git-skill: A Cross-AI Editor Git Workflow Skill Library

git-skill is an AI editor-agnostic Git workflow skill library designed to address the lack of standardization in Git workflow handling among AI programming tools (such as Claude Code, Cursor, etc.). It supports mainstream Git hosting platforms like GitHub, GitLab, and Gitea, providing standardized workflow automation capabilities. Key advantages include a proxy-agnostic architecture (cross-AI tool compatibility), multi-platform support, and an implemented Release Standard Operating Procedure (Release SOP), helping teams improve collaboration efficiency and process consistency.

With the popularity of AI programming assistants like Claude Code, Cursor, and GitHub Copilot, the way developers interact with code repositories has changed. However, different AI tools have varying Git workflow implementations, leading to friction and confusion in team collaboration. The git-skill project was born as a cross-platform Git workflow solution to address this pain point.

The core features of git-skill include:

1. Release Standard Operating Procedure (Release SOP)：Automatically handles semantic version increment, generates change logs, creates Git tags, and executes release checklists to reduce human errors.
2. Multi-platform Git Hosting Support：Compatible with GitHub (full API integration), GitLab (adapts to its API and workflows), and Gitea (supports self-hosted instances), catering to different team toolchain preferences.
3. Proxy-Agnostic Architecture：Uses a universal skill definition format that can be understood and executed by multiple AI agents, enabling tool freedom, easy migration, and cross-tool standardization.

git-skill adopts a modular and extensible architecture:

• Skill Definition Layer: Uses a standardized format to define Git workflow steps and rules.
• Platform Adaptation Layer: Provides a unified abstract interface for API differences across various Git hosting platforms.
• Agent Interface Layer: Offers adapters for different AI programming tools, allowing them to understand and execute skill definitions. This layered design enables git-skill to flexibly adapt to new platforms and tools without rewriting core logic.

• Development Team Standardization: Provides a unified Git workflow standard for large organizations, ensuring consistency across AI tools.
• CI/CD Integration: Integrates with existing pipelines to execute standardized Git operations, ensuring process consistency and traceability.
• Open Source Project Management: Automates Issue classification and PR reviews to reduce maintenance burden.
• Enterprise Compliance: Standardized processes and audit tracking capabilities help meet regulatory requirements.

• PR Review: Automatically checks code style, identifies issues, generates review comments, and tracks status.
• Issue Classification: Automatically classifies and tags issues, evaluates priorities, detects duplicates, and sends auto-replies.
• Change Log Bot: Tracks code changes, classifies types, generates formatted logs, and integrates with release processes.
• Hotfix Workflow: Quickly creates branches, automates test validation, performs emergency releases, and conducts post-mortem analysis.

Getting Started：

1. Environment Preparation: Install supported AI programming tools (e.g., Claude Code, Cursor).
2. Git Platform Configuration: Set up access credentials for GitHub/GitLab/Gitea.
3. Import Skills: Import git-skill skill definitions into your AI tool.
4. Try the Release Workflow: Start with the Release SOP feature.

Conclusion: Through its proxy-agnostic design, git-skill provides a promising solution for Git workflow standardization in the AI era. It is not tied to specific tools and supports multiple platforms, making it worth the attention and trial of AI programming teams.