Prepare Pr logo

Prepare Pr

Organization
greenfield-inc
prepare-pr

Prepare a branch for review by committing scoped changes, rebasing on main, running builds, and creating or updating a pull request. Use when the user wants the branch ready for PR review. Also use for rewriting an existing PR description from its current diff and evidence.

Overview

Publishergreenfield-inc
RepositoryPane
Skill nameprepare-pr
Stars
529
Forks
227
Bundled files
2
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.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by greenfield-inc on GitHub. Read the source before you install it.

Installation

Install the Prepare 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/greenfield-inc/Pane/tree/main/main/src/services/paneChatBundle/skills/prepare-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/greenfield-inc/Pane.git /tmp/Pane
mkdir -p .claude/skills
cp -r /tmp/Pane/main/src/services/paneChatBundle/skills/prepare-pr .claude/skills/prepare-pr
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Prepare 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 Prepare 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 Prepare 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.

Prepare PR

This is a high-trust workflow. Surface any destructive or ambiguous step before proceeding.

Detect and rewrite an existing PR

On invocation, resolve any supplied PR URL or query the current branch for an existing PR. If one exists, default to rewriting its description unless the user explicitly requests code/branch preparation; read the existing title/body, current diff, source ticket/discussion and available review/QA/check evidence; use the writing contract and reference to rewrite the requested narrative and refresh its Grain companion when connected. Preserve valid closing lines, relevant human context and honest tested-SHA/QA/publication limits; the request authorizes rewriting the requested prose. This mode runs only writing, visual/evidence verification and persisted-body readback: leave code, commits, branch history, labels and draft/ready state unchanged, and do not rerun application QA solely for an editorial rewrite. Report the description update separately from the PR's current readiness. Use the full workflow below when preparing code for review.

Workflow:

  1. Group current changes into logical commits, ideally by done-plan.
  2. Create focused commits without staging unrelated work.
  3. Fetch and rebase onto origin/main.
  4. Resolve obvious conflicts directly. Ask the user about semantic conflicts.
  5. Run the relevant build steps and fix straightforward failures.
  6. Create a visual PR diagram before opening/updating the PR:
    • Use the excalidraw-pr-diagrams skill.
    • Keep all generated diagram working files under /tmp, usually /tmp/codex-pr-diagrams/<branch-or-pr>/.
    • Add a ## Visual Overview section to the PR body.
    • Include explicit Before and After diagrams in the visual overview.
    • Use the rendered Excalidraw image as the primary visual. Add Mermaid only when the user requests a text-rendered fallback.
    • Reuse a repository-owned long-lived release such as pr-assets, and follow the diagram skill's unique naming, collision, manifest, and metadata/direct-content verification rules. Creating that release is a separate hard stop requiring an exact grant such as {"action":"create_release","repo":"owner/name","tag":"pr-assets"}; generic GitHub, PR, comment, or asset-upload authorization does not grant it. Otherwise prepare the exact commands and marked Markdown and report the blocker.
  7. Audit existing PR body/comment image references. Replace dead, expiring, temporary, or local-only URLs with verified durable assets. Update agent-owned marked sections in place, preserve author text outside them, and change only a broken URL when it sits in author-owned prose.
  8. Push the branch. Use --force-with-lease only when the rebase made it necessary.
  9. Create or update the PR with a summary built from the plans, current diff, and a visual overview bounded by <!-- pr-visual-overview:start --> / <!-- pr-visual-overview:end --> that embeds the verified image inline. Read the PR back and confirm it is non-draft when the requested outcome is a ready PR.
  10. Run the cold-read skill on the PR title and body and apply its improvements before reporting done. Human review has not been requested yet, so its creative freedom applies in full.
  11. Size the PR with git diff origin/main...HEAD --numstat, counting hand-written files and lines only (exclude lockfiles, generated and vendored files). If it exceeds 10 files or 300 lines, end the report with one line offering refactor (the blind simple + deep pass that merges once and stops before applying). Under that size say nothing. Offer, never run; use the bundled skill through the parent's configured native roles only when the user requests it.

Rules:

  • Before drafting, read references/writing-guide.md for the completed example and fidelity check; when Grain is connected, adapt its bundled visual template.
  • Write for a zero-context junior SWE: lead with the source discussion/ticket's motivation and intended outcome, then introduce core concepts and explain the diff in dependency order; flag missing rationale rather than inventing it.
  • Cover every changed area, why it changes, tradeoffs, validation and limitations; use ample concrete before/after examples and diagrams, regardless of Grain availability.
  • When Grain is connected, save and visually verify a rich version of the final PR body with section navigation, rendered diagrams and hyperlinks to code/evidence; the PR must remain understandable without opening Grain.
  • When Grain is available, use grain to discover/reuse the repository-and-PR (or branch) workspace, creating one if absent; store diagrams, QA media and reports there and link verified evidence in a self-contained PR, overriding release uploads and inline-asset requirements.
  • When that Grain workspace exists and the session-trace skill is installed, attach this session's trace to it and link it from the PR companion.
  • Extend the linked intent brief with the final PR explanation, before/after behavior, and verified results; retain intent and decision history.
  • New workspaces default to Development Artifacts/<org>/<repo>; explicit destinations win. Clarify ambiguity, name for the task/PR, verify organization/folder/audience, and return the location. Preserve local and tracker/evidence contracts.
  • Never use blanket staging.
  • Treat secrets and credentials as stop conditions.
  • Keep build-fix commits separate when they are distinct from the feature work.
  • If GitHub CLI or network access is unavailable, report exactly where the flow stopped.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Prepare Pr AI skill do?

Prepare a branch for review by committing scoped changes, rebasing on main, running builds, and creating or updating a pull request. Use when the user wants the branch ready for PR review. Also use for rewriting an existing PR description from its current diff and evidence.

Why use Prepare Pr on TypingMind?

Because you install it once and use it with any model. Prepare 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 Prepare Pr 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/prepare-pr. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Prepare 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 Prepare Pr?

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

Is the Prepare Pr 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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