beads-issue-tracker

Track dependency-aware issues with ready states and Git-like sync.

4|1|Updated Dec 9, 2025
One-click install
npx skills add https://github.com/stakpak/community-paks --skill beads-issue-tracker
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: beads-issue-tracker
Source: https://github.com/stakpak/community-paks/tree/main/beads-issue-tracker
Command: npx skills add https://github.com/stakpak/community-paks --skill beads-issue-tracker

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Beads addresses the challenge of coordinating AI-driven work where tasks have dependencies. It helps prevent duplicated efforts and ensures work proceeds only when prerequisites are complete.

Core Features & Use Cases

  • Dependency-aware issue tracking for AI agents (bd)
  • Supports blocking, related, parent-child, and discovered-from dependencies
  • Ready Work concept: tasks that are open and unblocked are ready to claim
  • Git-like sync and export/import to keep databases in sync across machines

Quick Start

Initialize beads in your project and begin creating and linking issues with dependencies to drive automated workflows.

Frequently Asked Questions about beads-issue-tracker

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

FAQPage Schema
How does dependency-aware issue tracking for AI agents work?

Dependency-aware issue tracking links tasks by blocking, related, or parent-child dependencies. It ensures AI agents only claim work when prerequisite tasks are complete, preventing duplicated efforts and unblocked states. It manages statuses and ready-to-work states for automated workflows.

How do I link tasks by dependencies to calculate ready-to-work states?

You link tasks by dependencies using a command interface to create, update, and manage relationships like blocking or parent-child. The system then automatically calculates ready-to-work states, identifying open and unblocked tasks that agents can immediately claim.

Can I sync issue tracking databases across different machines?

Yes, you can sync issue tracking databases across machines using Git-like export and import semantics. This functionality keeps your task management data synchronized across different environments and local setups for AI-driven workflows.

What is the best way to prevent duplicated efforts in AI-driven project management?

The best way to prevent duplicated efforts is using dependency-aware issue tracking. By linking tasks with blocking or parent-child relationships, AI agents can verify prerequisites are complete before starting, ensuring work proceeds only when truly ready.

Do I need a command interface to manage AI task tracking?

Yes, a command interface is required to create, list, and update issues. This interface handles dependency management, ready-state handling, and Git-like sync operations, serving as the primary control mechanism for AI-assisted project management.