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using-beads

Manage persistent task and issue tracking via the bd command-line interface.

Updated Nov 23, 2022
Search Tags:#task management#dependencies#cli#ai agent#issue tracking#persistence
One-click install
npx skills add https://github.com/tjmgregory/.dotfiles --skill using-beads
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: using-beads
Source: https://github.com/tjmgregory/.dotfiles/tree/main/agents/skills/using-beads
Command: npx skills add https://github.com/tjmgregory/.dotfiles --skill using-beads

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill provides persistent task memory for AI agents, allowing for multi-session work with dependencies and context recovery even after conversation compaction.

Core Features & Use Cases

  • Persistent Issue Tracking: Create, update, and manage issues that survive conversation history loss.
  • Dependency Management: Define and track blockers and relationships between tasks.
  • Context Recovery: Easily resume work after AI context compaction by referencing past comments and issue status.
  • Use Case: When working on a complex feature that spans multiple days or requires input from different AI sessions, using-beads ensures that progress, blockers, and decisions are recorded and accessible.

Quick Start

Use the bd CLI to create a new bug issue with the title "Fix login redirect loop".

Frequently Asked Questions about using-beads

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

FAQPage Schema
How do I maintain task tracking across multiple AI sessions after context loss?▼

Persistent task tracking across AI sessions is managed using the 'bd' CLI, which records issues, blockers, and comments to survive conversation history compaction. This allows you to resume complex workflows seamlessly.

How does dependency management work for complex AI agent workflows?▼

Dependency management for AI agent workflows works by defining and tracking blockers and relationships between tasks using the 'bd' CLI. This graph-based issue tracking ensures multi-session work respects task execution order.

What is the best way to recover context for an AI agent after conversation compaction?▼

The best way to recover AI agent context after compaction is by referencing past comments and issue status stored via the 'bd' CLI. This graph-based persistence restores progress and decisions without manual reconstruction.

Can I use the bd CLI to manage long-running features spanning multiple days?▼

Yes, you can use the 'bd' CLI to manage long-running features spanning multiple days. It handles issue creation, updates, status transitions, and dependency linking to ensure progress and decisions are accessible across sessions.

Does the bd CLI require external dependencies to track issues?▼

No external dependencies are required to track issues with the 'bd' CLI. The Skill operates independently using scripts and references to provide graph-based persistence for complex AI agent workflows.

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