checkpoint-agent 1.1.1

AI-powered developer onboarding and context recovery system for git repositories

Code Checkpoint

Code Checkpoint is an AI-powered developer onboarding and context recovery tool for git repositories. It automatically generates living documentation that evolves with every commit, so returning developers can get up to speed instantly and new developers can understand the codebase without reading every file.

What it does

• Master Context (MASTER_CONTEXT.md) — A full architectural overview of the codebase, regenerated on every PR merge. Perfect for new developers.
• Personalized Catchup (checkpoints/Checkpoint_<email>.md) — A "While You Were Gone" briefing per developer, updated on every push. Shows exactly what changed since their last commit.
• Commit Checkpoints — Per-commit summaries stored in checkpoints/, used as the source material for catchups.
• PR Summaries — A consolidated summary for each pull request.

All generation runs via GitHub Actions — no local hooks required.

Installation

pip install checkpoint-agent

Quick Start

# Navigate to your git repository
cd /path/to/your/repo

# Install the GitHub Actions workflow + create default config
checkpoint --init

Then add your LLM API key as a GitHub Secret (e.g. MISTRAL_API_KEY) and push — checkpoints will be generated automatically.

Commands

# Setup
checkpoint --init                        # Install GitHub Actions workflow + create config
checkpoint --config                      # Show current configuration

# Generation (also runs automatically via GitHub Actions)
checkpoint --onboard                     # Generate MASTER_CONTEXT.md
checkpoint --catchup                     # Generate your personal catchup
checkpoint --catchup [e-mail]      # Generate catchup for a specific user
checkpoint --catchup-all                 # Generate catchups for all active developers

# Commit analysis
checkpoint --commit <hash>               # Analyze a specific commit
checkpoint --commit <hash> --dry-run     # Preview without saving

# Info
checkpoint --stats                       # Show checkpoint statistics

GitHub Actions (recommended)

Run checkpoint --init to install the workflow and create the default config, then add your LLM API key as a GitHub secret (e.g. MISTRAL_API_KEY).

The workflow runs three jobs automatically:

Trigger	Job	Output
Push to any branch	Generate commit checkpoints + catchups for all developers	checkpoints/Checkpoint-*.md, checkpoints/Checkpoint_*.md
PR opened/updated	Generate per-commit checkpoints + PR summary	checkpoints/PR-*.md
PR merged to main	Regenerate master context	MASTER_CONTEXT.md

Configuration

.checkpoint.yaml:

llm:
  provider: mistral          # openai, anthropic, mistral, ollama, google, azure
  model: mistral-medium-2508
  temperature: 0.7
  max_tokens: 2000

repository:
  output_dir: ./checkpoints
  master_context_file: MASTER_CONTEXT.md

features:
  git_hook: false            # Local hook (GitHub Actions is preferred)
  diagrams: true             # Generate Mermaid diagrams in master context
  auto_catchup: false

languages:
  - Python

API keys go in .env:

MISTRAL_API_KEY=...
# OPENAI_API_KEY=...
# ANTHROPIC_API_KEY=...

Supported LLM Providers

Any provider supported by LiteLLM: OpenAI, Anthropic, Mistral, Google Gemini, Azure, Ollama (local), and more. Set provider and model in .checkpoint.yaml.

Project Structure

checkpoint_agent/
├── __main__.py          # CLI entry point
├── agents.py            # LLM prompts (CheckpointGenerator, CatchupGenerator, etc.)
├── graph.py             # Commit analysis pipeline
├── llm.py               # LiteLLM configuration
├── config.py            # Pydantic config models
├── storage.py           # Checkpoint file I/O
├── git_utils.py         # GitPython wrappers
├── mermaid_utils.py     # AST-based diagram generation (Python)
├── llm_diagrams.py      # LLM-based diagram generation (other languages)
├── setup_wizard.py      # Config display utilities
├── git_hook_installer.py
└── templates/
    └── checkpoint.yml   # Bundled GitHub Actions workflow

Development

git clone https://github.com/BurntDosa/Checkpoint
cd Checkpoint
pip install -e ".[dev]"
pytest tests/

License

MIT