changelog-automation

wshobson/agents · updated Apr 8, 2026

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$npx skills add https://github.com/wshobson/agents --skill changelog-automation
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summary

Automate changelog generation from commits following Conventional Commits and Keep a Changelog standards.

  • Supports multiple implementation methods: Conventional Changelog (Node.js), standard-version, semantic-release with full CI/CD automation, git-cliff (Rust-based), and commitizen (Python)
  • Enforces Conventional Commits format with commitlint validation, mapping commit types (feat, fix, perf, etc.) to changelog sections automatically
  • Includes semantic versioning integration, GitHub
skill.md

Changelog Automation

Patterns and tools for automating changelog generation, release notes, and version management following industry standards.

When to Use This Skill

  • Setting up automated changelog generation
  • Implementing Conventional Commits
  • Creating release note workflows
  • Standardizing commit message formats
  • Generating GitHub/GitLab release notes
  • Managing semantic versioning

Core Concepts

1. Keep a Changelog Format

# Changelog

All notable changes to this project will be documented in this file.

The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.1.0/),
and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).

## [Unreleased]

### Added

- New feature X

## [1.2.0] - 2024-01-15

### Added

- User profile avatars
- Dark mode support

### Changed

- Improved loading performance by 40%

### Deprecated

- Old authentication API (use v2)

### Removed

- Legacy payment gateway

### Fixed

- Login timeout issue (#123)

### Security

- Updated dependencies for CVE-2024-1234

[Unreleased]: https://github.com/user/repo/compare/v1.2.0...HEAD
[1.2.0]: https://github.com/user/repo/compare/v1.1.0...v1.2.0

2. Conventional Commits

<type>[optional scope]: <description>

[optional body]

[optional footer(s)]
Type Description Changelog Section
feat New feature Added
fix Bug fix Fixed
docs Documentation (usually excluded)
style Formatting (usually excluded)
refactor Code restructure Changed
perf Performance Changed
test Tests (usually excluded)
chore Maintenance (usually excluded)
ci CI changes (usually excluded)
build Build system (usually excluded)
revert Revert commit Removed

3. Semantic Versioning

MAJOR.MINOR.PATCH

MAJOR: Breaking changes (feat! or BREAKING CHANGE)
MINOR: New features (feat)
PATCH: Bug fixes (fix)

Implementation

Method 1: Conventional Changelog (Node.js)

# Install tools
npm install -D @commitlint/cli @commitlint/config-conventional
npm install -D husky
npm install -D standard-version
# or
npm install -D semantic-release

# Setup commitlint
cat > commitlint.config.js << 'EOF'
module.exports = {
  extends: ['@commitlint/config-conventional'],
  rules: {
    'type-enum': [
      2,
      'always',
      [
        'feat',
        'fix',
        'docs',
        'style',
        'refactor',
        'perf',
        'test',
        'chore',
        'ci',
        'build',
        'revert',
      ],
    ],
    'subject-case': [2, 'never', ['start-case', 'pascal-case', 'upper-case']],
    'subject-max-length': [2, 'always', 72],
  },
};
EOF

# Setup husky
npx husky init
echo "npx --no -- commitlint --edit \$1" > .husky/commit-msg

Method 2: standard-version Configuration

// .versionrc.js
module.exports = {
  types: [
    { type: "feat", section: "Features" },
    { type: "fix", section: "Bug Fixes" },
    { type: "perf", section: "Performance Improvements" },
    { type: "revert", section: "Reverts" },
    { type: "docs", section: "Documentation", hidden: true },
    { type: "style", section: "Styles", hidden: true },
    { type: "chore", section: "Miscellaneous", hidden: true },
    { type: "refactor", section: "Code Refactoring", hidden: true },
    { type: "test", section: "Tests", hidden: true },
    { type: "build", section: "Build System", hidden: true },
    { type: "ci", section: "CI/CD", hidden: true },
  ],
  commitUrlFormat: "{{host}}/{{owner}}/{{repository}}/commit/{{hash}}",
  compareUrlFormat:
    "{{host}}/{{owner}}/{{repository}}/compare/{{previousTag}}...{{currentTag}}",
  issueUrlFormat: "{{host}}/{{owner}}/{{repository}}/issues/{{id}}",
  userUrlFormat: "{{host}}/{{user}}",
  releaseCommitMessageFormat: "chore(release): {{currentTag}}",
  scripts: {
    prebump: 'echo "Running prebump"',
    postbump: 'echo "Running postbump"',
    prechangelog: 'echo "Running prechangelog"',
    postchangelog: 'echo "Running postchangelog"',
  },
};
// package.json scripts
{
  "scripts": {
    "release": "standard-version",
    "release:minor": "standard-version --release-as minor",
    "release:major": "standard-version --release-as major",
    "release:patch": "standard-version --release-as patch",
    "release:dry": "standard-version --dry-run"
  }
}

Method 3: semantic-release (Full Automation)

// release.config.js
module.exports = {
  branches: [
    "main",
    { name: "beta", prerelease: true },
    { name: "alpha", prerelease: true },
  ],
  plugins: [
    "@semantic-release/commit-analyzer",
    "@semantic-release/release-notes-generator",
    [
how to use changelog-automation

How to use changelog-automation on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add changelog-automation
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/wshobson/agents --skill changelog-automation

The skills CLI fetches changelog-automation from GitHub repository wshobson/agents and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/changelog-automation

Reload or restart Cursor to activate changelog-automation. Access the skill through slash commands (e.g., /changelog-automation) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

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Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.675 reviews
  • Harper Ghosh· Dec 28, 2024

    Useful defaults in changelog-automation — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Aarav Wang· Dec 28, 2024

    changelog-automation is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Meera Desai· Dec 20, 2024

    changelog-automation fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Sofia Sethi· Dec 12, 2024

    changelog-automation has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Fatima Huang· Dec 12, 2024

    changelog-automation has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Aditi Sharma· Dec 4, 2024

    changelog-automation reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Aditi Kapoor· Nov 23, 2024

    I recommend changelog-automation for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Maya Sanchez· Nov 19, 2024

    Registry listing for changelog-automation matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Ishan Bhatia· Nov 19, 2024

    Solid pick for teams standardizing on skills: changelog-automation is focused, and the summary matches what you get after install.

  • Ira Ramirez· Nov 7, 2024

    changelog-automation fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

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