AI Slop Cleaner Task Card
SkillDev toolsThe ai-slop-cleaner skill runs an anti-slop cleanup/refactor/deslop workflow for code that has become bloated, noisy, repetitive, over-abstracted, or AI-generated. It locks existing behavior with regression tests, inventories suspicious patterns such as swallowed errors and unnecessary abstractions, then runs ordered passes covering dead-code deletion, duplication removal, naming and error-handling cleanup, and test reinforcement. It finishes with a report listing changes, quality gates, and remain
Available today. Use it from your connected AI after setup.
No other account needed.
Have the working code, the requested feature or files, and the behavior to preserve.
Then ask your AI: use the AI Slop Cleaner Task Card skill
What your AI can do with it
- Lock behavior with targeted regression tests before editing
- Inventory fallback-like code such as swallowed errors and silent defaults
- Classify smells including duplication, dead code, and needless abstraction
- Run ordered cleanup passes for dead code, duplication, naming, and errors
- Reinforce tests and produce a report of changes and remaining risks
Getting started
- Have the working code, the requested feature or files, and the behavior to preserve.
- Identify the behavior to preserve and run or add the narrowest targeted tests.
- Create a cleanup plan listing scope, smells, and ordered fixes before editing.
- Inventory fallback-like code in scope and classify each finding.
- Run the ordered passes and finish with a report of changes, quality gates, and remaining risks.
What this skill tells your AI
The instructions your AI receives, as published by yeachan-heo/oh-my-codex in skills/ai-slop-cleaner/SKILL.md and read by ahel’s review.
Use this bounded helper for cleanup/refactor/deslop work, not as a competing top-level
workflow. Shared operating invariants live in templates/AGENTS.md; this card defines
scope, smell taxonomy, passes, and evidence.
When to use and inputs
Use when working code is bloated, noisy, repetitive, over-abstracted, or AI-generated; the user requests cleanup/refactor/deslop; or a follow-up left duplicate/dead code, weak boundaries, missing tests, fallback-like paths, or wrappers. Inputs are the requested feature/files and behavior to preserve. A file list scope is valid; keep the pass bounded to it. Limit the pass to the calling task's changed files unless broader cleanup was requested.
Before editing
- Lock behavior with regression tests first: identify behavior to preserve, run/add the narrowest targeted tests, and cover both primary and preserved compatibility/fail-safe fallback paths.
- Create a cleanup plan before code: list scope and smells, include fallback findings/classifications/escalation, and order safest/highest-signal fixes first.
- Inventory fallback-like code in scope: quick hacks, temporary workaround, temporary fallback, just bypass, just skip, fallback if it fails, swallowed errors, silent defaults, broad compatibility shims, and duplicate alternate execution paths.
- Classify each fallback: Masking fallback slop hides evidence, bypasses the contract, suppresses validation, swallows failures, silently defaults, or adds untested paths; Grounded compatibility/fail-safe fallback is narrow at an external/version/fail-safe boundary, documents rationale, preserves failure evidence, and tests primary plus fallback.
- Prefer root-cause repair, deletion, boundary repair, or explicit failure behavior. For broad/ambiguous/cross-layer/architectural findings, invoke
$ralplanfor consensus resolution; when already inside ralplan, ultragoal, team, or another OMX workflow, do not spawn a nested$ralplan—attach the finding to the active handoff.
Smell taxonomy and passes
Classify before changing:
- Fallback-like code: masking fallbacks, workaround branches, bypasses, swallowed errors, silent defaults, broad shims, alternate paths.
- Duplication: repeated logic, copy-paste branches, redundant helpers.
- Dead code: unused/unreachable code, stale flags, debug leftovers.
- Needless abstraction: pass-through wrappers, speculative indirection, single-use layers.
- Boundary violations: hidden coupling, leaky responsibilities, wrong-layer imports/side effects.
- Missing tests: behavior not locked or edge cases uncovered.
- UI/design slop: context-sensitive signals, not absolute bans; preserve intentional brand, design-system, accessibility, or product-context exceptions. Challenge Korean body text at 11-12px (generally 14px or larger); gratuitous box shadows; repetitive eyebrow + title + description + paragraph stacks and generic emoji badges; default AI blue/purple such as
#3B82F6; reflexive 3-column or 4-column grids; and extreme gradients unless justified by context.
Resolve the fallback-like code resolution gate first, then 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 and avoid unrelated refactors. Prefer deletion/existing utilities; no new abstractions or dependencies unless explicitly required.
Evidence/output contract
Report:
AI SLOP CLEANUP REPORT
Scope: [files/feature]
Behavior Lock: [targeted tests added/run]
Cleanup Plan: [bounded smells/order]
Fallback Findings: [finding -> masking fallback slop | grounded compatibility/fail-safe fallback -> escalation]
UI/Design Findings: [none/N/A or signal -> action/defer -> intentional rationale]
Passes Completed: [resolution gate; Passes 1-4]
Quality Gates: Regression tests, Lint, Typecheck, Tests, Static/security scan (PASS/FAIL/N/A)
Changed Files: [path -> simplification]
Remaining Risks: [none or deferred item]
Include changed files, simplifications, fallback classifications/escalation status, tests/diagnostics/build checks run, UI findings when relevant, and deferred risks. Keep writer/reviewer separation for cleanup plans and approvals.
Exit condition
Stop when the requested scope has behavior-lock evidence, each selected smell pass is complete or explicitly deferred with rationale, verification is reported, and no unrelated files or temporary artifacts remain. Never present an unverified cleanup as complete; escalate a real architectural blocker rather than masking it.
Signals
- GitHub stars
- 33k
- Forks
- 3k
- Last commit
- Oct 2026
Questions
- When should I use this skill?
- Use it when working code is bloated, noisy, repetitive, over-abstracted, or AI-generated; when cleanup, refactor, or deslop is requested; or when a follow-up left duplicate or dead code, weak boundaries, missing tests, fallback-like paths, or wrappers.
- What inputs does it need?
- The requested feature or files and the behavior to preserve. A file list scope is valid; keep the pass bounded to it. Limit the pass to the calling task's changed files unless broader cleanup was requested.
Advanced
- Item type
- skill
- Key
ai-slop-cleaner-2- Source
- github.com/yeachan-heo/oh-my-codex