Create Pr logo

Create Pr

Organization
warpdotdev
create-pr

Create a pull request in the warp repository for the current branch. Use when the user mentions opening a PR, creating a pull request, submitting changes for review, or preparing code for merge.

Overview

Publisherwarpdotdev
Repositorycommon-skills
Skill namecreate-pr
Stars
597
Forks
33
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 warpdotdev 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/warpdotdev/common-skills/tree/main/.agents/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/warpdotdev/common-skills.git /tmp/common-skills
mkdir -p .claude/skills
cp -r /tmp/common-skills/.agents/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-pr

Overview

This guide covers best practices for creating pull requests in the warp repository, including merging master, validating changes efficiently, linking Linear tasks, ensuring appropriate test coverage, and structuring your PR for effective review.

Related Skills

  • write-pr-description - Write the PR body itself: template sections, prose, and reviewer guidance
  • fix-errors - Fix targeted compilation, test, lint, or formatting failures before opening a PR
  • warp-integration-test - Add or update integration coverage for user-visible flows, regressions, and P0 use cases
  • add-feature-flag - Gate changes behind feature flags

Pre-PR Checklist

1. Merge master into your feature branch

Always merge master into your feature branch before starting the review process.

bash
git fetch origin
git merge origin/master

Resolve any merge conflicts locally before opening the PR.

2. Review your changes

Before creating a PR, review what changes you're about to submit:

bash
# View commits in your branch (comparing against base branch)
git --no-pager log <base-branch>..HEAD --oneline

# View file statistics for changes
git --no-pager diff <base-branch>...HEAD --stat

# View full diff
git --no-pager diff <base-branch>...HEAD

This helps you:

  • Verify all intended changes are included
  • Catch unintended changes before review
  • Write an accurate PR description
  • Ensure you're comparing against the correct base branch
  • Tests: Include tests when required—bug fixes (regression test), algorithmic code (unit tests), UI components (layout test), P0 use cases (integration test). See Testing Requirements below.

3. Respect implementation agent validation

PR creation is not a validation boundary. If the implementation workflow already completed its tests, lint checks, and final formatting pass and the candidate has not changed, do not rerun them.

If merging master or preparing the PR changed source, tests, manifests, generated code, or configuration, validate the new candidate in this order:

  1. Run the relevant tests and fix the code until they pass.
  2. Run the applicable Clippy and other lint, typecheck, or build checks and fix their findings. Return to affected tests only when a fix materially changes behavior.
  3. Run ./script/format once after all other code changes are complete.

Do not rerun tests or lint after formatting, and do not run ./script/presubmit, unless the user, task, or approved spec explicitly requires it. CI owns uncommon failures outside targeted local coverage. Documentation-only changes do not require Rust tests, Clippy, or formatting.

4. Link to Linear task

When possible, PRs should be associated with a Linear task. Use the Linear MCP tool (if available) to find corresponding issues.

Branch naming convention: Remote branches should be prefixed with your name (e.g., zheng/feature, alice/fix-bug).

How to link PRs to Linear: Include the issue ID in the PR title (e.g., [WARP-1234] Add new feature). Do this before creating the PR for automatic linking.

5. Open the PR

Use the PR template at .github/pull_request_template.md when opening PRs.

Add changelog entries when appropriate using the format at the bottom of the PR template. Some examples:

  • Feature: "Global search in files across your current directories. Use CMD-F/CTRL-SHIFT-F to open."
  • Improvement: "Added horizontal autoscrolling when jumping to line/column."
  • Bug fix: "Fixed session viewer input being cleared when agent runs commands.

CLI workflow:

  • Check if PR exists for current branch:

    bash
    gh pr view --json number,url

    Exit code 0 if PR exists, 1 if not.

  • Create a new PR:

    bash
    # With title and body
    gh pr create --title "Title" --body "Description" --draft
    
    # Auto-fill from commits
    gh pr create --fill --draft
    
    # Use PR template file
    gh pr create --body-file .github/pull_request_template.md --title "Title" --draft

    Key flags: --draft / -d, --fill / -f, --body-file / -F, --web / -w

  • Update an existing PR:

    bash
    gh pr edit --title "New title" --body "New body"
    gh pr edit --add-reviewer username --add-label bug
  • Mark PR ready for review:

    bash
    gh pr ready

6. Include co-author attribution

When committing changes, include attribution as a trailer at the end of the commit message only — never in the PR description — and never add a second Warp/Oz co-author trailer if the commit already has one:

Co-Authored-By: Warp Agent <agent@warp.dev>

Testing Requirements

Bug fixes require regression tests

All bug fixes should be accompanied by a regression test. This helps prevent re-breaking something that was already broken once.

The test should:

  • Reproduce the original bug (would fail before the fix)
  • Pass after the fix is applied
  • Be clearly named to indicate what bug it's preventing

Algorithmic code requires unit tests

Code with non-trivial logic should have unit tests to validate functionality:

Examples of what needs unit tests:

  • Custom data structures (e.g., SumTree)
  • Search-related APIs that should return expected results for a given query
  • Core layout code in the UI framework
  • Any algorithmic or computational logic

Not required for:

  • Sufficiently-simple functions
  • Trivial getters/setters

Follow the repository's local testing conventions for guidance on writing unit tests.

UI components need layout validation tests

All UI components (implementations of View) should have a simple unit test to validate that they can be laid out without a panic.

This provides high-level coverage over rendering "safety" (though not "correctness"):

rust
#[test]
fn test_component_can_layout() {
    use warpui::App;
    use warp::test_util::{terminal::initialize_app_for_terminal_view, add_window_with_terminal};
    
    App::test((), |mut app| async move {
        initialize_app_for_terminal_view(&mut app);
        let term = add_window_with_terminal(&mut app, None);
        
        // Render the component - should not panic
        term.update(&mut app, |view, ctx| {
            // Create and layout your component
        });
    })
}

Ask before skipping integration coverage

If the PR changes a user-visible flow, fixes an end-to-end regression, or otherwise looks like it would benefit from integration coverage, use the ask_user_question tool before creating or updating the PR to ask whether the user wants an integration test added as part of the work.

Prefer a direct choice such as:

  • Yes, add an integration test before creating the PR
  • No, continue without an integration test

If the user chooses to add one, use the warp-integration-test skill.

P0 use cases require integration tests

All "P0 use cases" require an integration test that covers the behavior/flow in question.

A "P0 use case" is defined as: Any behavior of the application that, if broken, warrants an out-of-band release.

Integration tests should:

  • Exercise the full user-facing flow
  • Validate end-to-end functionality
  • Be placed in the integration/ directory

Use the warp-integration-test skill for implementation details, test registration steps, and validation workflow.

PR Description Guidelines

Use the write-pr-description skill for the body itself. It covers following the repository's template, the prose baseline, and when to add a reading order and focus areas for the reviewer.

After Opening the PR

  1. Monitor CI checks - Ensure all automated checks pass
  2. Respond to review comments - Address feedback promptly
  3. Keep the PR up to date - Merge master if conflicts arise
  4. Validate changed candidates - After code changes from review feedback, run affected tests, then lint checks, then ./script/format once. Do not repeat validation for PR metadata or an unchanged candidate.

Best Practices

  • Keep PRs focused - One logical change per PR when possible
  • Write clear commit messages - Explain what and why, not just what
  • Self-review first - Review your own diff before requesting review
  • Update tests - Ensure test coverage reflects your changes
  • Document breaking changes - Call out any API changes or breaking modifications
  • Use feature flags - Gate risky changes behind feature flags when appropriate (see the add-feature-flag skill)

Frequently asked questions

What does the Create Pr AI skill do?

Create a pull request in the warp repository for the current branch. Use when the user mentions opening a PR, creating a pull request, submitting changes for review, or preparing code for merge.

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/warpdotdev/common-skills/tree/main/.agents/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 warpdotdev 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.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇