MCP HubMCP Hub
スキル一覧に戻る

generating-conventional-commits

jeremylongshore
更新日 Today
89 閲覧
712
74
712
GitHubで表示
メタai

について

このスキルは、ステージングされたGitの変更を分析し、従来のコミット仕様に従ったコミットメッセージを自動生成します。コード変更をコミットする準備をする際に、開発者が明確で標準化されたコミットメッセージを素早く作成するのに役立ちます。「コミットメッセージを生成」などのコマンドで起動でき、プロジェクトのGitワークフローの一貫性を維持することができます。

クイックインストール

Claude Code

推奨
プラグインコマンド推奨
/plugin add https://github.com/jeremylongshore/claude-code-plugins-plus
Git クローン代替
git clone https://github.com/jeremylongshore/claude-code-plugins-plus.git ~/.claude/skills/generating-conventional-commits

このコマンドをClaude Codeにコピー&ペーストしてスキルをインストールします

ドキュメント

Overview

This skill helps you create well-formatted, informative commit messages that follow the conventional commits standard, improving collaboration and automation in your Git workflow. It saves you time and ensures consistency across your project.

How It Works

  1. Analyze Changes: The skill analyzes the staged changes in your Git repository.
  2. Generate Suggestion: It uses AI to generate a commit message based on the analyzed changes, adhering to the conventional commits format (e.g., feat: add new feature, fix: correct bug).
  3. Present to User: The generated commit message is presented to you for review and acceptance.

When to Use This Skill

This skill activates when you need to:

  • Create a commit message after making code changes.
  • Ensure your commit messages follow the conventional commits standard.
  • Save time writing commit messages manually.

Examples

Example 1: Adding a New Feature

User request: "Generate a commit message for these changes."

The skill will:

  1. Analyze the staged changes related to a new feature.
  2. Generate a commit message like feat: Implement user authentication.

Example 2: Fixing a Bug

User request: "Create a commit for the bug fix."

The skill will:

  1. Analyze the staged changes related to a bug fix.
  2. Generate a commit message like fix: Resolve issue with incorrect password reset.

Best Practices

  • Stage Changes: Ensure all relevant changes are staged before using the skill.
  • Review Carefully: Always review the generated commit message before accepting it.
  • Customize if Needed: Feel free to customize the generated message to provide more context.

Integration

This skill integrates with your Git workflow, providing a convenient way to generate commit messages directly within Claude Code. It complements other Git-related skills in the DevOps Automation Pack, such as /branch-create and /pr-create.

GitHub リポジトリ

jeremylongshore/claude-code-plugins-plus
パス: backups/skills-batch-20251204-000554/plugins/packages/devops-automation-pack/skills/devops-automation-pack
aiautomationclaude-codedevopsmarketplacemcp

関連スキル

evaluating-llms-harness

テスト

This Claude Skill runs the lm-evaluation-harness to benchmark LLMs across 60+ standardized academic tasks like MMLU and GSM8K. It's designed for developers to compare model quality, track training progress, or report academic results. The tool supports various backends including HuggingFace and vLLM models.

スキルを見る

sglang

メタ

SGLang is a high-performance LLM serving framework that specializes in fast, structured generation for JSON, regex, and agentic workflows using its RadixAttention prefix caching. It delivers significantly faster inference, especially for tasks with repeated prefixes, making it ideal for complex, structured outputs and multi-turn conversations. Choose SGLang over alternatives like vLLM when you need constrained decoding or are building applications with extensive prefix sharing.

スキルを見る

cloudflare-turnstile

メタ

This skill provides comprehensive guidance for implementing Cloudflare Turnstile as a CAPTCHA-alternative bot protection system. It covers integration for forms, login pages, API endpoints, and frameworks like React/Next.js/Hono, while handling invisible challenges that maintain user experience. Use it when migrating from reCAPTCHA, debugging error codes, or implementing token validation and E2E tests.

スキルを見る

langchain

メタ

LangChain is a framework for building LLM applications using agents, chains, and RAG pipelines. It supports multiple LLM providers, offers 500+ integrations, and includes features like tool calling and memory management. Use it for rapid prototyping and deploying production systems like chatbots, autonomous agents, and question-answering services.

スキルを見る