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Deslop

CommunityPopular
rohitg00
deslop

Remove AI-generated code slop, unnecessary comments, and over-engineering from the current branch diff. Cleans up boilerplate, simplifies abstractions, strips defensive code, and in skill-file mode lints SKILL.md files for quality. Use when cleaning up code, simplifying, removing boilerplate, before committing, or when reviewing a skill before promoting it.

Overview

Publisherrohitg00
Repositorypro-workflow
Skill namedeslop
Stars
2.9K
Forks
286
Bundled files
Instructions only
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by rohitg00 on GitHub. Read the source before you install it.

Installation

Install the Deslop AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/rohitg00/pro-workflow.git /tmp/pro-workflow
mkdir -p .claude/skills
cp -r /tmp/pro-workflow/skills/deslop .claude/skills/deslop
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Deslop in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Deslop on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Deslop is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Remove AI Code Slop

Check the diff against main and remove AI-generated slop introduced in the branch.

Trigger

Use after completing changes, before committing, or when code feels over-engineered.

Commands

bash
git fetch origin main
git diff origin/main...HEAD --stat
git diff origin/main...HEAD

Workflow

  1. Run diff commands to see all changes on the branch.
  2. Identify slop patterns from the focus areas below.
  3. Apply minimal, focused edits to remove slop.
  4. Re-run git diff origin/main...HEAD to verify only slop was removed.
  5. Run tests or type-check to confirm behaviour unchanged: npm test -- --changed --passWithNoTests 2>&1 | tail -10
  6. Summarise what was cleaned.

Focus Areas

  • Extra comments that state the obvious or are inconsistent with local style
  • Defensive try/catch blocks that are abnormal for trusted internal code paths
  • Casts to any used only to bypass type issues
  • Over-engineered abstractions for one-time operations (premature helpers, factories)
  • Deeply nested code that should be simplified with early returns
  • Backwards-compatibility hacks (renamed _vars, re-exports, // removed comments)
  • Features, refactoring, or "improvements" beyond what was requested
  • Added docstrings, type annotations, or comments on code that wasn't changed
  • Error handling for scenarios that can't happen in trusted internal paths

Guardrails

  • Keep behavior unchanged unless fixing a clear bug.
  • Prefer minimal, focused edits over broad rewrites.
  • Three similar lines of code is better than a premature abstraction.
  • If you remove something, verify it's truly unused first.
  • Keep the final summary concise (1-3 sentences).

Skill-file mode

When the target is a SKILL.md (not a code diff), lint it against the same slop instinct applied to prose. Run this before promoting a skill. Flag:

  • Stale lines - guidance written for an old version of the skill that no longer matches what it does. Cut it.
  • Bloat - the skill runs past one screen with detail that belongs in a linked reference. Push it down: in-skill step, then in-skill reference, then an external file behind a pointer.
  • Dead sentences - a line that changes nothing if deleted. Delete it.
  • Duplication - the same instruction stated in two places, so edits drift. Keep one source of truth.
  • Premature stop - the method ends before the work does (asks the question but never records the answer, cleans but never verifies).
  • Weak anchor - no single concept the skill turns on. A skill the reader can name in one word triggers and executes in fewer tokens.
  • Missing invocation intent - no declared human-run vs auto-triggered mode. See rules/skill-conventions.mdc.
  • Wrong write op - a state-changing skill that does not say whether it adds, updates, or appends, or that duplicates its output on a second run.

Skill-file mode output: the flagged issues by line, the edits applied, the cleanup summary, and whether the skill is ready to promote.

Output (code mode)

  • List of slop patterns found with file locations
  • Edits applied
  • One-line summary of what was cleaned

Frequently asked questions

What does the Deslop AI skill do?

Remove AI-generated code slop, unnecessary comments, and over-engineering from the current branch diff. Cleans up boilerplate, simplifies abstractions, strips defensive code, and in skill-file mode lints SKILL.md files for quality. Use when cleaning up code, simplifying, removing boilerplate, before committing, or when reviewing a skill before promoting it.

Why use Deslop on TypingMind?

Because you install it once and use it with any model. Deslop is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Deslop in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/rohitg00/pro-workflow/tree/main/skills/deslop. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Deslop?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Deslop?

As many as you like. As long as a model supports skills, you can use Deslop with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Deslop AI skill free?

It is published on GitHub by rohitg00. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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