Changelog Generator

A high-performance changelog generator for Git repositories that automatically creates comprehensive, well-formatted changelogs from your git history and GitHub pull requests.

Features

One-pass git history walking: Efficiently processes entire repository history in a single pass
Automatic PR detection: Extracts pull request information from merge commits
GitHub API integration: Fetches detailed PR information including commits, authors, and descriptions
Smart caching: SQLite-based caching for instant incremental updates
Unreleased changes: Tracks all commits since the last release
Concurrent processing: Parallel GitHub API calls for improved performance
Flexible output: Generate complete changelogs or target specific versions
GraphQL optimization: Ultra-fast PR fetching using GitHub GraphQL API (~5-10 calls vs 1000s)
Intelligent sync: Automatically syncs new PRs every 24 hours or when missing PRs are detected
AI-powered summaries: Optional Fabric integration for enhanced changelog summaries
Advanced caching: Content-based change detection for AI summaries with hash comparison
Author type detection: Distinguishes between users, bots, and organizations
Lightning-fast incremental updates: SHA→PR mapping for instant git operations

Installation

bash

go install github.com/danielmiessler/fabric/cmd/generate_changelog@latest

Usage

Basic usage (generate complete changelog)

bash

generate_changelog

Save to file

bash

generate_changelog -o CHANGELOG.md

Generate for specific version

bash

generate_changelog -v v1.4.244

Limit to recent versions

bash

generate_changelog -l 10

Using GitHub token for private repos or higher rate limits

bash

export GITHUB_TOKEN=your_token_here
generate_changelog

# Or pass directly
generate_changelog --token your_token_here

AI-enhanced summaries

bash

# Enable AI summaries using Fabric
generate_changelog --ai-summarize

# Use custom model for AI summaries
FABRIC_CHANGELOG_SUMMARIZE_MODEL=claude-opus-4 generate_changelog --ai-summarize

Cache management

bash

# Rebuild cache from scratch
generate_changelog --rebuild-cache

# Force a full PR sync from GitHub
generate_changelog --force-pr-sync

# Disable cache usage
generate_changelog --no-cache

# Use custom cache location
generate_changelog --cache /path/to/cache.db

Command Line Options

Flag	Short	Description	Default
`--repo`	`-r`	Repository path	`.` (current directory)
`--output`	`-o`	Output file	stdout
`--limit`	`-l`	Limit number of versions	0 (all)
`--version`	`-v`	Generate for specific version
`--save-data`		Save version data to JSON	false
`--cache`		Cache database file	`./cmd/generate_changelog/changelog.db`
`--no-cache`		Disable cache usage	false
`--rebuild-cache`		Rebuild cache from scratch	false
`--force-pr-sync`		Force a full PR sync from GitHub	false
`--token`		GitHub API token	`$GITHUB_TOKEN`
`--ai-summarize`		Generate AI-enhanced summaries using Fabric	false
`--release`		Update GitHub release description with AI summary for version

Output Format

The generated changelog follows this structure:

markdown

# Changelog

## Unreleased

### PR [#1601](url) by [author](profile): PR Title
- Change description 1
- Change description 2

### Direct commits
- Direct commit message 1
- Direct commit message 2

## v1.4.244 (2025-07-09)

### PR [#1598](url) by [author](profile): PR Title
- Change description
...

How It Works

Git History Walking: The tool walks through your git history from newest to oldest commits
Version Detection: Identifies version bump commits (pattern: "Update version to vX.Y.Z")
PR Extraction: Detects merge commits and extracts PR numbers
GitHub API Calls: Fetches detailed PR information in parallel batches
Change Extraction: Extracts changes from PR commit messages or PR body
Formatting: Generates clean, organized markdown output

Performance

Native Go libraries: Uses go-git and go-github for maximum performance
Concurrent API calls: Processes up to 10 GitHub API requests in parallel
Smart caching: SQLite cache eliminates redundant API calls
Incremental updates: Only processes new commits on subsequent runs
GraphQL optimization: Uses GitHub GraphQL API to fetch all PR data in ~5-10 calls
AI-powered summaries: Optional Fabric integration with intelligent caching
Content-based change detection: AI summaries only regenerated when content changes
Lightning-fast git operations: SHA→PR mapping stored in database for instant lookups

Major Optimization: GraphQL + Advanced Caching

The tool has been optimized to drastically reduce GitHub API calls and improve performance:

Previous approach: Individual API calls for each PR (2 API calls per PR)

For a repo with 500 PRs: 1,000 API calls

Current approach: GraphQL batch fetching with intelligent caching

For a repo with 500 PRs: ~5-10 GraphQL calls (initial fetch) + 0 calls (subsequent runs with cache)
99%+ reduction in API calls after initial run!

The optimization includes:

GraphQL Batch Fetch: Uses GitHub's GraphQL API to fetch all merged PRs with commits in minimal calls
Smart Caching: Stores complete PR data, commits, and SHA mappings in SQLite
Incremental Sync: Only fetches PRs merged after the last sync timestamp
Automatic Refresh: PRs are synced every 24 hours or when missing PRs are detected
AI Summary Caching: Content-based change detection prevents unnecessary AI regeneration
Fallback Support: If GraphQL fails, falls back to REST API batch fetching
Lightning Git Operations: Pre-computed SHA→PR mappings for instant commit association

Requirements

Go 1.24+ (for installation from source)
Git repository
GitHub token (optional, for private repos or higher rate limits)
Fabric CLI (optional, for AI-enhanced summaries)

Authentication

The tool supports GitHub authentication via:

Environment variable: export GITHUB_TOKEN=your_token
Command line flag: --token your_token
.env file in the same directory as the binary

Environment File Support

Create a .env file next to the generate_changelog binary:

bash

GITHUB_TOKEN=your_github_token_here
FABRIC_CHANGELOG_SUMMARIZE_MODEL=claude-sonnet-4-20250514

The tool automatically loads .env files for convenient configuration management.

Without authentication, the tool is limited to 60 GitHub API requests per hour.

Caching

The SQLite cache stores:

Version information and commit associations
Pull request details (title, body, commits, authors)
Last processed commit SHA for incremental updates
Last PR sync timestamp for intelligent refresh
AI summaries with content-based change detection
SHA→PR mappings for lightning-fast git operations

Cache benefits:

Instant changelog regeneration
Drastically reduced GitHub API usage (99%+ reduction after initial run)
Offline changelog generation (after initial cache build)
Automatic PR data refresh every 24 hours
Batch database transactions for better performance
Content-aware AI summary regeneration

AI-Enhanced Summaries

The tool can generate AI-powered summaries using Fabric for more polished, professional changelogs:

bash

# Enable AI summarization
generate_changelog --ai-summarize

# Custom model (default: claude-sonnet-4-20250514)
FABRIC_CHANGELOG_SUMMARIZE_MODEL=claude-opus-4 generate_changelog --ai-summarize

AI Summary Features

Content-based change detection: AI summaries are only regenerated when version content changes
Intelligent caching: Preserves existing summaries and only processes changed versions
Content hash comparison: Uses SHA256 hashing to detect when "Unreleased" content changes
Automatic fallback: Falls back to raw content if AI processing fails
Error detection: Identifies and handles AI processing errors gracefully
Minimum content filtering: Skips AI processing for very brief content (< 256 characters)

AI Model Configuration

Set the model via environment variable:

bash

export FABRIC_CHANGELOG_SUMMARIZE_MODEL=claude-opus-4
# or
export FABRIC_CHANGELOG_SUMMARIZE_MODEL=gpt-5.2

AI summaries are cached and only regenerated when:

Version content changes (detected via hash comparison)
No existing AI summary exists for the version
Force rebuild is requested

Contributing

This tool is part of the Fabric project. Contributions are welcome!

License

The MIT License. Same as the Fabric project.