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Create Pr

Community
tobihagemann
create-pr

Create a GitHub pull request with a drafted title and description. Use when the user asks to "create a PR", "create a pull request", "open a PR", or "submit a PR".

Overview

Publishertobihagemann
Repositoryturbo
Skill namecreate-pr
Stars
417
Forks
32
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 tobihagemann on GitHub. Read the source before you install it.

Installation

Install the Create 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/tobihagemann/turbo/tree/main/claude/skills/create-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/tobihagemann/turbo.git /tmp/turbo
mkdir -p .claude/skills
cp -r /tmp/turbo/claude/skills/create-pr .claude/skills/create-pr
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Create 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 Create 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 Create 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.

Create Pull Request

Draft a concise and descriptive title and a body for a PR. Explain the purpose of the changes, the problem they solve, and the general approach taken. When the changes involve clear runtime flows or state transitions, include Mermaid diagrams. When they add a user-facing surface or change how one looks, and this session already captured it, include screenshots.

Step 1: Analyze Changes

If git is in a feature branch, examine all commit messages and the full diff to understand the overall changes. Analyze the diff for framing, diagram, and screenshot opportunities.

Source every claim about prior behavior from the base branch itself, by reading its code with git show origin/<base>:<path>. A long session leaves the working tree carrying intermediate states that were never the state this PR is measured against, and describing one of those as the prior behavior misleads the reviewer.

Before writing that two pull requests must land together, check whether the consumer uses what changed: git grep <symbol> in its checkout, or the other repository's working copy when the dependency crosses repositories. When it does, name the actual cause. When it does not, drop the landing-order claim and keep any reference to the related pull request as plain context. State the claim as unverified when the consumer is not reachable.

When the PR closes an issue, read the issue before drafting.

Step 2: Run /github-voice Skill

Run the /github-voice skill to load writing style rules.

Step 3: Draft Title and Description

Pick a framing, then draft a title and description in it, embedding any diagrams and screenshots in the body. Output the drafted title and description as chat text so the user can review it, followed by the path of each capture that will upload, if any. After that, name each added surface or changed look that none of those captures shows in its final state, if any, with the reason it goes unshown.

Step 4: Confirm and Create

Generate a random tag so the body file is unique across sessions:

bash
head -c 4 /dev/urandom | xxd -p

Write the drafted body to .turbo/pr/<tag>-body.md (using the printed tag) with the Write tool.

Use AskUserQuestion to choose among three outcomes, and act on the one selected:

  • Post the PR now — create it with the command below.
  • Edit the description first — give the user the path to the body file and stop there. Once they say they are done editing, use AskUserQuestion again to offer posting the PR or cancelling, then act on that answer. Posting reads the file, so their edits carry through.
  • Cancel — create no PR.
bash
gh pr create --title "<TITLE>" --body-file .turbo/pr/<tag>-body.md

When the body references captures, add one --attach <path> per capture, using the absolute path the body references. Take the list from the body file as it stands when posting, re-reading it after the user edits it.

When the command reports a failed upload, act on what it printed, then report which captures the PR went up without:

  • No PR URL — nothing uploaded and no PR exists. Remove the screenshot table and its heading from the body file and run the command again without --attach.
  • A PR URL — the PR exists, and its body references the captures that did not upload by local path. Fetch the posted body with gh pr view <PR_URL> --json body --jq .body, remove each table column whose image is still a local path, write the result to the body file, and apply it with gh pr edit <PR_URL> --body-file .turbo/pr/<tag>-body.md.

When the user asks, before the PR is posted, to change content this session committed for it, fold the change into the commit that carries that content instead of adding a commit, and push with --force-with-lease when that commit was already pushed. Update the drafted title and the body file where the change alters what they describe, then return to this gate.

Do not set --assignee unless the user explicitly asks to assign someone. Reserve --draft for an explicit request for a draft pull request on GitHub.

Then use the TaskList tool and proceed to any remaining task.

Framing

Every body says what the change does and why. How it is organized past that follows from what the change is: pick the framing that carries the most user-visible meaning, and combine two when the change genuinely has both shapes.

Summary Paragraph

The default. Use when the PR makes one coherent change with one purpose.

Itemized Changes

Use when the PR carries several distinct changes and the reviewer needs the inventory. One item per change, ordered by what matters most.

User Stories

Use when the change delivers capability someone can name. Write each as As a <persona>, I want <capability> so that <outcome>.

Before and After

Use when the reviewer's question is what changed rather than what exists: several distinct fixes, or behavior that reads as a feature description unless the delta is spelled out. Give each item a Before line and an After line. Head each item with its user story in bold and list the Before and After lines beneath it. Reserve a plain heading, such as the name of the code the item touches, for an item that changes nothing a user or operator would notice.

Write Before lines in the past tense, with two exceptions. A sentence describing code the PR leaves alone stays present tense. A claim about what was merely possible stays modal ("could post"), never simple past, which asserts it happened.

Rules

  • Raise each item, heading included, to behavior a user or operator would notice. Mechanism the reviewer can read off the diff belongs in the diff. Leave out which existing pattern or sibling the implementation is modeled on.
  • Describe the net change against the base. Leave out what the session tried and weighed along the way, and what the PR leaves undone: follow-ups, problems found but not fixed, and notes that code it leaves alone still behaves as before. When the PR closes an issue, still state any part of that issue it does not deliver.
  • Write the body for someone who knows only the repository the PR targets. When the change is paired with work in another repository, name the interface the code calls and leave that repository's internal names, data shapes, and mechanisms out of the body. Explaining a cause does not license importing those internals. State the observable outcome instead. Describe the change on its own terms, without reference to how a different repository or product does it.
  • When the PR closes an issue, open with Closes #N. Carry only what the issue does not already say: the interface being added, behavior a reviewer cannot infer from the diff, and above all any deviation from what the issue asked for. The issue carries the bug, its root cause, and the motivation; reference it rather than restating it.
  • After cutting for any rule above, re-read what remains. A claim whose setup lived in a cut passage no longer stands on its own.

Diagrams

GitHub renders Mermaid natively in PR descriptions via ```mermaid code blocks. Include diagrams only when they add clarity a text description can't — skip for trivial changes or obvious flows.

Sequence Diagram

Include when the changes introduce or modify a clear runtime flow: API endpoints, event handlers, pipelines, multi-service interactions, webhook flows.

markdown
```mermaid
sequenceDiagram
  Client->>API: POST /payments
  API->>PaymentService: processPayment()
  PaymentService->>StripeClient: charge()
  StripeClient-->>PaymentService: confirmation
  PaymentService->>DB: save()
```

State Diagram

Include when the changes add or modify entity states, status enums, workflow transitions, or lifecycle hooks.

markdown
```mermaid
stateDiagram-v2
  [*] --> Draft
  Draft --> Pending: submit()
  Pending --> Approved: approve()
  Pending --> Rejected: reject()
  Approved --> [*]
```

Rules

  • Only include when the diagram genuinely adds clarity
  • Keep diagrams focused — max ~10 nodes/transitions
  • Use descriptive labels on arrows (method names, HTTP verbs)
  • Place diagrams after the opening body text under a ## Flow or ## State Machine heading
  • One diagram per type max — don't include both unless the PR truly has both patterns

Screenshots

Include screenshots when the PR adds a user-facing surface or changes how one looks, and this session already holds captures of that surface in its final state. Reuse those captures after viewing each one, keeping the fewest that show the change. A change in when an existing surface appears leaves its look unchanged, so add no capture of it. Take no new captures: with none on hand, omit the section.

Reference every kept capture in one row of a markdown table, with its caption in the header cell above it:

markdown
| <caption> | <caption> |
| --- | --- |
| ![<caption>](<absolute path>) | ![<caption>](<absolute path>) |

Rules

  • Use markdown image syntax with the capture's absolute path. gh points only markdown references at the uploaded asset, so a raw <img> tag keeps its local path.
  • Keep every capture in the table row. gh appends an attached file the body never references as its own paragraph.
  • Place the table after the opening body text under a ## Screenshots heading, ahead of any diagram.

Rules

  • Don't reference .turbo/ content (filenames, acceptance criteria, step numbers, headings) in the title or body. .turbo/ is gitignored, so these references would be opaque to anyone reading without local copies.

Frequently asked questions

What does the Create Pr AI skill do?

Create a GitHub pull request with a drafted title and description. Use when the user asks to "create a PR", "create a pull request", "open a PR", or "submit a PR".

Why use Create Pr on TypingMind?

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

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

Which AI models can use Create 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 Create Pr?

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

Is the Create Pr AI skill free?

Yes. It is published on GitHub by tobihagemann 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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