Commit Message Generator (Grade A) logo

Commit Message Generator (Grade A)Security-tested development skill for Claude AI. Grade A. Generate structured Conventional Commit messages from staged changes, diffs, or descriptions. Use when the user asks to write a commit message

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Daniel NikulshynReviewed by Daniel Nikulshyn·Updated July 2026

Overview

The Commit Message Generator is a development skill for Claude AI that generates structured Conventional Commit messages from staged changes, diffs, or descriptions. It is used when a user asks to write a commit message. The skill analyzes code changes and produces well-structured Conventional Commit messages following project conventions. It works by gathering change context, classifying the change type, determining the scope, writing a subject line and body, and adding a footer if needed. The generator ensures that commit messages are in the Conventional Commits format, do not include secrets or internal information, and are concise and descriptive.

Key features

  • Generates Conventional Commit messages
  • Analyzes code changes and diffs
  • Classifies change types (feat, fix, docs, style, refactor, test, chore, perf, ci)
  • Determines scope and writes subject line and body
  • Adds footer with breaking changes, issue references, or co-authors

Pricing

Model
Free
Category
Skills
Rating
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Use cases

Feature development

Generate structured Conventional Commit messages when implementing new features or capabilities.

Bug fixing

Produce well-formatted commit messages for bug fixes and other changes, including references to resolved issues.

Code maintenance

Use the commit message generator to write commit messages for refactorings, documentation updates, and performance improvements.

Pros & Cons

Pros

  • Ensures commit messages follow Conventional Commits format
  • Saves time by automating commit message generation
  • Improves commit message quality and consistency
  • Reduces errors and inconsistencies in commit messages

Cons

  • May not handle very complex or nuanced changes
  • Requires a Git repository and staged changes to work effectively
  • May not always perfectly capture the intent or scope of changes

Battle record

Across 1 battle in the Pantheon.

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Q&A

What You Can Customize?

You can customize project identity (name, description, repo URL), tech stack (languages, frameworks, tools), directory paths, business domain entities, code patterns, testing quality gates, database conventions, internal package scopes, and Git/workflow conventions such as branch prefixes and commit formats.

Asked by Petros Georgiou · Oct 11, 2025

Why You Should Use This?

Individuals save over 30% token usage, avoid repeating standards, gain security guardrails, and get instant scaffolding. Teams benefit from consistent AI behavior, rapid onboarding, codified patterns, and compounded cost savings. Organizations get always-on compliance, uniform standards across many projects, central governance, and measurable ROI.

Asked by Salome Beridze · Oct 12, 2025

What it detects?

It detects language files like tsconfig.json, go.mod, Cargo.toml, requirements.txt, pom.xml, and file extensions. It also identifies frameworks from dependencies in package.json or requirements.txt (e.g., React, Express, Django, Spring), database configurations (ORM configs, .sql files, migration folders), testing setups (jest, vitest, pytest, cypress, playwright), infrastructure files (Dockerfile, terraform, cdk.json, serverless.yml), and CI/CD pipelines (.github/workflows, .gitlab-ci.yml, Jenkinsfile).

Asked by Xavier Costa · Sep 24, 2025

What's Inside?

The tool includes multiple layers: 47 always-on rules that enforce coding standards, 62 agents for complex tasks, 50 skills that provide guided workflows, 37 commands for quick actions, 12 hooks for automation scripts, and 9 templates for scaffolding handlers, components, and tests.

Asked by Katarzyna Zielinska · Jul 29, 2025

How It Works?

Layer 1 — Pre-Processing: Hooks inject project context and block dangerous commands before your prompt reaches the AI. Layer 2 — Rules Engine: 47 always-on rules enforce token efficiency, security, architecture, code standards, database conventions, and testing thresholds. Layer 3 — Specialized Processing: The right component activates — an agent, skill, or command — based on your prompt. Layer 4 — Post-Processing: Hooks validate output, auto-format, scan for secrets, and verify coverage.

Asked by Mustafa Yilmaz · Jul 14, 2025

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