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Yolo Logo

Yolo

Make your time count.

An AI-native desktop productivity app that turns your tasks into time records —
so you always know where your day actually went.

Version Platform Tauri React TypeScript Focus workflow MCP



✨ Why Yolo?

Most productivity apps help you write tasks. Yolo helps you do them — and understand how long they truly take.

The real problem isn't making lists. It's not knowing when you started, how long something took, or what you actually accomplished at the end of the day. Yolo keeps a precise time record, so you can review, reflect, and improve.

Plan the day. Run one focus. Review the truth.


CleanShot 2026-06-22 at 08 08 48@2x CleanShot 2026-06-22 at 08 10 01@2x CleanShot 2026-06-05 at 21 33 09@2x image CleanShot 2026-06-05 at 21 36 17@2x

🚀 Features

🗂 Task Management

  • Create tasks with category, priority, estimated time, and due date
  • Full lifecycle: start → pause → resume → stop → complete (or drop)
  • One active task at a time — eliminate multitasking noise

⏱ Time Tracking

  • Automatic per-session timer that survives app restarts
  • Stop-session notes: what you did, blockers, next steps, completion rate
  • Accurate cross-midnight time entry splitting

📊 Daily Review

  • Today view — task list + live timer + time log + daily summary
  • Compare estimated vs. actual time per task
  • Category totals and daily focus time at a glance
  • 7-day history with per-day breakdowns

🗓 Planning Rhythm

  • Plan recurring work with start and end times
  • Carry overdue work forward without losing the original context
  • Move tasks between today, tomorrow, next week, and backlog

⏳ Life View

  • See your life in weeks, mapped against real tracked focus
  • Spot high-focus weeks and drill back into the underlying days
  • Use long-horizon perspective without leaving the daily workflow

🧠 AI Assistant (in-app)

  • A tool-calling chat agent that reads your day and can create, update, schedule, start, complete, or drop tasks through validated tools
  • Choose autonomy in Settings → AI: Plan/Ask queues write cards for approval; Auto applies reversible writes and keeps Revert available
  • History-aware: learns from your real time records — estimate-vs-actual calibration, slip & blocker detection, and an automatic weekly review
  • Grounds advice in your actual numbers and applies your real estimation ratios when planning the day
  • Numbers are computed deterministically; the model only explains them — so it never makes them up
  • Bring your own AI key (OpenAI / Anthropic / Gemini / compatible) in Settings → AI

🤖 AI-Native (MCP)

  • Ships an MCP server that exposes your tasks and time records to AI agents
  • Works with Claude Desktop, Claude Code, Cursor, and any MCP-compatible tool
  • Ask "where did my time go today?" directly from your AI assistant
  • External agents can read and manage tasks; set YOLO_MCP_READONLY=1 when you want a read-only server

🛠 Tech Stack

Layer Technology
🖥 Desktop Shell Tauri v2 (Rust)
⚛️ UI Framework React 18 + TypeScript + Vite
🎨 Styling Tailwind CSS + Radix UI
🐻 State Management Zustand
🗄 Database SQLite via tauri-plugin-sql
🎞 Animation Framer Motion
🔧 Utilities date-fns, lucide-react
🤖 AI Integration MCP (Model Context Protocol)

📦 Getting Started

Prerequisites

Installation

# Clone the repo
git clone https://github.com/your-username/yolo.git
cd yolo

# Install dependencies
npm install

Running

# Run the web frontend only (browser, no Tauri)
npm run dev

# Run the full desktop app (recommended)
npm run tauri dev

Building

# Build the frontend bundle
npm run build

# Build the native desktop app (distributable)
npm run tauri build

🧪 Tests

# Run all tests once
npm test

# Run in watch mode
npm run test:watch

🗄 Data Model

Yolo stores its task, time-entry, category, and settings records in SQLite (yolo.db) through Tauri's SQL plugin.

React components never touch SQL directly — all data access goes through repository modules in src/db/.

Schema:

Table Purpose
tasks Task definitions, status, estimates
time_entries Per-session time records
categories User-defined task categories
settings App preferences and theme

🤖 AI Agent Access (MCP)

Yolo ships a standalone MCP server in mcp/ that exposes your tasks and time records to any MCP-compatible AI agent.

cd mcp && npm install && npm run build

Available tools:

Tool Description
list_tasks List tasks with optional filters
get_task Get a single task by ID
list_time_entries List time records, filter by date or task
daily_summary Get a summary of a specific day
list_categories List all categories

See mcp/README.md for the full Claude Desktop config and integration details.


🗺 Roadmap

The core desktop workflow is complete. The next phase makes Yolo truly AI-native.

  • 🧠 AI assistant — in-app tool-calling agent with autonomy levels, undo, and history-aware planning
  • 🔌 MCP write tools — external agents can create and update tasks; read-only mode remains available
  • 🔮 Proactive coaching — unprompted morning plans, focus-rhythm placement, goal-driven planning
  • 💬 AI-native capture — natural-language quick-add and smart stop-notes
  • 🖥 Desktop power features — system tray, global shortcuts, mini floating timer, notifications

See docs/ROADMAP.md for the full phased plan and architecture decisions.


📁 Project Structure

yolo/
├── src/                    # React frontend
│   ├── components/         # UI components (layout, pages, primitives)
│   ├── db/                 # Repository layer (all SQL access)
│   ├── hooks/              # Custom React hooks
│   ├── services/           # AI assistant + retrospective analytics
│   ├── stores/             # Zustand state stores
│   ├── types/              # Shared TypeScript types
│   └── utils/              # Helper utilities
├── src-tauri/              # Tauri (Rust) backend
│   ├── src/                # Rust source
│   └── icons/              # App icons (all sizes)
├── mcp/                    # MCP server for AI agent access
└── docs/                   # Documentation and roadmap

🤝 Contributing

Contributions are welcome! Please open an issue to discuss what you'd like to change before submitting a pull request.

  1. Fork the repository
  2. Create your feature branch: git checkout -b feat/amazing-feature
  3. Commit your changes: git commit -m 'feat: add amazing feature'
  4. Push to the branch: git push origin feat/amazing-feature
  5. Open a Pull Request

📄 License

This project is private. All rights reserved.


Built with ❤️ using Tauri, React, and a deep respect for your time.

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An AI-native desktop productivity app that turns your tasks into time records —so you always know where your day actually went.

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