Refactor Apply logo

Refactor Apply

Organization
greenfield-inc
refactor-apply

Applies a refactor plan written by refactor-simple, refactor-deep, or the refactor orchestrator's merged report - auto-fixable items first, then manual items one at a time with the user, verifying with the repo's own checks after each group. Use only after the user has reviewed the plan and said to apply it.

Overview

Publishergreenfield-inc
RepositoryPane
Skill namerefactor-apply
Stars
529
Forks
227
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 greenfield-inc on GitHub. Read the source before you install it.

Installation

Install the Refactor Apply 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.
    https://github.com/greenfield-inc/Pane/tree/main/main/src/services/paneChatBundle/skills/refactor-apply
  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/greenfield-inc/Pane.git /tmp/Pane
mkdir -p .claude/skills
cp -r /tmp/Pane/main/src/services/paneChatBundle/skills/refactor-apply .claude/skills/refactor-apply
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Refactor Apply 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 Refactor Apply 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 Refactor Apply 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.

Refactor Apply

Turns a reviewed plan into edits. Never runs unasked; the plan it consumes was shown to the user first, by refactor or by the user invoking an analysis directly.

Input

One plan file: an individual ./tmp/simple-refactor-plan-*.md or ./tmp/deep-refactor-plan-*.md, or the orchestrator's ./tmp/refactor-merged-*.md. All three share the same shape - Critical / Warning / Info sections, each item with file:line, a fix, and an Auto-fixable: Yes/No flag.

Process

1. Read the plan and the repo's checks

Parse every item. Then find what "passing" means in this repository - its lint, typecheck, and test commands from package.json, Makefile, CLAUDE.md or AGENTS.md. Run them once before touching anything so a pre-existing failure is not mistaken for one you caused.

2. Auto-fixable first

Apply every Auto-fixable: Yes item, grouped by file. Rules:

  • Change only the lines the finding names and what the fix strictly requires. A refactor pass does not widen a PR's scope.
  • Never alter behaviour to satisfy a convention; if a fix would, it is not auto-fixable - move it to manual and say why.
  • After the group, run the repo's checks. Fix straightforward failures you introduced; revert an item you cannot make pass and report it.

--auto-only stops here with a summary.

3. Manual, one at a time with the user

For each Auto-fixable: No item, in plan priority order - Critical first: state the finding, the proposed change, and any judgment call it needs; wait for the user's answer; apply; run the checks. The user may skip any item; a skipped Critical is recorded, not argued.

4. Report

Applied: X auto-fixable, Y manual (Z skipped by user)
Checks: [each command] PASS/FAIL
Reverted: [items that could not pass, with reason]
Left for follow-up: [skipped or out-of-scope items]

Do not commit. The user (or prepare-pr) owns the commit, and the diff should be reviewable as its own step.

Rules

  • No blanket rewrites; every edit traces to a plan item.
  • Behaviour-preserving only. If a change would alter behaviour, it needs the user's explicit yes and a test.
  • Pre-existing debt marked "not against this PR" is not applied unless the user asks for it by name.
  • Secrets, credentials, and generated files are stop conditions.

Frequently asked questions

What does the Refactor Apply AI skill do?

Applies a refactor plan written by refactor-simple, refactor-deep, or the refactor orchestrator's merged report - auto-fixable items first, then manual items one at a time with the user, verifying with the repo's own checks after each group. Use only after the user has reviewed the plan and said to apply it.

Why use Refactor Apply on TypingMind?

Because you install it once and use it with any model. Refactor Apply 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 Refactor Apply in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/greenfield-inc/Pane/tree/main/main/src/services/paneChatBundle/skills/refactor-apply. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Refactor Apply?

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 Refactor Apply?

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

Is the Refactor Apply AI skill free?

It is published on GitHub by greenfield-inc. 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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