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ai-slop-cleaner

Enforce a regression-tests-first cleanup workflow for AI-generated code slop.

1|Updated Mar 17, 2025
Search Tags:#planning#ai#cleanup#quality#refactor#code-smells#regression-tests
One-click install
npx skills add https://github.com/ozby/node-pubsub --skill ai-slop-cleaner-ozby
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: ai-slop-cleaner
Source: https://github.com/ozby/node-pubsub/tree/main/.codex/skills/ai-slop-cleaner
Command: npx skills add https://github.com/ozby/node-pubsub --skill ai-slop-cleaner-ozby

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Reduce AI-generated slop by applying a regression-tests-first, smell-by-smell cleanup workflow that preserves behavior and raises signal quality.

Core Features & Use Cases

  • Regression-testing-first cleanup plan that prioritizes high-signal smells
  • Scoped changes to a file list or feature area with explicit planning
  • Structured passes (dead code deletion, duplicate removal, naming/error handling cleanup) and validation through tests

Quick Start

Provide a bounded cleanup scope (e.g., changed files only) and run regression tests to begin the cleanup workflow.

Frequently Asked Questions about ai-slop-cleaner

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I clean up AI-generated slop in code without breaking existing functionality?▼

Clean up AI-generated slop safely by enforcing a regression-tests-first workflow that categorizes smells and runs gated quality checks before applying changes to preserve behavior.

What is a regression-tests-first cleanup workflow for AI code outputs?▼

A regression-tests-first cleanup workflow requires defining a cleanup plan, running regression tests, categorizing code smells, and passing quality gates before applying staged changes to AI-generated code.

How do I scope code refactoring to only clean up AI slop in changed files?▼

Scope code refactoring by providing a bounded cleanup scope like a changed-files list or feature area, ensuring the structured passes for dead code and duplicate removal only target those specific paths.

Can I remove dead code and duplicates from AI outputs while maintaining behavior?▼

Yes, you can remove dead code and duplicates from AI outputs by running structured cleanup passes and validating the changes through regression tests to ensure original behavior is strictly maintained.

Do I need to define a cleanup plan before resolving code smells in AI-generated code?▼

Yes, you must define an explicit cleanup plan before resolving code smells to prioritize high-signal issues and ensure changes are gated by regression tests and quality checks.

When should I avoid using automated cleanup on AI-generated code paths?▼

Avoid automated cleanup on AI-generated code paths when you cannot establish a bounded scope or provide regression tests, as the workflow requires defined plans and test validation to safely apply changes.

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