git-summary

A comprehensive CLI tool for analyzing and summarizing GitHub user activity

Extract, analyze, and summarize GitHub user activity across repositories and projects. Get comprehensive insights into commits, issues, pull requests, and other GitHub events with beautiful CLI output.

🎯 NEW: Adaptive Comprehensive Analysis - Overcomes GitHub's 300-event limitation with intelligent analysis strategies. Automatically detects user types and adapts analysis approach for complete coverage of activity history, even for high-volume users and automation accounts.

🚀 Quick Start

Prerequisites

Python 3.12 or higher
UV package manager (recommended) or pip

Installation

Option 1: Using UV (Recommended)

# Clone the repository
git clone https://github.com/samtexas/git-summary.git
cd git-summary

# Install dependencies
uv sync

# Set up authentication
uv run git-summary auth

Option 2: Using pip

# Clone the repository
git clone https://github.com/samtexas/git-summary.git
cd git-summary

# Install in development mode
pip install -e .

# Set up authentication
git-summary auth

First Run

Set up GitHub authentication (one time setup):
```
uv run git-summary auth
```
Analyze a GitHub user:
```
uv run git-summary summary octocat
```

📖 Usage

Basic Commands

# Analyze a user's activity (last 7 days)
git-summary summary username

# Analyze with custom time range
git-summary summary username --days 30

# Save output to file
git-summary summary username --output results.json

# Interactive mode - prompts for username and token if needed
git-summary summary

🚀 Adaptive Analysis (NEW)

Overcome GitHub's 300-event API limitation with intelligent analysis strategies:

# Automatic strategy selection (recommended)
git-summary summary username --days 30

# Force comprehensive multi-source analysis for power users
git-summary summary username --comprehensive

# Limit repositories for focused analysis
git-summary summary username --max-repos 10

# Force specific strategy (mainly for testing)
git-summary summary username --force-strategy intelligence_guided
git-summary summary username --force-strategy multi_source

How it works:

Regular Users (98% of cases): Fast intelligence-guided analysis optimizes for most active repositories
Power Users & Bots: Comprehensive multi-source discovery ensures complete coverage
Automatic Detection: Analyzes user patterns to select optimal strategy
No 300-Event Limit: Accesses unlimited activity history through intelligent API usage

🤖 AI-Powered Analysis

Generate intelligent, narrative summaries of GitHub activity with comprehensive engagement tracking. AI analysis includes commits, pull requests, issues, reviews, comments, branch management, and documentation contributions across all repositories or filtered to specific projects:

# Technical analysis for engineers
git-summary ai-summary username --persona "Tech Analyst"

# Business-focused insights for stakeholders
git-summary ai-summary username --persona "Product Manager"

# Engaging first-person narratives
git-summary ai-summary username --persona "Ghost Writer"

# Team collaboration insights
git-summary ai-summary username --persona "Team Lead"

# Data-driven metrics analysis
git-summary ai-summary username --persona "Data Analyst"

# Focus analysis on specific repositories
git-summary ai-summary username --repo owner/repo-name

# Analyze multiple repositories
git-summary ai-summary username --repo myorg/frontend --repo myorg/backend

# Combine with time range and persona
git-summary ai-summary username --days 30 --repo myproject/api --persona "Tech Analyst"

AI Command Options

git-summary ai-summary [USERNAME] [OPTIONS]

Options:
  --persona, -p TEXT       AI persona for analysis style (default: "Tech Analyst")
  --model, -m TEXT         AI model to use (default: "claude-3-7-sonnet-latest")
  --days, -d INTEGER       Number of days to analyze (default: 7)
  --output, -o TEXT        Output file (.md or .json format)
  --repo, -r TEXT          Filter events to specific repositories (can be used multiple times)
  --max-events INTEGER     Limit number of events processed
  --token-budget INTEGER   AI token budget for analysis (default: 8000)
  --estimate-cost          Show cost estimate before processing

Available Personas

Persona	Focus	Best For
Tech Analyst	Technical depth, code quality	Engineering teams, code reviews
Product Manager	Business impact, user value	Stakeholder updates, roadmaps
Ghost Writer	Personal narratives, storytelling	Portfolios, blog posts, retrospectives
Team Lead	Collaboration, team health	Team management, performance reviews
Data Analyst	Metrics, trends, quantitative insights	KPI tracking, trend analysis

👉 Complete AI Personas Guide - Learn how to create custom personas

Authentication Commands

# Set up GitHub Personal Access Token (interactive)
git-summary auth

# Check current authentication status
git-summary auth-status

# Remove stored token
git-summary auth-remove

# Set up AI API keys for analysis features
git-summary ai-auth anthropic    # For Claude models
git-summary ai-auth openai       # For GPT models
git-summary ai-auth groq         # For Groq models

# Check AI API key status
git-summary ai-auth-status

# Remove AI API key
git-summary ai-auth-remove anthropic

# Persona management
git-summary personas              # List available personas
git-summary personas --sources    # Show persona sources
git-summary create-persona "Custom Name" --type basic
git-summary reload-personas       # Reload custom personas
git-summary persona-info "Persona Name"

All Available Options

git-summary summary [USERNAME] [OPTIONS]

Arguments:
  USERNAME    GitHub username to analyze (optional, will prompt if not provided)

Options:
  --token, -t TEXT             GitHub Personal Access Token
  --days, -d INTEGER           Number of days to analyze (default: 7)
  --output, -o TEXT            Output file (JSON format)
  --max-events INTEGER         Maximum number of events to process

  # NEW: Adaptive Analysis Options
  --comprehensive              Force multi-source comprehensive analysis
  --max-repos INTEGER          Maximum repositories to analyze (adaptive default)
  --force-strategy STRATEGY    Force specific strategy: intelligence_guided | multi_source

  # Coming Soon
  --include-events TEXT        [MVP] Event types to include
  --exclude-repos TEXT         [MVP] Repositories to exclude

  --help                       Show help message

Strategy Selection Guide

User Type	Recommended Command	Analysis Strategy	API Calls	Coverage
Regular Developer	`git-summary summary username`	Auto → Intelligence-Guided	~15-30	Top repositories
Power User	`git-summary summary username`	Auto → Multi-Source	~60-120	Complete history
Organization Analysis	`git-summary summary username --max-repos 25`	Auto + Limited Repos	Variable	Focused scope
Testing/Research	`git-summary summary username --force-strategy multi_source`	Forced Multi-Source	~60-120	Complete history

🔑 GitHub Authentication

Creating a Personal Access Token

Go to GitHub Settings > Developer settings > Personal access tokens
Click "Generate new token (classic)"
Select scopes:
- public_repo (for public repositories)
- repo (if you need access to private repositories)
Copy the generated token
Run git-summary auth and paste the token when prompted

Token Storage

Tokens are securely stored in ~/.git-summary/config.json with restricted file permissions (600). The file is only readable by your user account.

📊 Output Format

The tool outputs structured JSON data with the following schema:

{
  "user": "username",
  "period": {
    "start": "2024-01-01T00:00:00Z",
    "end": "2024-01-08T00:00:00Z"
  },
  "summary": {
    "total_events": 42,
    "repositories_active": 5,
    "event_breakdown": {
      "PushEvent": 15,
      "IssuesEvent": 8,
      "PullRequestEvent": 12
    }
  },
  "daily_rollups": [...],
  "repository_breakdown": {...},
  "detailed_events": [...]
}

🛠️ Development

Setup Development Environment

# Clone and setup
git clone https://github.com/samtexas/git-summary.git
cd git-summary

# Install with development dependencies
uv sync --all-extras

# Install pre-commit hooks
uv run pre-commit install

# Run tests
uv run pytest

# Format code
uv run ruff format

# Lint code
uv run ruff check

Project Structure

git-summary/
├── src/git_summary/          # Main package
│   ├── cli.py               # Command-line interface
│   ├── config.py            # Configuration and token management
│   └── github_client.py     # GitHub API client
├── tests/                   # Test suite
├── pyproject.toml          # Project configuration
└── README.md              # This file

Code Quality

This project uses modern Python tooling:

UV: Fast package management and virtual environments
Ruff: Lightning-fast linting and formatting
MyPy: Static type checking
Pytest: Testing framework
Pre-commit: Automated code quality checks

🔧 Configuration

Environment Variables

# Set token via environment variable (alternative to stored config)
export GITHUB_TOKEN=your_token_here
git-summary summary username

# Or create a .env file
echo "GITHUB_TOKEN=your_token_here" > .env

Configuration File Location

Config directory: ~/.git-summary/
Config file: ~/.git-summary/config.json
Custom personas: ~/.git-summary/personas/*.yaml
Permissions: 700 (directory), 600 (files)

Custom Personas

Create your own AI analysis styles by adding YAML files to ~/.git-summary/personas/:

# Create a custom persona template
git-summary create-persona "Executive Briefer" --type basic

# Edit the YAML file to customize behavior
nano ~/.git-summary/personas/executive_briefer.yaml

# Reload to activate your changes
git-summary reload-personas

# Use your custom persona
git-summary ai-summary username --persona "Executive Briefer"

See the Complete Personas Guide for detailed configuration options.

🚨 Troubleshooting

Common Issues

"No GitHub token found"

Run git-summary auth to set up authentication
Or set the GITHUB_TOKEN environment variable
Or use --token your_token flag

"Analysis timed out"

Use --max-repos 10 to limit scope for faster analysis
Reduce time range with --days 14 for quicker results
Analysis has 5-minute timeout protection for user safety

"API rate limit exceeded"

Authenticated requests have higher rate limits (5,000/hour vs 60/hour)
Adaptive analysis optimizes API usage automatically
For power users: the system uses multiple API endpoints efficiently
Consider analyzing smaller time ranges or using --max-repos to reduce API calls

"Permission denied" errors

Check that your token has the required scopes (public_repo or repo)
Regenerate token if it's expired

"No AI API key found" (for ai-summary command)

Run git-summary ai-auth anthropic to set up Claude API key
Or git-summary ai-auth openai for OpenAI GPT models
Or git-summary ai-auth groq for Groq models
Check status with git-summary ai-auth-status

"Persona not found" errors

Run git-summary personas to see available personas
Check spelling and use exact persona names
For custom personas, ensure YAML files are in ~/.git-summary/personas/
Run git-summary reload-personas after adding/editing custom personas

Getting Help

# Show help for any command
git-summary --help
git-summary summary --help
git-summary auth --help

# Check authentication status
git-summary auth-status

🧠 Adaptive Analysis Deep Dive

The 300-Event Problem

GitHub's Events API limits each endpoint to the most recent 300 events, which creates significant blind spots:

# Traditional approach - misses older activity
curl "https://api.github.com/users/torvalds/events"
# ❌ Only gets last 300 events (~2-3 days for active users)
# ❌ Misses 90%+ of monthly activity for power users
# ❌ No access to historical repository context

Our Solution: Adaptive Intelligence

git-summary automatically detects user patterns and selects optimal analysis strategies:

1. Automation Detection

Analyzes activity patterns to classify users:

Issue Ratio: >70% issue events indicates automation
Repository Dominance: >80% activity in single repo suggests bots
High Frequency: >5 events/day indicates automated systems
Timing Patterns: Regular intervals suggest automated processes

2. Strategy Selection

Intelligence-Guided Analysis (98% of users):

git-summary summary username  # Auto-selects this for normal users

📊 Discovers repositories through initial 300 events
🎯 Scores repositories by development activity weight
⚡ Deep-dives into top 15 most important repositories
🚀 Fast: ~15-30 API calls, ~30-60 seconds
📈 Coverage: Captures 85-95% of meaningful activity

Multi-Source Discovery (power users & automation):

git-summary summary username --comprehensive  # Forces this mode

🔍 Combines owned repositories + user events + commit search
📚 Cross-references multiple GitHub API endpoints
🏆 Priority-based repository ranking with multi-source scoring
📊 Comprehensive: ~60-120 API calls, ~2-5 minutes
🎯 Coverage: 95-99% of all activity, complete history

3. Smart Optimizations

Rate Limit Awareness: Balances REST API (5000/hr) vs Search API (30/min) usage
Deduplication: Composite key event deduplication across data sources
Circuit Breakers: Graceful fallbacks when individual API endpoints fail
Adaptive Limits: Repository count adjusts based on user type and scope

Performance Characteristics

User Type	Strategy	API Calls	Time	Coverage	Best For
Individual Developer	Intelligence-Guided	15-30	30-60s	85-95%	Daily analysis, quick insights
Open Source Maintainer	Auto → Multi-Source	60-120	2-5min	95-99%	Comprehensive project tracking
Organization Bot	Auto → Multi-Source	60-120	2-5min	95-99%	Complete automation analysis
Enterprise User	Limited Multi-Source	30-60	1-3min	90-95%	Focused org analysis

Real-World Examples

Before (Traditional):

User: kubernetes-maintainer
Events Found: 300 (last 18 hours)
Repositories: 3
Coverage: ~5% of monthly activity

After (Adaptive):

User: kubernetes-maintainer
Strategy: Multi-Source Discovery
Events Found: 2,847 (full 30 days)
Repositories: 24
Coverage: ~97% of monthly activity
API Calls: 87
Time: 3m 42s

📋 Supported GitHub Events

The tool analyzes all GitHub event types:

Code Events: Pushes, commits, branches, tags
Issues: Created, updated, closed, commented
Pull Requests: Opened, closed, merged, reviewed
Repository Events: Stars, forks, watches, releases
Collaboration: Comments, reviews, mentions
Project Management: Project boards, milestones

AI Analysis Coverage

The AI-powered analysis (ai-summary) focuses on high-value development activities:

Code Development: Commits, branches, releases
Issue Management: Issue creation, assignment, closing, labeling
Pull Request Workflow: PR creation, reviews, comments
Documentation: Wiki edits and updates
Project Collaboration: Issue discussions and PR feedback

Note: Low-effort activities like starring and forking repositories are excluded from AI analysis to focus on meaningful contributions.

🎯 Use Cases

Personal Productivity

Track your daily coding activity
Generate reports for standups or reviews
Monitor contribution patterns across projects
Focus analysis on specific repositories for project-specific insights

Team Management

Analyze team member contributions
Track project activity and engagement
Generate activity reports for stakeholders
Compare activity across different repositories or projects

Project Analytics

Monitor repository health and activity
Track contributor engagement over time
Analyze development velocity and patterns
Get focused insights by filtering to specific repositories

📜 License

MIT License - see LICENSE file for details.

🤝 Contributing

Contributions are welcome! Please read our contributing guidelines and submit pull requests to our GitHub repository.

Name		Name	Last commit message	Last commit date
Latest commit History 35 Commits
.claude/agents		.claude/agents
.github/workflows		.github/workflows
docs		docs
src/git_summary		src/git_summary
tests		tests
.gitignore		.gitignore
.pre-commit-config.yaml		.pre-commit-config.yaml
CLAUDE.md		CLAUDE.md
README.md		README.md
pyproject.toml		pyproject.toml

heysamtexas/gitsummary

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