Naming and error-handling cleanup
    • Pass 4: Test reinforcement
    • Re-run targeted verification after each pass.
    • Do not bundle unrelated refactors into the same edit set.
  5. Run the quality gates

    • Keep regression tests green.
    • Run the relevant lint, typecheck, and unit/integration tests for the touched area.
    • Run existing static or security checks when available.
    • If a gate fails, fix the issue or back out the risky cleanup instead of forcing it through.
  6. Close with an evidence-dense report Always report:

    • Changed files
    • Simplifications
    • Behavior lock / verification run
    • Remaining risks

Usage

  • /oh-my-claudecode:ai-slop-cleaner <target>
  • /oh-my-claudecode:ai-slop-cleaner <target> --review

Good Fits

Good: deslop this module: too many wrappers, duplicate helpers, and dead code

Good: cleanup the AI slop in src/auth and tighten boundaries without changing behavior

Bad: refactor auth to support SSO

Bad: clean up formatting

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