Taskdog is a terminal-based task management system offering CLI, TUI, and REST API interfaces. It addresses individual task management by providing intelligent schedule optimization, time tracking, and a visual Gantt chart, all stored locally in an SQLite database. Designed for keyboard-only operation, it aims to reduce micromanagement for power users and developers.

How It Works

The project utilizes a monorepo architecture comprising five packages: taskdog-core (business logic, SQLite), taskdog-client (API), taskdog-server (FastAPI), taskdog-ui (CLI/TUI), and taskdog-mcp (Claude Desktop integration). Schedule optimization is powered by nine algorithms, including greedy, genetic, and Monte Carlo methods. Key features include automatic time tracking with planned vs. actual comparison, circular dependency detection for tasks, Markdown note support with Rich rendering, and audit logging.

Quick Start & Requirements

• Demo: Run docker run --rm -it ghcr.io/kohei-wada/taskdog:demo for a no-install experience. For better TUI keybinding handling, run the server in Docker (docker run --rm -d -p 8000:8000 --name taskdog-demo ghcr.io/kohei-wada/taskdog:demo) and connect via uvx --from taskdog-ui taskdog tui.
• Installation:
  • make install (Linux/macOS): Installs CLI/TUI/server and sets up systemd/launchd services.
  • pip install taskdog-ui[server]: Requires manual server process management.
• Prerequisites: Python 3.12+, uv.
• Links: Quick Start Guide, CLI Commands Reference, API Reference, Configuration Guide, Design Philosophy, Deployment Guide, CONTRIBUTING.md.

Highlighted Details

• Schedule Optimization: Employs 9 algorithms (greedy, genetic, Monte Carlo, etc.).
• Interfaces: Supports CLI, full-screen TUI, and REST API.
• Time Tracking: Automatic with planned vs. actual comparison.
• Gantt Chart: Visual timeline with workload analysis.
• Task Dependencies: Includes circular dependency detection.
• Notes: Markdown support with Rich rendering.
• MCP Integration: Supports Claude Desktop via Model Context Protocol.

Maintenance & Community

Contributions are welcomed, with guidelines provided in CONTRIBUTING.md. No specific community channels (e.g., Discord, Slack) or sponsorship details were found in the provided README text.

Licensing & Compatibility

Licensed under the MIT License. This typically permits commercial use and integration with closed-source projects without significant restrictions.

Limitations & Caveats

The Docker demo may exhibit keybinding conflicts (e.g., Ctrl+P) with the Docker environment. The pip installation method necessitates manual management of the server process.