Git-Flow-Branch-Creator
Git-Flow-Branch-Creator是一款code方向的AI技能,核心价值是Intelligent Git Flow branch creator that analyzes git status/diff and creates appropriate branches following the nvie Git Flow branching model,可用于解决开发者在code领域的实际问题,帮助用户提升效率、自动化重复任务或优化工作流。
Intelligent Git Flow branch creator that analyzes git status/diff and creates appropriate branches following the nvie Git Flow branching model.
mkdir -p ./skills/git-flow-branch-creator && curl -sfL https://raw.githubusercontent.com/github/awesome-copilot/main/skills/git-flow-branch-creator/SKILL.md -o ./skills/git-flow-branch-creator/SKILL.md Run in terminal / PowerShell. Requires curl (Unix) or PowerShell 5+ (Windows).
Skill Content
Instructions
<instructions>
<title>Git Flow Branch Creator</title>
<description>This prompt analyzes your current git changes using git status and git diff (or git diff --cached), then intelligently determines the appropriate branch type according to the Git Flow branching model and creates a semantic branch name.</description>
<note>
Just run this prompt and Copilot will analyze your changes and create the appropriate Git Flow branch for you.
</note>
</instructions>Workflow
**Follow these steps:**
1. Run `git status` to review the current repository state and changed files.
2. Run `git diff` (for unstaged changes) or `git diff --cached` (for staged changes) to analyze the nature of changes.
3. Analyze the changes using the Git Flow Branch Analysis Framework below.
4. Determine the appropriate branch type based on the analysis.
5. Generate a semantic branch name following Git Flow conventions.
6. Create the branch and switch to it automatically.
7. Provide a summary of the analysis and next steps.
Git Flow Branch Analysis Framework
<analysis-framework>
<branch-types>
<feature>
<purpose>New features, enhancements, non-critical improvements</purpose>
<branch-from>develop</branch-from>
<merge-to>develop</merge-to>
<naming>feature/descriptive-name or feature/ticket-number-description</naming>
<indicators>
<indicator>New functionality being added</indicator>
<indicator>UI/UX improvements</indicator>
<indicator>New API endpoints or methods</indicator>
<indicator>Database schema additions (non-breaking)</indicator>
<indicator>New configuration options</indicator>
<indicator>Performance improvements (non-critical)</indicator>
</indicators>
</feature>
<release>
<purpose>Release preparation, version bumps, final testing</purpose>
<branch-from>develop</branch-from>
<merge-to>develop AND master</merge-to>
<naming>release-X.Y.Z</naming>
<indicators>
<indicator>Version number changes</indicator>
<indicator>Build configuration updates</indicator>
<indicator>Documentation finalization</indicator>
<indicator>Minor bug fixes before release</indicator>
<indicator>Release notes updates</indicator>
<indicator>Dependency version locks</indicator>
</indicators>
</release>
<hotfix>
<purpose>Critical production bug fixes requiring immediate deployment</purpose>
<branch-from>master</branch-from>
<merge-to>develop AND master</merge-to>
<naming>hotfix-X.Y.Z or hotfix/critical-issue-description</naming>
<indicators>
<indicator>Security vulnerability fixes</indicator>
<indicator>Critical production bugs</indicator>
<indicator>Data corruption fixes</indicator>
<indicator>Service outage resolution</indicator>
<indicator>Emergency configuration changes</indicator>
</indicators>
</hotfix>
</branch-types>
</analysis-framework>Branch Naming Conventions
<naming-conventions>
<feature-branches>
<format>feature/[ticket-number-]descriptive-name</format>
<examples>
<example>feature/user-authentication</example>
<example>feature/PROJ-123-shopping-cart</example>
<example>feature/api-rate-limiting</example>
<example>feature/dashboard-redesign</example>
</examples>
</feature-branches>
<release-branches>
<format>release-X.Y.Z</format>
<examples>
<example>release-1.2.0</example>
<example>release-2.1.0</example>
<example>release-1.0.0</example>
</examples>
</release-branches>
<hotfix-branches>
<format>hotfix-X.Y.Z OR hotfix/critical-description</format>
<examples>
<example>hotfix-1.2.1</example>
<example>hotfix/security-patch</example>
<example>hotfix/payment-gateway-fix</example>
<example>hotfix-2.1.1</example>
</examples>
</hotfix-branches>
</naming-conventions>Analysis Process
<analysis-process>
<step-1>
<title>Change Nature Analysis</title>
<description>Examine the types of files modified and th🎯 Best For
- Data analysts
- Business intelligence teams
- Claude users
- GitHub Copilot users
- Software engineers
💡 Use Cases
- Finding patterns in customer data
- Creating automated dashboards
- Code quality improvement
- Best practice enforcement
📖 How to Use This Skill
- 1
Install the Skill
Copy the install command from the Terminal tab and run it. The SKILL.md file downloads to your local skills directory.
- 2
Load into Your AI Assistant
Open Claude or GitHub Copilot and reference the skill. Paste the SKILL.md content or use the system prompt tab.
- 3
Apply Git-Flow-Branch-Creator to Your Work
Open your project in the AI assistant and ask it to apply the skill. Start with a small module to verify the output quality.
- 4
Review and Refine
Review AI suggestions before committing. Run tests, check for regressions, and iterate on the skill output.
❓ Frequently Asked Questions
Can this connect to my database directly?
Most data skills accept CSV or JSON input. Database connectors are listed in the Works With section.
Is Git-Flow-Branch-Creator compatible with Cursor and VS Code?
Yes — this skill works with any AI coding assistant including Cursor, VS Code with Copilot, and JetBrains IDEs.
Do I need specific dependencies for Git-Flow-Branch-Creator?
Check the install command and Works With section. Most code skills only require the AI assistant and your codebase.
How do I install Git-Flow-Branch-Creator?
Copy the install command from the Terminal tab and run it. The skill downloads to ./skills/git-flow-branch-creator/SKILL.md, ready to use.
Can I customize this skill for my team?
Absolutely. Edit the SKILL.md file to add team-specific instructions, examples, or workflows.
⚠️ Common Mistakes to Avoid
Not validating data quality
AI analysis is only as good as your input data. Profile and clean data before analysis.
Skipping validation
Always test AI-generated code changes, even for simple refactors.
Missing dependency updates
Check if the skill requires updated dependencies or new packages.