ai-slop-cleaner
Run an anti-slop cleanup/refactor/deslop workflow
Best use case
ai-slop-cleaner is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Run an anti-slop cleanup/refactor/deslop workflow
Teams using ai-slop-cleaner should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/ai-slop-cleaner/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How ai-slop-cleaner Compares
| Feature / Agent | ai-slop-cleaner | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Run an anti-slop cleanup/refactor/deslop workflow
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
# AI Slop Cleaner Skill Reduce AI-generated slop with a regression-tests-first, smell-by-smell cleanup workflow that preserves behavior and raises signal quality. ## When to Use Use this skill when: - A code path works but feels bloated, noisy, repetitive, or over-abstracted - A user asks to “cleanup”, “refactor”, or “deslop” AI-generated output - Follow-up implementation left duplicate code, dead code, weak boundaries, missing tests, or unnecessary wrapper layers - You need a disciplined cleanup workflow without broad rewrites ## GPT-5.4 Guidance Alignment - Keep outputs concise and evidence-dense unless risk or the user requests more detail. - Treat newer user instructions as local workflow updates without discarding earlier non-conflicting constraints. - Keep using inspection, tests, diagnostics, and verification until the cleanup is grounded. - Proceed automatically through clear, reversible cleanup steps; ask only when a choice materially changes scope or behavior. ## Scoped File Lists and Ralph Workflow - This skill can accept a **file list scope** instead of a whole feature area. - When the caller provides a changed-files list (for example, Ralph session-owned edits), keep the cleanup strictly bounded to those files. - In the **Ralph workflow**, the mandatory deslop pass should run this skill on Ralph's changed files only, in standard mode unless the caller explicitly requests otherwise. ## Procedure 1. **Lock behavior with regression tests first** - Identify the behavior that must not change - Add or run targeted regression tests before editing cleanup candidates - If behavior is currently untested, create the narrowest test coverage needed first 2. **Create a cleanup plan before code** - List the specific smells to remove - Bound the pass to the requested files/scope - If a file list scope is provided, keep the pass restricted to that changed-files list - Order fixes from safest/highest-signal to riskiest - Do not start coding until the cleanup plan is explicit 3. **Categorize issues 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, leaky responsibilities, wrong-layer imports or side effects - **Missing tests** — behavior not locked, weak regression coverage, gaps around edge cases 4. **Execute passes one smell at a time** - **Pass 1: Dead code deletion** - **Pass 2: Duplicate removal** - **Pass 3: Naming/error handling cleanup** - **Pass 4: Test reinforcement** - Re-run targeted verification after each pass - Avoid bundling unrelated refactors into the same edit set 5. **Run quality gates** - Regression tests stay green - Lint passes - Typecheck passes - Relevant unit/integration tests pass - Static/security scan passes when available - Diff stays minimal and scoped - No new abstractions or dependencies unless explicitly required 6. **Finish with an evidence-dense report** - Changed files - Simplifications made - Tests/diagnostics/build checks run - Remaining risks - Residual follow-ups or consciously deferred cleanup ## Output Format ```text 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] ``` ## Scenario Examples **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.
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