# Omh AI Slop Cleaner

[omh] Messy or AI-generated code to clean up: delete AI-generated slop, dead code, and...

- Repository: https://github.com/rlaope/oh-my-hermes (5004 stars)
- Category: Engineering
- License: MIT
- Last updated: 2026-11-01
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add rlaope/oh-my-hermes --skill omh-ai-slop-cleaner -g -a claude-code -y`
Codex: `npx skills add rlaope/oh-my-hermes --skill omh-ai-slop-cleaner -g -a codex -y`
Cursor: `npx skills add rlaope/oh-my-hermes --skill omh-ai-slop-cleaner -g -a cursor -y`
Gemini CLI: `npx skills add rlaope/oh-my-hermes --skill omh-ai-slop-cleaner -g -a gemini-cli -y`

## Description

[omh] Messy or AI-generated code to clean up: delete AI-generated slop, dead code, and duplication while observable behavior stays identical. Use when the user says: ai-slop-cleaner, cleanup, deslop, refactor, risky, behavior-preserving refactor, risk analysis, refactor workflow.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# Ai Slop Cleaner

This is an OMH `ai-slop-cleaner` workflow skill, projected for Agent Skills hosts (Claude Code, Codex, Cursor, opencode, OpenClaw, pi).

## Why This Exists

`ai-slop-cleaner` exists to keep `maintenance` work explicit, evidence-backed, and inside the Hermes/executor boundary instead of relying on ad hoc chat narration.

## Do Not Use When

- The goal is new or changed behavior rather than removing existing code; a plain refactor, feature, or fix request belongs to `ulw-work`.
- The cleanup would change architecture or module boundaries and needs its execution shaped into phases first; use `omh-refactor-plan`, or `ulw-plan` when the direction itself is still contested.
- The user wants code judged for bugs or merge readiness with no drafted slop removal to inspect; use `omh-code-review` for a bug-first review and `omh-failure-signal-audit` for swallowed failures.

## Examples

Good example:

- Prompt: $ai-slop-cleaner remove duplicated router branches and lock behavior with regression tests before refactoring.
- Expected behavior: Plan cleanup, preserve behavior, delete or simplify code, and prove it with targeted tests.
- Why: The request is maintenance cleanup with regression risk.

Bad example:

- Prompt: ai-slop-cleaner: treat casual chat or unaccepted work as if this workflow already produced verified results.
- Expected behavior: Ask a clarification question or route to a narrower workflow instead of forcing `ai-slop-cleaner`.
- Why: The request lacks the required inputs or would overclaim work that Hermes did not observe.

## Completion Checklist

The rest: https://github.com/rlaope/oh-my-hermes/blob/HEAD/agent-skills/omh-ai-slop-cleaner/SKILL.md