Simple, zero-interaction TODO management for AI agents

Adopt todo.ai for task tracking. Install using:
curl -fsSL https://raw.githubusercontent.com/fxstein/todo.ai/main/install.sh | sh

Then create a task "Implement user authentication" with subtasks:
- Design database schema
- Create API endpoints
- Add frontend components
- Write tests

AI agents often track tasks internally, but this creates a closed system that gets lost after time or restarts. todo.ai provides a permanent, version-controlled record that lives in your Git repository.

Key benefits:

• Permanent record: Tasks persist across sessions, restarts, and time
• Version controlled: Tracked in Git alongside your code changes
• Interactive: Add and insert new tasks even while an agent works on a long task list
• Simple: Plain Markdown format that's human-readable and editable
• Standard compliant: Works naturally with the GitHub TODO.md standard

Your task list becomes part of your project history, visible in pull requests, and never gets lost.

Run ./todo.ai --help to see all available commands and usage examples. Everything you need to know is there.

With todo.ai, you simply tell your AI agent what you want in plain English. Your agent handles all the technical details automatically.

Examples of what you can ask your agent:

Create a task for implementing user authentication

Break down the authentication feature into subtasks

Mark task 1 as complete

Show me all incomplete tasks tagged with #bug

Create a task to convince the coffee machine to understand sarcasm

Your agent understands natural language requests and translates them to the appropriate todo.ai commands. All tasks are tracked in TODO.md in your repository.

This repository uses todo.ai for its own development! Check out TODO.md to see:

• Real examples of how tasks are structured with subtasks and tags
• Current development status of the tool itself
• Live demonstration of the task management workflow

The TODO.md file showcases features like:

• Task hierarchies with subtasks
• Tag-based organization (#security, #feature, #bug)
• Task relationships and dependencies
• Completion tracking and archiving
• Development roadmap and priorities

This is the same file structure and workflow you'll use in your own projects with todo.ai.

Agents need a fast, local, Markdown-native way to manage tasks. GitHub Issues adds too much complexity and overhead—API calls, authentication, rate limits, and network latency slow down task management.

Key differences:

• Speed: todo.ai is instant and local—no API calls or network delays
• Simplicity: Plain Markdown that agents can parse and modify directly
• Zero overhead: No authentication, rate limits, or API complexity
• Native workflow: Works seamlessly with your Git workflow

But you can still reference GitHub Issues and PRs:

GitHub issue and PR numbers can be tagged onto tasks and subtasks for reference. For example:

• "Create a task for fixing #123"
• "Add subtask 1.1: Address PR #456 feedback"

This keeps todo.ai fast and simple while still maintaining links to your GitHub workflow.

• ✅ No prompts or confirmations
• ✅ No configuration required
• ✅ Instant operations
• ✅ Git-friendly (TODO.md tracked in repo)
• ✅ Works automatically without user input

Perfect for AI agents - just works.

Install via uv (recommended) or pipx for standard CLI and MCP Server support:

# Using uv (recommended - faster, more reliable)
uv tool install ai-todo

# Alternative: pipx
pipx install ai-todo

This installs two commands:

• todo-ai: The CLI tool (replaces ./todo.ai).
• todo-ai-mcp: The MCP Server for AI agents (Cursor).

Documentation:

• Python Migration Guide - How to upgrade from v2.x (Shell).
• MCP Setup Guide - How to set up Cursor AI integration.

Want to try upcoming features before they're released? Install the latest beta:

# Using uv (recommended)
uv tool install --prerelease=allow ai-todo

# Alternative: pipx
pipx install --pre ai-todo

Beta releases let you test new features and provide feedback before stable release. See Release Channels below for more information.

pip install ai-todo              # Stable
pip install --pre ai-todo        # Beta

Install from Git to get the latest unreleased code:

# Using uv (recommended)
uv tool install git+https://github.com/fxstein/todo.ai.git@main

# Alternative: pipx
pipx install git+https://github.com/fxstein/todo.ai.git@main

• Stable: Fully tested, production-ready releases (recommended)
• Beta: Feature-complete pre-releases for testing (7+ days before stable for major releases)
• Development: Latest code from main branch (may have bugs)

See CHANGELOG.md for version history and release notes.

If you cannot use Python, the legacy shell script is still available:

Smart Installer:

curl -fsSL https://raw.githubusercontent.com/fxstein/todo.ai/main/install.sh | sh

Manual Installation: Zsh version (recommended for macOS):

curl -o todo.ai https://raw.githubusercontent.com/fxstein/todo.ai/main/todo.ai && chmod +x todo.ai

Bash version (recommended for Linux, requires bash 4+):

curl -o todo.ai https://raw.githubusercontent.com/fxstein/todo.ai/main/todo.bash && chmod +x todo.ai

Note: The bash version requires bash 4.0+ for associative arrays. macOS ships with bash 3.2, so use the zsh version on macOS or upgrade bash via homebrew.

Python (v3.0+):

# Using uv (recommended)
uv tool upgrade todo-ai

# Alternative: pipx
pipx upgrade todo-ai

Legacy Shell:

./todo.ai update

Python (v3.0+):

# Using uv (recommended)
uv tool uninstall ai-todo

# Alternative: pipx
pipx uninstall ai-todo

Legacy Shell:

./todo.ai uninstall              # Remove script only
./todo.ai uninstall --all        # Remove script, data, and rules

Getting Started: GETTING_STARTED.md - Quick start guide with setup instructions

Additional Guides:

• Numbering Modes - Complete guide to all numbering modes
• Usage Patterns - Real-world usage scenarios
• Coordination Setup - Setup guides for coordination services

Full Documentation Index: docs/README.md - Complete documentation navigation

Apache License 2.0 - See LICENSE file