beads

Organize AI agent tasks and dependencies in a Git-backed issue graph.

21|1|Updated Jan 8, 2026
One-click install
npx skills add https://github.com/metalagman/agent-skills --skill beads-metalagman
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: beads
Source: https://github.com/metalagman/agent-skills/tree/main/beads
Command: npx skills add https://github.com/metalagman/agent-skills --skill beads-metalagman

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Beads helps AI agents manage tasks and dependencies in a Git-backed issue graph, providing structured workflows and reliable synchronization.

Core Features & Use Cases

  • Expert guidance on Beads CLI commands (init, status, sync) and dependency management.
  • Workflow support for formulas, molecules, gates; integration with agent hooks.
  • Real-world scenarios include initializing a project, syncing state, and handling issues with dependencies.

Quick Start

Initialize a Beads project with bd init and then start syncing state with bd sync.

Frequently Asked Questions about beads

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I track AI agent tasks and dependencies using a Git-backed issue graph?

AI agent task tracking utilizes a Git-backed issue graph to organize dependencies and synchronize state. You initialize the project via CLI, manage issue lifecycles, and use deterministic commands to export JSON context for reliable agent automation.

How do I initialize a project and sync state for AI task tracking?

To initialize a project, run the bd init command to set up the Git-backed issue graph. After initialization, use bd sync to synchronize state, ensuring your AI agent tasks and dependencies are reliably tracked and updated across workflows.

What is a Git-backed issue graph and how does it manage task dependencies?

A Git-backed issue graph structures AI agent tasks and dependencies directly within the repository. It enables reliable planning and progress tracking by mapping issue lifecycles and relationships, allowing deterministic commands to sync state and export JSON context.

Can I integrate AI agent hooks with issue lifecycles and dependency management?

Yes, AI agent hooks integrate directly with issue lifecycles and dependency management. The system provides integration hooks that allow agents to interact with workflows, formulas, molecules, and gates, enabling safe automation and reliable task synchronization.

What are the limitations or recovery options when syncing dependencies in an issue graph?

When syncing dependencies in an issue graph fails, the system provides guidance for recovery, debugging, and safe automation. It uses deterministic commands to ensure reliable synchronization, helping you resolve issues and restore consistent state across your AI agent tasks.