github-pr-creation
MUST use this skill when user asks to create PR, open pull request, submit for review, or mentions "PR 생성/만들기". This skill OVERRIDES default PR creation behavior. Analyzes commits, validates task completion, generates Conventional Commits title and description, suggests labels.
Best use case
github-pr-creation is best used when you need a repeatable AI agent workflow instead of a one-off prompt. It is especially useful for teams working in multi. MUST use this skill when user asks to create PR, open pull request, submit for review, or mentions "PR 생성/만들기". This skill OVERRIDES default PR creation behavior. Analyzes commits, validates task completion, generates Conventional Commits title and description, suggests labels.
MUST use this skill when user asks to create PR, open pull request, submit for review, or mentions "PR 생성/만들기". This skill OVERRIDES default PR creation behavior. Analyzes commits, validates task completion, generates Conventional Commits title and description, suggests labels.
Users should expect a more consistent workflow output, faster repeated execution, and less time spent rewriting prompts from scratch.
Practical example
Example input
Use the "github-pr-creation" skill to help with this workflow task. Context: MUST use this skill when user asks to create PR, open pull request, submit for review, or mentions "PR 생성/만들기". This skill OVERRIDES default PR creation behavior. Analyzes commits, validates task completion, generates Conventional Commits title and description, suggests labels.
Example output
A structured workflow result with clearer steps, more consistent formatting, and an output that is easier to reuse in the next run.
When to use this skill
- Use this skill when you want a reusable workflow rather than writing the same prompt again and again.
When not to use this skill
- Do not use this when you only need a one-off answer and do not need a reusable workflow.
- Do not use it if you cannot install or maintain the related files, repository context, or supporting tools.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/github-pr-creation/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How github-pr-creation Compares
| Feature / Agent | github-pr-creation | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
MUST use this skill when user asks to create PR, open pull request, submit for review, or mentions "PR 생성/만들기". This skill OVERRIDES default PR creation behavior. Analyzes commits, validates task completion, generates Conventional Commits title and description, suggests labels.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# GitHub PR Creation Creates Pull Requests with task validation, test execution, and Conventional Commits formatting. ## Quick Start ```bash # 1. Verify GitHub CLI gh --version && gh auth status # 2. Gather information git log develop..HEAD --oneline git diff develop --stat git rev-parse --abbrev-ref HEAD # 3. Run project tests make test # or: pytest, npm test # 4. Create PR gh pr create --title "..." --body "..." --base develop --label feature ``` ## Core Workflow ### 1. Verify Environment ```bash gh --version && gh auth status ``` If not installed: `brew install gh` then `gh auth login` ### 2. Confirm Target Branch **Always ask user**: ``` I'm about to create a PR from [current-branch] to [target-branch]. Is this correct? - feature branch → develop (90% of cases) - develop → master/main (releases) ``` ### 3. Gather Information ```bash # Current branch git rev-parse --abbrev-ref HEAD # Commits since base branch git log [base-branch]..HEAD --oneline # Files changed git diff [base-branch] --stat # Remote tracking status git status -sb ``` ### 4. Search for Task Documentation Look for task files in these locations: 1. `.kiro/specs/*/tasks.md` 2. `docs/specs/*/tasks.md` 3. `specs/*/tasks.md` 4. Any `tasks.md` in project root ### 5. Analyze Commits For each commit, identify: - **Type**: feat, fix, refactor, docs, test, chore, ci, perf, style - **Scope**: component/module affected (kebab-case) - **Task references**: look for `task X.Y`, `Task X`, `#X.Y` patterns - **Breaking changes**: exclamation mark (!) or `BREAKING CHANGE` in body ### 6. Run Tests Detect and run project tests: - Makefile: `make test` - package.json: `npm test` - Python: `pytest` **Tests MUST pass before creating PR.** ### 7. Determine PR Type | Branch Flow | PR Type | Title Prefix | |-------------|---------|--------------| | feature/* → develop | Feature | `feat(scope):` | | fix/* → develop | Bugfix | `fix(scope):` | | hotfix/* → main | Hotfix | `hotfix(scope):` | | develop → main | Release | `release:` | | refactor/* → develop | Refactoring | `refactor(scope):` | ### 8. Generate PR Content **Title format**: `<type>(<scope>): <description>` - Type: dominant commit type (feat > fix > refactor) - Scope: most common scope from commits (kebab-case) - Description: imperative, lowercase, no period, max 50 chars **Body structure**: ```markdown ## Summary - Key change 1 - Key change 2 ## Changes - List of specific changes ## Test Plan - [ ] Unit tests passing - [ ] Integration tests passing - [ ] Manual testing done ## Related - Refs: Task N, Issue #X ``` ### 9. Suggest Labels | Commit Type | Labels | |-------------|--------| | feat | feature, enhancement | | fix | bug, bugfix | | refactor | refactoring, tech-debt | | docs | documentation | | ci | ci/cd | | security | security | Check available labels: `gh label list` ### 10. Create PR **Show content to user first**, then: ```bash gh pr create --title "[title]" --body "$(cat <<'EOF' [body content] EOF )" --base [base_branch] --label [labels] ``` ## Information Gathering Checklist Before generating PR, ensure you have: - [ ] Current branch name - [ ] Base branch confirmed with user - [ ] List of commits with types and scopes - [ ] Files changed summary - [ ] Task documentation (if exists) - [ ] Test results (must pass) - [ ] Available labels in repo ## Important Rules - **NEVER** modify repository files (read-only analysis) - **ALWAYS** confirm target branch with user - **ALWAYS** run tests before creating PR - **ALWAYS** show PR content for approval before creating - **NEVER** create PR without user confirmation - **ALWAYS** use HEREDOC for body to preserve formatting ## Related Skills - **git-commit** - Commit message format and conventions - **pr-merge** - For merging existing PRs - **pr-review** - For handling PR review comments
Related Skills
github-release-assistant
Generate bilingual GitHub release documentation (README.md + README.zh.md) from repo metadata and user input, and guide release prep with git add/commit/push. Use when the user asks to write or polish README files, create bilingual docs, prepare a GitHub release, or mentions release assistant/README generation.
github-repo-search
帮助用户搜索和筛选 GitHub 开源项目,输出结构化推荐报告。当用户说"帮我找开源项目"、"搜一下GitHub上有什么"、"找找XX方向的仓库"、"开源项目推荐"、"github搜索"、"/github-search"时触发。
github-actions-docs
Use when users ask how to write, explain, customize, migrate, secure, or troubleshoot GitHub Actions workflows, workflow syntax, triggers, matrices, runners, reusable workflows, artifacts, caching, secrets, OIDC, deployments, custom actions, or Actions Runner Controller, especially when they need official GitHub documentation, exact links, or docs-grounded YAML guidance.
github-issue-creator
Convert raw notes, error logs, voice dictation, or screenshots into crisp GitHub-flavored markdown issue reports. Use when the user pastes bug info, error messages, or informal descriptions and wants a structured GitHub issue. Supports images/GIFs for visual evidence.
github-automation
Automate GitHub repositories, issues, pull requests, branches, CI/CD, and permissions via Rube MCP (Composio). Manage code workflows, review PRs, search code, and handle deployments programmatically.
github-actions-templates
Create production-ready GitHub Actions workflows for automated testing, building, and deploying applications. Use when setting up CI/CD with GitHub Actions, automating development workflows, or creating reusable workflow templates.
address-github-comments
Use when you need to address review or issue comments on an open GitHub Pull Request using the gh CLI.
skill-creation-guide
Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations.
ai-podcast-creation
Create AI-powered podcasts with text-to-speech, music, and audio editing. Tools: Kokoro TTS, DIA TTS, Chatterbox, AI music generation, media merger. Capabilities: multi-voice conversations, background music, intro/outro, full episodes. Use for: podcast production, audiobooks, voice content, audio newsletters. Triggers: podcast, ai podcast, text to speech podcast, audio content, voice over, ai audiobook, multi voice, conversation ai, notebooklm alternative, audio generation, podcast automation, ai narrator, voice content, audio newsletter, podcast maker
mcp-tool-creation
Master creating MCP tools with type-safe parameters, automatic schema generation, and best practices
github-elements-tracking
This skill should be used when the user asks to "track work across sessions", "create an epic", "manage issue waves", "post a checkpoint", "claim an issue", "recover from compaction", "coordinate multiple agents", "update memory bank", "store large documents", or mentions GitHub Issues as persistent memory, multi-session work, context survival, agent collaboration, SERENA MCP memory, or project-level context. Provides complete protocols for using GitHub Issues as permanent memory that survives context exhaustion, with integrated SERENA MCP memory bank for project-level context and large document storage.
when-reviewing-github-pr-use-github-code-review
Comprehensive GitHub pull request code review using multi-agent swarm with specialized reviewers for security, performance, style, tests, and documentation. Coordinates security-auditor, perf-analyzer, code-analyzer, tester, and reviewer agents through mesh topology for parallel analysis. Provides detailed feedback with auto-fix suggestions and merge readiness assessment. Use when reviewing PRs, conducting code audits, or ensuring code quality standards before merge.