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deslop

Detect and remove debugging traces, placeholder text, and dead code from repositories.

951|110|Updated Jan 15, 2026
Search Tags:#automation#static-analysis#dead-code#code-cleanup#deslop#debug-statements
One-click install
npx skills add https://github.com/avifenesh/awesome-slash --skill deslop-avifenesh
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: deslop
Source: https://github.com/avifenesh/awesome-slash/tree/main/plugins/deslop/skills/deslop
Command: npx skills add https://github.com/avifenesh/awesome-slash --skill deslop-avifenesh

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

Clean AI slop from code to improve readability, remove debugging traces, and prune ghost or unused code to keep repositories maintainable.

Core Features & Use Cases

  • Deterministic detection of debug statements, placeholder text, and dead code
  • Auto-fix capable cleanup workflows to reduce noise in PRs
  • Suitable for routine hygiene passes, post-LLM generation cleanup, and pre-release hardening

Quick Start

Run the detection pipeline on your project and apply fixes as needed.

Frequently Asked Questions about deslop

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

FAQPage Schema
How do I automatically remove AI-generated debug statements and placeholder text from my codebase?▼

To remove AI-generated debug statements and placeholder text, run a deterministic detection pipeline that scans your codebase, identifies hygiene issues, and applies optional auto-fixes to clean the code.

What is the best way to clean up dead code before a release?▼

The best way to clean up dead code before a release is using a two-phase static analysis pipeline that detects unused code and ghost functions, returning structured findings for optional auto-fix application.

How does static analysis identify and prune ghost code in any programming language?▼

Static analysis identifies ghost code by running a deterministic detection phase followed by optional repo-map analysis, scanning across any language repository to locate and flag unused code for removal.

Can I use automated code cleanup for routine maintenance on repositories with mixed languages?▼

Yes, automated code cleanup applies to routine maintenance across any language repository, deterministically detecting debugging traces and dead code to keep mixed-language codebases maintainable.

Does the auto-fix workflow support reducing noise in pull requests after LLM generation?▼

Yes, the auto-fix workflow supports post-LLM generation cleanup by deterministically removing debugging traces, placeholder text, and dead code, which significantly reduces noise in pull requests.

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