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003 Name Skill 771f59ba

ASecurity

Analyze git branches and generate comprehensive merge request descriptions with structured domain-based change categorization (bug fixes, enhancements, technical debt, documentation, testing). Use when preparing MR/PR descriptions, documenting branch changes, or analyzing git diffs for release notes. Works with any git repository without requiring JIRA or issue tracker integration.

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  • Added May 31, 2026
documentationpythongobashdockertestingrefactoringgitapidatabaseperformance

Works with

  • claude code
  • cli
  • api

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Scanned May 31, 2026

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SKILL.md
---
name: create-merge-request-changelog
description: Analyze git branches and generate comprehensive merge request descriptions with structured domain-based change categorization (bug fixes, enhancements, technical debt, documentation, testing). Use when preparing MR/PR descriptions, documenting branch changes, or analyzing git diffs for release notes. Works with any git repository without requiring JIRA or issue tracker integration.
argument-hint: '[base-branch] [head-branch]'
---
# Create Merge Request Changelog

Generate comprehensive, business-focused merge request descriptions by analyzing git changes. This skill adapts the structured analysis approach from JIRA release notes to work purely with git data.

## Quick Start

```bash
# Analyze current branch against main
/create-merge-request-changelog

# Analyze specific branch
/create-merge-request-changelog feature/new-auth

# Analyze specific branch against custom target
/create-merge-request-changelog feature/new-auth develop

# Analyze specific commit range
/create-merge-request-changelog abc123f def456g
```

## Workflow

### Option A: From Git Branch (Most Common)

#### Step 1: Extract Git Data

Run the Python CLI to gather commits, diffs, and statistics:

```bash
python scripts/analyze_git_changes.py [base_ref] [head_ref] --output-dir /tmp/mr-analysis
```

**Examples:**

```bash
# Current branch vs main (default)
python scripts/analyze_git_changes.py

# Specific branch vs develop
python scripts/analyze_git_changes.py develop feature/new-auth

# Specific commit range
python scripts/analyze_git_changes.py abc123f def456g

# Custom output directory
python scripts/analyze_git_changes.py main HEAD --output-dir ./analysis-output
```

**Output files created:**
- `commits_oneline.txt` - Concise commit list
- `commits_detailed.txt` - Full commit messages with metadata
- `changes.diff` - Complete unified diff
- `changes_stat.txt` - Diffstat summary
- `changed_files.txt` - File list with change status (A/M/D)
- `changes_numstat.txt` - Per-file line changes
- `summary.json` - Machine-readable statistics

### Option B: From Existing GitLab MR

#### Step 1: Fetch MR Data

Use the GitLab CLI integration to fetch existing MR data:

```bash
python scripts/fetch_gitlab_mr.py <mr-id> --output /tmp/mr-data.json
```

**Examples:**

```bash
# By MR ID
python scripts/fetch_gitlab_mr.py 123

# By !notation
python scripts/fetch_gitlab_mr.py !123

# By full URL
python scripts/fetch_gitlab_mr.py https://gitlab.com/org/project/-/merge_requests/123

# Without diff (faster)
python scripts/fetch_gitlab_mr.py 123 --no-diff

# Custom output file
python scripts/fetch_gitlab_mr.py 123 --output ./mr-metadata.json
```

**Output:** JSON file with MR metadata, commits, and diffs

### Step 2: Analyze Changes with AI

Load the analysis prompts and use them to categorize changes:

1. **Read the primary analysis prompt** from `references/analysis_prompts.md`
2. **Load the extracted git data** from Step 1 output files
3. **Run the analysis** using the prompt template with your git data
4. **Get structured JSON** with categorized changes

The AI analysis will:
- Categorize changes into domains (bug fixes, enhancements, tech debt, docs, testing, build/CI, non-functional)
- Extract intent from commit messages and diff patterns
- Identify breaking changes and migration requirements
- Determine affected components
- Assess impact on users and developers

### Step 3: Format MR Description

Use the Python formatter to generate polished markdown from AI analysis:

```bash
python scripts/format_mr_description.py <analysis-json> --output /tmp/mr-description.md
```

**Examples:**

```bash
# With markdown preview (default)
python scripts/format_mr_description.py analysis.json

# Without preview
python scripts/format_mr_description.py analysis.json --no-preview

# Custom output file
python scripts/format_mr_description.py analysis.json --output ./MR_DESCRIPTION.md

# With custom title
python scripts/format_mr_description.py analysis.json --title "feat: Add authentication system"
```

The formatter automatically:
- Applies templates from `references/output_template.md`
- Formats each category (bug fixes, enhancements, tech debt, etc.)
- Truncates long file lists (>5 files)
- Highlights breaking changes
- Generates deployment notes if needed
- Renders markdown preview with Rich

### Step 4: Use the Description

The final MR description is ready to:
- Copy to clipboard (from preview or file)
- Paste into GitLab/GitHub MR/PR
- Save as documentation
- Use in release notes

**Integration examples:**

```bash
# GitLab MR creation
python scripts/format_mr_description.py analysis.json --output /tmp/mr.md --no-preview
glab mr create --fill --description "$(cat /tmp/mr.md)"

# GitHub PR creation
python scripts/format_mr_description.py analysis.json --output /tmp/pr.md --no-preview
gh pr create --fill --body-file /tmp/pr.md

# Copy to clipboard (macOS)
python scripts/format_mr_description.py analysis.json --no-preview --output - | pbcopy

# Copy to clipboard (Linux)
python scripts/format_mr_description.py analysis.json --no-preview --output - | xclip -selection clipboard
```

## Change Categorization Guide

### Bug Fixes πŸ›

**Indicators:**
- Commit keywords: "fix", "bug", "issue", "correct", "resolve"
- Diff patterns: Added error handling, validation, defensive checks

**What to capture:**
- What was broken
- How it's now fixed
- Who/what was affected
- Migration steps if behavior changed

### Enhancements ✨

**Indicators:**
- Commit keywords: "feat", "add", "improve", "enhance", "implement"
- Diff patterns: New functions/classes, expanded APIs, additional features

**What to capture:**
- New capability added
- Benefits to users/developers
- How to use it
- API additions or changes

### Technical Debt πŸ—οΈ

**Indicators:**
- Commit keywords: "refactor", "cleanup", "simplify", "optimize"
- Diff patterns: Code reorganization, reduced duplication, dependency updates

**What to capture:**
- Why refactoring was needed
- What changed internally
- How it improves maintainability/performance
- Developer-facing improvements

### Documentation πŸ“š

**Indicators:**
- File patterns: `*.md`, `*.rst`, README, docs/
- Diff patterns: Only documentation files or comments changed

**What to capture:**
- What documentation was added/updated
- Where to find it
- Why it helps users/developers

### Testing πŸ§ͺ

**Indicators:**
- File patterns: `test_*.py`, `*.spec.js`, `tests/`, `__tests__/`
- Commit keywords: "test", "coverage", "spec"

**What to capture:**
- What's now tested
- Test type (unit/integration/e2e)
- Coverage improvements

### Build & CI πŸ”§

**Indicators:**
- File patterns: `.github/workflows/`, `.gitlab-ci.yml`, `Dockerfile`, build scripts
- Commit keywords: "ci", "build", "deploy", "docker"

**What to capture:**
- Build/deployment changes
- Workflow improvements
- Developer experience enhancements

### Non-Functional 🧹

**Indicators:**
- Commit keywords: "chore", "style", "format", "lint"
- Diff patterns: Whitespace, formatting, import ordering, minor config

**What to capture:**
- Type (formatting/linting/config/deps)
- Brief description
- Files affected

## Breaking Changes Detection

Automatically detect and highlight breaking changes:

**Detection patterns:**
- Commit messages: "BREAKING CHANGE", "breaking:", "incompatible"
- API changes: Removed public functions, changed signatures
- Configuration: Required new environment variables
- Database: Schema migrations, data migrations

**Required information:**
- What changed and why it breaks compatibility
- Migration steps for users
- Affected APIs or components
- Commit references

## Advanced Usage

### Custom Component Mapping

Map files to logical components for better organization:

```json
{
  "src/auth/*": "Authentication",
  "src/api/*": "API Layer",
  "src/database/*": "Data Layer",
  "tests/*": "Test Suite",
  "docs/*": "Documentation"
}
```

### Conventional Commits Integration

The skill automatically recognizes conventional commit prefixes:

- `fix:` β†’ Bug Fixes
- `feat:` β†’ Enhancements
- `refactor:` β†’ Technical Debt
- `docs:` β†’ Documentation
- `test:` β†’ Testing
- `chore:` β†’ Non-Functional
- `ci:` β†’ Build & CI
- `perf:` β†’ Performance (Enhancement with perf tag)
- `style:` β†’ Non-Functional (formatting)

### GitLab/GitHub CLI Integration

Use with GitLab or GitHub CLI tools:

```bash
# Generate description and create GitLab MR
/create-merge-request-changelog
# ... Copy output to clipboard ...
glab mr create --fill --description "$(pbpaste)"

# Generate description and create GitHub PR
/create-merge-request-changelog
# ... Save output to file ...
gh pr create --fill --body-file /tmp/mr-description.md
```

## Example Output

```markdown
# feat: Add user authentication with JWT and refresh tokens

## Summary

This merge request implements a complete user authentication system using JWT tokens with refresh token rotation. The implementation includes password hashing with bcrypt, token expiration handling, and secure session management.

## Statistics

- **Commits**: 12
- **Files Changed**: 18
- **Lines Added**: 1,247
- **Lines Deleted**: 89

## Changes by Category

### ✨ Enhancements

- **JWT-based authentication system with refresh token rotation**
  - **Feature:** Complete authentication flow with access tokens (15min) and refresh tokens (7 days)
  - **Benefits:** Secure, stateless authentication with automatic token refresh for better UX
  - **Usage:** POST /api/auth/login with credentials, use returned access token in Authorization header
  - **Files:** `src/auth/jwt_service.py`, `src/auth/token_store.py`, `src/api/auth_routes.py`
  - **Technical Details:** Uses RS256 algorithm, tokens stored in Redis, automatic cleanup of expired tokens

- **Password strength validation and bcrypt hashing**
  - **Feature:** Enforces strong passwords (min 12 chars, mixed case, numbers, symbols) with bcrypt hashing
  - **Benefits:** Prevents weak passwords and protects against rainbow table attacks
  - **Usage:** Automatic validation on user registration and password changes
  - **Files:** `src/auth/password_validator.py`, `src/models/user.py`

### πŸ§ͺ Testing

- **Comprehensive authentication test suite**: Added 47 unit tests and 12 integration tests covering all auth flows
  - **Type:** unit, integration
  - **Files:** `tests/unit/test_jwt_service.py`, `tests/integration/test_auth_flow.py`

### πŸ“š Documentation

- **Authentication API documentation with examples**: Complete API docs with curl examples and error codes
  - **Location:** `docs/api/authentication.md`, added to main README
  - **Importance:** Enables developers to integrate authentication without trial-and-error

## Components Affected

- **Authentication**: Complete new authentication system
- **API Layer**: New /api/auth endpoints
- **User Model**: Added password hashing and token tracking
- **Database**: New refresh_tokens table

## Breaking Changes ⚠️

- **User model now requires password hashing**
  - **Migration:** Run `python scripts/migrate_passwords.py` to hash existing plaintext passwords
  - **Affected:** `src/models/user.py`, all user creation code
  - **Commits:** abc123f, def456g

---

*Generated by Claude Code `/create-merge-request-changelog` skill*
```

## Tips for Best Results

1. **Use descriptive commit messages**: The AI analysis works better with clear commit messages
2. **Follow conventional commits**: Helps with automatic categorization
3. **Break up large MRs**: Smaller, focused changes generate clearer descriptions
4. **Review and edit**: The AI-generated description is a starting point - edit for your specific context
5. **Include context**: Add project-specific details or link to related issues/docs

## Troubleshooting

### Issue: Analysis script fails

**Check:**
- Are you in a git repository?
- Does the base branch exist?
- Are there commits between base and head?

**Solution:**
```bash
git rev-parse --git-dir  # Verify git repo
git branch -a | grep <branch-name>  # Verify branch exists
git log <base>..<head>  # Verify commits exist
```

### Issue: Too many files in diff

**Solution:** Use filters to focus analysis:
```bash
# Exclude generated files
git diff <base>..<head> -- . ':(exclude)dist/*' ':(exclude)*.lock'
```

### Issue: AI categorization incorrect

**Solution:** The analysis is based on patterns - you can:
- Override categories manually in the final description
- Improve commit messages for future MRs
- Add project-specific detection patterns to the prompts

## Complete Workflow Examples

### Example 1: New MR from Git Branch

```bash
# 1. Extract git data
python scripts/analyze_git_changes.py main feature/auth-system --output-dir /tmp/analysis

# 2. Analyze with AI (using prompts from references/analysis_prompts.md)
# - Read commits and diffs from /tmp/analysis
# - Categorize changes using the primary analysis prompt
# - Save categorized JSON to /tmp/analysis/categorized.json

# 3. Format into MR description
python scripts/format_mr_description.py /tmp/analysis/categorized.json --output /tmp/mr-desc.md

# 4. Create GitLab MR
glab mr create --fill --description "$(cat /tmp/mr-desc.md)"
```

### Example 2: Update Existing GitLab MR

```bash
# 1. Fetch existing MR data
python scripts/fetch_gitlab_mr.py 123 --output /tmp/mr-data.json

# 2. Analyze with AI (enhance existing description)
# - Read MR metadata from /tmp/mr-data.json
# - Re-analyze commits/diffs with updated prompts
# - Save enhanced JSON to /tmp/enhanced.json

# 3. Format improved description
python scripts/format_mr_description.py /tmp/enhanced.json --output /tmp/updated-mr.md

# 4. Update MR description
glab mr update 123 --description "$(cat /tmp/updated-mr.md)"
```

### Example 3: Quick Analysis for Review

```bash
# Quick preview without saving files
python scripts/analyze_git_changes.py | \
  python scripts/format_mr_description.py --preview
```

## CLI Scripts Reference

### analyze_git_changes.py

Extracts git data between two references.

**Usage:** `python scripts/analyze_git_changes.py [BASE_REF] [HEAD_REF] [OPTIONS]`

**Options:**
- `--output-dir PATH`: Output directory (default: current directory)

**Defaults:** BASE_REF=main, HEAD_REF=HEAD

### fetch_gitlab_mr.py

Fetches GitLab MR data using glab CLI.

**Usage:** `python scripts/fetch_gitlab_mr.py MR_ID [OPTIONS]`

**Options:**
- `--output PATH`: Output JSON file (default: stdout)
- `--no-diff`: Skip diff fetching (faster)

**MR ID formats:** `123`, `!123`, or full URL

### format_mr_description.py

Formats AI analysis into markdown MR description.

**Usage:** `python scripts/format_mr_description.py ANALYSIS_JSON [OPTIONS]`

**Options:**
- `--output PATH`: Output file (default: stdout, `-` for explicit stdout)
- `--title TEXT`: Custom MR title
- `--no-preview`: Skip markdown preview
- `--max-files INT`: Max files to show per change (default: 5)

## Resources

- **scripts/analyze_git_changes.py**: Python CLI to extract git data
- **scripts/fetch_gitlab_mr.py**: Python CLI to fetch GitLab MR data via glab
- **scripts/format_mr_description.py**: Python CLI to format AI analysis into markdown
- **scripts/README.md**: Comprehensive CLI documentation and examples
- **references/analysis_prompts.md**: AI prompts for categorization and formatting
- **references/output_template.md**: MR description template structure

Files in this skill

  • README.md1023 B
  • skill.md15 KB

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