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Worktree Pr

Community
scarletkc
worktree-pr

Decide whether a task deserves its own git worktree and, if chosen, run it end to end: branch from the integration branch rather than the current tree, keep the main working copy untouched while the task runs, compare the result against the untouched baseline before declaring it done, and prepare it for a pull request instead of merging. Use when a request says to do the work in a new worktree or branch, when a change is large or risky enough that the main tree should stay usable, when several tasks need to run in parallel on one repository, when a result has to be diffed against current behavior, and when deciding where screenshots, builds, and other artifacts produced in a worktree should end up.

Overview

Publisherscarletkc
Repositoryagents
Skill nameworktree-pr
Stars
225
Forks
12
Bundled files
Instructions only
LicenseApache-2.0
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 scarletkc on GitHub. Read the source before you install it.

Installation

Install the Worktree Pr 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/scarletkc/agents/tree/main/skills/worktree-pr
  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/scarletkc/agents.git /tmp/agents
mkdir -p .claude/skills
cp -r /tmp/agents/skills/worktree-pr .claude/skills/worktree-pr
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Worktree Pr 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 Worktree Pr 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 Worktree Pr 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.

Worktree & PR

A worktree buys two things: the main working copy stays usable while the task runs, and the untouched copy remains available as a baseline to compare against. Both are worth real setup cost, and neither applies to every change.

This covers the isolation mechanics. How large the change itself should be is scoped-change, and it applies inside a worktree exactly as it does anywhere else.

Deciding

Consider a worktree when at least one holds: the task is large enough that a half-finished state would block other work, several tasks need to progress on the same repository at once, the result has to be compared against current behavior, or the change is risky enough that abandoning it should cost nothing.

Skip it when the change is small, self-contained, and reviewable in one pass. Setting up an isolated copy for a typo fix or a one-line config edit costs more than it saves, and the extra branch, directory, and PR are all overhead that someone pays later. When the requester says to work directly on the current branch, that decision is already made.

Running

  • Branch from the integration branch, not from whatever is checked out. The point of the isolated copy is a clean starting state; inheriting unrelated in-progress edits forfeits it and makes the eventual diff unreadable. Fetch first so the base is current, not a stale local ref.
  • Leave the main working copy alone while the task runs. Editing both defeats the isolation and destroys the baseline. If the task turns out to need a change in the main tree, stop and say so rather than reaching across.
  • Parallel worktrees stay independent only while they stay disjoint. Two copies of one repository editing the same files converge into a conflict nobody scheduled, and the cost lands at merge time rather than now. Before opening a second one, check what the first is touching.
  • Name the artifacts' destination explicitly. Screenshots, builds, and exports produced inside a worktree vanish with it. Anything the requester needs to see must be written somewhere durable, or attached to the PR, and the location has to be stated rather than assumed.

Before declaring it done

  • Compare against the untouched baseline, not against expectation. The reason to keep a clean copy is to run both and see the difference. For behavior changes this means exercising the old path and the new one; for visual changes it means the same view captured twice. "Should be equivalent" is a claim, and the baseline is right there to check it.
  • Account for what the tooling added. Generated output, formatter churn, and dependency lock updates accumulate in an isolated copy without anyone choosing them, and they are indistinguishable from intent once merged. Either explain why each belongs in this branch, or drop it.

Landing

Follow the user's established authorization preferences. If committing, pushing, or opening a pull request requires explicit authorization, complete and validate the local changes, then hand over the exact commands until authorized. When authorized, push the branch and open a pull request describing motivation, the commands exercised, and anything reviewers must check by hand; leave merging to the repository owner unless told otherwise. Say plainly which parts are done, which are unverified, and which were deliberately left out, since a worktree's isolation makes it easy to report an untested result as finished. Once the branch has landed, remove the worktree; a stale copy of a merged branch is a trap for the next session that opens it.

Frequently asked questions

What does the Worktree Pr AI skill do?

Decide whether a task deserves its own git worktree and, if chosen, run it end to end: branch from the integration branch rather than the current tree, keep the main working copy untouched while the task runs, compare the result against the untouched baseline before declaring it done, and prepare it for a pull request instead of merging. Use when a request says to do the work in a new worktree or branch, when a change is large or risky enough that the main tree should stay usable, when several tasks need to run in parallel on one repository, when a result has to be diffed against current be...

Why use Worktree Pr on TypingMind?

Because you install it once and use it with any model. Worktree Pr 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 Worktree Pr in TypingMind?

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

Which AI models can use Worktree Pr?

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 Worktree Pr?

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

Is the Worktree Pr AI skill free?

Yes. It is published on GitHub by scarletkc under the Apache-2.0 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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