ai-slop-cleaner

Remove AI-generated dead code and duplication while preserving behavior.

Updated Apr 20, 2026
One-click install
npx skills add https://github.com/hotaq/Sprite_harmess --skill ai-slop-cleaner-hotaq
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: ai-slop-cleaner
Source: https://github.com/hotaq/Sprite_harmess/tree/main/.codex/skills/ai-slop-cleaner
Command: npx skills add https://github.com/hotaq/Sprite_harmess --skill ai-slop-cleaner-hotaq

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps remove AI-generated clutter, duplication, dead code, and weak abstractions from working code while preserving behavior and improving signal quality.

Core Features & Use Cases

  • Regression-first cleanup: Locks behavior with targeted tests before any edits are made.
  • Scoped refactoring: Keeps changes bounded to the requested files or feature area, including changed-file lists.
  • Fallback review: Identifies masking fallbacks, grounded compatibility paths, and escalation needs before code changes.
  • Quality verification: Re-runs tests, lint, and type checks after each cleanup pass.
  • Use case: A developer asks to deslop a noisy implementation after AI-assisted coding left behind duplicate branches, dead helpers, and unclear error handling.

Quick Start

Ask the agent to clean up the selected code path with regression tests first, keep the refactor bounded to the stated scope, and report the simplified changes with verification results.

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 code without breaking existing behavior?

To clean up AI-generated code without breaking behavior, lock the current functionality with targeted regression tests first, then refactor duplicate branches and dead code within bounded file scopes while verifying with lint and type checks.

What is AI code slop and when should I refactor it?

AI code slop is the duplicate branches, dead helpers, and unclear error handling left by AI-assisted coding. You should refactor it when a working codebase has noisy implementations that reduce signal quality and require fallback review.

How do I remove dead code and duplicate branches from my codebase safely?

Remove dead code and duplicate branches safely by applying regression-first cleanup, identifying masking fallbacks and grounded compatibility paths, and re-running targeted tests, lint, and type checks after each deletion pass.

Can I scope an AI code cleanup to only the changed files in my feature branch?

Yes, you can scope an AI code cleanup to only changed files in your feature branch. The deslop workflow keeps refactoring bounded to the requested file lists or feature areas to ensure changes remain isolated and verifiable through targeted tests.

What are the limitations of automated dead code deletion during refactoring?

A limitation of automated dead code deletion during refactoring is that it requires regression tests and fallback classification beforehand, otherwise you risk removing grounded compatibility paths or masking fallbacks that the cleanup process cannot safely detect.