Create a GitHub Pull Request

VerifiedSafe

Complete workflow for creating a GitHub pull request: branch setup, implementation, testing, formatting, and submission.

Sby Skills Guide Bot
DevelopmentIntermediate
7/22/2026
Claude Code
#pull-request#git-workflow#testing#code-coverage#ci-formatting

Recommended for

Automated summary

This skill walks through the full GitHub pull request workflow, from branch creation to PR submission, including testing, formatting, and a detailed description.

Strengths

  • Sequences the work in a clear order: branch, implementation, tests, formatting, commit, push, and PR
  • Enforces explicit conventions for branch prefixes, conventional commit messages, and PR body structure
  • Builds in coverage verification through coverage annotate and interpretation of ,cover markers
  • Reminds the user to check the project's GitHub workflows for the exact formatting commands

Limitations

  • The sample commands target one Python project (uv, black, ruff, pytest) and need adapting elsewhere
  • The PR body template in the example is cut off, so the intended structure is incomplete
  • Assumes a GitHub repo with an authenticated gh CLI and main as the base branch
When to use it

Use it when preparing and submitting a complete GitHub contribution that needs tests and a well-written PR description.

When not to use it

Skip it for quick tweaks on an existing branch or for repositories not hosted on GitHub.

Security analysis

Safe
Quality score78/100

Every command is visible, standard developer tooling (git, gh, uv, black, ruff, pytest) used for its intended purpose. There is no curl|sh, no base64/obfuscated payload, no credential or token exfiltration, and no safety-disabling instruction. The only deletion is a narrowly scoped cleanup of generated `.coverage.*` artifacts, so overall risk is low.

Findings
  • •Uses git/gh/uv/pytest shell commands for legitimate PR workflow; no untrusted input is executed
  • •Includes `rm -f .coverage.*`, which only removes generated coverage data files and is scoped/benign
  • •Network access via `git push` and `gh` is inherent to opening a PR and is transparent
  • •Hardcodes a `Co-Authored-By: Claude` trailer and bot footer in commits/PRs (minor attribution/automation concern, not a security risk)
How this analysis is made

Examples

Create a feature PR
Create a PR that adds a learning-rate warmup option to the training config, with tests and a proper description.
Open a bug-fix pull request
Open a pull request fixing the crash when the dataset path is empty — branch from main, add a regression test, run formatting, and write the PR body.
Submit changes for review
Make a PR for my refactor of the data loader module, and check coverage on the files I changed before committing.

name: pr description: > Create a well-structured GitHub PR with proper branching, testing, formatting, and documentation. Use when the user says "create a PR", "make a PR", "open a pull request", or wants to submit changes for review. Handles the full workflow: branch creation, implementation, testing, formatting, committing, and PR creation with comprehensive descriptions.

Create a GitHub Pull Request

Overview

This skill guides the complete PR workflow from branch creation to PR submission. Follow all steps in order to ensure high-quality, well-documented contributions.

Step 1: Branch Setup

Pull latest main

git checkout main
git pull origin main

Create feature branch

Use a descriptive branch name following the pattern: {type}/{description}

Types:

  • feature/ - New functionality
  • fix/ - Bug fixes
  • refactor/ - Code restructuring
  • docs/ - Documentation updates
  • test/ - Test additions/improvements
git checkout -b feature/descriptive-name

Step 2: Understand the Problem

Before coding, clearly identify:

  1. Core problem: What issue are we solving?
  2. Scope: What files/modules will be affected?
  3. Approach: What's the implementation strategy?
  4. Edge cases: What scenarios need special handling?

If there's an associated GitHub issue, fetch it for context:

gh issue view <issue-number>

Step 3: Implement Changes

  • Make focused, incremental changes
  • Follow existing code patterns and style
  • Add docstrings and comments for complex logic
  • Consider backwards compatibility

Step 4: Write Tests

Location

Tests go in the tests/ directory, mirroring the source structure.

Requirements

  • Cover all new functionality
  • Test edge cases and error conditions
  • Test both success and failure paths
  • Aim for high coverage of changed code

Test file naming

  • test_{module_name}.py for module tests
  • Place in corresponding tests/ subdirectory

Step 5: Format Code

Check GitHub workflows for the project's formatting commands:

# Check .github/workflows/ for exact commands
# Typical formatting for this project:
uv run black sleap_nn tests
uv run ruff check sleap_nn/ --fix

Step 6: Run Tests with Coverage

Run the full test suite with coverage:

uv run pytest -q --maxfail=1 --cov --cov-branch && rm -f .coverage.* && uv run coverage annotate

Check coverage for changed files

The coverage annotate command creates {module_name.py},cover files next to each module.

To find which files changed:

git diff --name-only $(git merge-base origin/main HEAD)

Review the ,cover files for your changed modules to ensure adequate coverage.

Coverage markers in annotated files

| Marker | Meaning | |--------|---------| | > | Line was executed | | ! | Line was NOT executed (needs test coverage) | | - | Line is not executable (comments, blank lines) |

Step 7: Commit Changes

Commit structure

Make well-structured, atomic commits:

  • Each commit should be a logical unit of work
  • Write clear, descriptive commit messages
  • Use conventional commit format when appropriate

Commit message format

<type>: <short description>

<optional longer description>

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

Types: feat, fix, refactor, test, docs, chore

Step 8: Push to GitHub

git push -u origin <branch-name>

Step 9: Create Pull Request

Create the PR

gh pr create --title "<descriptive title>" --body "$(cat <<'EOF'
## Summary
<1-3 bullet points describing the changes>

## Changes Made
- <detailed list of changes>

## Example Usage
```python
# For enhancements, show how to use the new functionality

API Changes

  • <list any API changes, new parameters, removed functionality>

Testing

  • <describe test coverage>
  • <note any manual testing done>

Design Decisions

  • <explain key architectural choices>
  • <note trade-offs considered>

Future Considerations

  • <potential improvements not in scope>
  • <known limitations>

Related Issues

Closes #<issue-number> (if applicable)


🤖 Generated with Claude Code EOF )"


### If updating an existing PR

Fetch current PR description:
```bash
gh pr view <pr-number> --json body -q '.body'

Update PR description:

gh pr edit <pr-number> --body "<new body>"

Fetch associated issue for context

If an issue is linked:

gh issue view <issue-number>

Use issue context to ensure PR description addresses all requirements.

PR Description Checklist

  • [ ] Summary clearly explains the "what" and "why"
  • [ ] All significant changes are documented
  • [ ] Example usage provided for new features
  • [ ] API changes explicitly listed
  • [ ] Breaking changes highlighted
  • [ ] Test coverage described
  • [ ] Design decisions explained with reasoning
  • [ ] Related issues linked

Quick Reference Commands

# Branch setup
git checkout main && git pull origin main
git checkout -b feature/my-feature

# Format and lint
uv run black sleap_nn tests
uv run ruff check sleap_nn/ --fix

# Test with coverage
uv run pytest -q --maxfail=1 --cov --cov-branch && rm -f .coverage.* && uv run coverage annotate

# Find changed files
git diff --name-only $(git merge-base origin/main HEAD)

# Commit
git add <files>
git commit -m "feat: description"

# Push and create PR
git push -u origin <branch>
gh pr create --title "Title" --body "Description"

# View/edit existing PR
gh pr view <number>
gh pr edit <number> --body "New description"

# View linked issue
gh issue view <number>

From the file to a first result

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Download SKILL.md

From the root of a test project, save the file as .skill-downloads/create-a-github-pull-request-mrwakdb5/SKILL.md, or use the command below. This folder is for inspecting the skill before installation.

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Read SKILL.md before using it. If it references scripts or external services, inspect them and prepare the required access in your test environment.

Original excerpt: Requirements
  • Cover all new functionality
  • Test edge cases and error conditions
  • Test both success and failure paths
  • Aim for high coverage of changed code

The platforms on this page are catalog indications. The paths below follow tool documentation; they do not prove this skill has been run in those tools. No minimum tool version is confirmed for this listing.

3. Load the skill

After inspection, copy the complete folder into your project using one of the commands below, then open a new tool session. The command stops if a folder with the same name already exists: compare the files before replacing it.

Claude Code
test -f '.skill-downloads/create-a-github-pull-request-mrwakdb5/SKILL.md' && test -s '.skill-downloads/create-a-github-pull-request-mrwakdb5/SKILL.md' && mkdir -p '.claude/skills' && test ! -e '.claude/skills/pr' && cp -R '.skill-downloads/create-a-github-pull-request-mrwakdb5' '.claude/skills/pr'

OpenSkills

OpenSkills must already be installed. The local install/read procedure is checked with OpenSkills 1.5.0, which requires Node.js ≥ 20.6.0. Catalog slugs are not resolved automatically.

Official OpenSkills installation
openskills install './.skill-downloads/create-a-github-pull-request-mrwakdb5'

openskills read 'create-a-github-pull-request-mrwakdb5'

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For an agent that reads AGENTS.md, then sync the index. This command changes AGENTS.md: review the diff before using it.

openskills sync

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Read .skill-downloads/create-a-github-pull-request-mrwakdb5/SKILL.md and apply its instructions to this example: [describe a test input]. Identify any missing files, dependencies or access. Produce the result requested by the skill without inventing data or running unreviewed scripts.

Expected result: output matching the skill instructions, or a precise list of missing prerequisites. A read confirmation alone does not validate a first use. If an external resource is unavailable, that path remains untested.

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