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Plan Refactor

Community
danielvm-git
plan-refactor

Create a detailed refactor plan with tiny commits via user interview, then save it as specs/REFACTOR_LATEST.md. Use when user wants to plan a refactor, create a refactoring RFC, or break a refactor into safe incremental steps.

Overview

Publisherdanielvm-git
Repositorybigpowers
Skill nameplan-refactor
Stars
206
Forks
18
Bundled files
Instructions only
LicenseMIT
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 danielvm-git on GitHub. Read the source before you install it.

Installation

Install the Plan Refactor 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/danielvm-git/bigpowers.git /tmp/bigpowers
mkdir -p .claude/skills
cp -r /tmp/bigpowers/skills/plan-refactor .claude/skills/plan-refactor
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Plan Refactor 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 Plan Refactor 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 Plan Refactor 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.

Plan Refactor

HARD GATEHARD GATE — Before refactoring, document the current behavior and why it is wrong. Extract one invariant that must be preserved. If you skip this, you will break things you don't expect.

Create a detailed refactor plan through a user interview. Save output to specs/REFACTOR_LATEST.md.

Steps

  1. Ask the user for a long, detailed description of the problem they want to solve and any potential ideas for solutions.

  2. Explore the repo to verify their assertions and understand the current state of the codebase.

  3. Ask whether they have considered other options, and present other options to them.

  4. Interview the user about the implementation. Be extremely detailed and thorough.

  5. Hammer out the exact scope of the implementation. Work out what you plan to change and what you plan not to change.

  6. Look in the codebase to check for test coverage of this area. If there is insufficient test coverage, ask the user what their plans for testing are.

  7. Break the implementation into a plan of tiny commits. Remember Martin Fowler's advice: "make each refactoring step as small as possible, so that you can always see the program working."

  8. Save the refactor plan to specs/REFACTOR_LATEST.md. Create the specs/ directory if it doesn't exist.

Problem Statement

The problem that the developer is facing, from the developer's perspective.

Solution

The solution to the problem, from the developer's perspective.

Commits

A LONG, detailed implementation plan. Write the plan in plain English, breaking down the implementation into the tiniest commits possible. Each commit should leave the codebase in a working state.

Each commit entry follows this format:

N. <commit description> → verify: <runnable command>

Decision Document

A list of implementation decisions that were made:

  • The modules that will be built/modified
  • The interfaces of those modules that will be modified
  • Technical clarifications from the developer
  • Architectural decisions
  • Schema changes, API contracts, specific interactions

Do NOT include specific file paths or code snippets. They may end up being outdated very quickly.

Testing Decisions

  • A description of what makes a good test (only test external behavior, not implementation details)
  • Which modules will be tested
  • Prior art for the tests (i.e. similar types of tests in the codebase)

Out of Scope

A description of the things that are out of scope for this refactor.

Further Notes (optional)

Any further notes about the refactor.

After writing specs/REFACTOR_LATEST.md, suggest running kickoff-branch next to create a refactor branch.

References

Verify

Frequently asked questions

What does the Plan Refactor AI skill do?

Create a detailed refactor plan with tiny commits via user interview, then save it as specs/REFACTOR_LATEST.md. Use when user wants to plan a refactor, create a refactoring RFC, or break a refactor into safe incremental steps.

Why use Plan Refactor on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/danielvm-git/bigpowers/tree/main/skills/plan-refactor. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Plan Refactor?

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 Plan Refactor?

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

Is the Plan Refactor AI skill free?

Yes. It is published on GitHub by danielvm-git under the MIT license. 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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