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ai-slop-cleaner

Identify and eliminate code smells in AI-generated code with regression tests.

1|Updated May 7, 2026
Search Tags:#refactoring#software quality#code smells#AI code#code cleanup
One-click install
npx skills add https://github.com/zchee/json-repair-rs --skill ai-slop-cleaner-zchee
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: ai-slop-cleaner
Source: https://github.com/zchee/json-repair-rs/tree/main/.codex/skills/ai-slop-cleaner
Command: npx skills add https://github.com/zchee/json-repair-rs --skill ai-slop-cleaner-zchee

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill streamlines the process of refactoring, cleaning, and removing unnecessary or problematic code artifacts produced by AI, improving code quality and maintainability.

Core Features & Use Cases

  • Code Cleanup Workflow: Remove bloated, noisy, and redundant code sections in AI-generated outputs.
  • Refactoring Support: Detect and address issues like duplicate code, dead code, and poor abstractions.
  • Use Case: A developer asks to clean up a large AI-generated codebase that contains multiple duplicate functions and unnecessary wrappers, enabling a more concise and robust code structure.

Quick Start

instruct the AI to analyze the code snippets in the provided files and perform refactoring to improve clarity and reduce smells.

Frequently Asked Questions about ai-slop-cleaner

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

FAQPage Schema
How do I refactor and clean up AI-generated code to remove code smells?▼

This process removes unnecessary wrappers and bloated sections from AI-generated code, ensuring behavior preservation through regression tests while enabling a more concise and robust code structure.

How do I remove duplicate code and unnecessary wrappers from an AI-generated codebase?▼

You can remove duplicate code and unnecessary wrappers by running a structured cleanup plan that detects poor abstractions and redundant sections, refactoring the AI-generated codebase into a more concise structure.

What is the best way to ensure behavior preservation when refactoring AI code?▼

Regression tests validate that the refactoring process does not alter the software's external behavior, ensuring behavior preservation while continuously enhancing the quality of the AI-generated code.

Can I use automated refactoring tools for AI code without external dependencies?▼

Yes, you can perform automated refactoring and code cleanup for AI outputs without external dependencies, as the process relies entirely on core scripting capabilities to detect and address code smells.

What types of code smells are typically found in AI-generated code?▼

Typical code smells found in AI-generated code include duplicate functions, dead code, unnecessary wrappers, poor abstractions, and bloated or redundant sections that require continuous refactoring to resolve.

Does refactoring AI-generated code require setting up a specific environment?▼

Refactoring AI-generated code requires no specific environment setup or external dependencies, allowing software engineers to directly analyze provided file snippets and perform refactoring using core scripting capabilities.

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