ai-slop-cleanerlisted

# AI Slop Cleaner Skill Reduce AI-generated slop with a regression-tests-first, smell-by-smell cleanup workflow that preserves behavior and raises signal quality. ## When to Use Use this skill when: - A code path works but feels bloated, noisy, repetitive, or over-abstracted - A user asks to “cleanup”, “refactor”, or “deslop” AI-generated output - Follow-up implementation left duplicate code, dead code, weak boundaries, missing tests, or unnecessary wrapper layers - You need a disciplined cleanup workflow without broad rewrites ## GPT-5.4 Guidance Alignment - Keep outputs concise and evidence-dense unless risk or the user requests more detail. - Treat newer user instructions as local workflow updates without discarding earlier non-conflicting constraints. - Keep using inspection, tests, diagnostics, and verification until the cleanup is grounded. - Proceed automatically through clear, reversible cleanup steps; ask only when a choice materially changes scope or behavior. ## Scoped File Lists and Ralph Workflow - This skill can accept a **file list scope** instead of a whole feature area. - When the caller provides a changed-files list (for example, Ralph session-owned edits), keep the cleanup strictly bounded to those files. - In the **Ralph workflow**, the mandatory deslop pass should run this skill on Ralph's changed files only, in standard mode unless the caller explicitly requests otherwise. ## Procedure 1. **Lock behavior with regression tests first** - Identi