beads

Manage persistent task memory across AI agent sessions.

15|4|Updated Jan 20, 2026

Search Tags:#task management #development workflow #ai agent #memory #persistence #context survival

Ready to run

npx skills add https://github.com/cofin/flow --skill beads-cofin

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: beads
Source: https://github.com/cofin/flow/tree/main/skills/beads
Command: npx skills add https://github.com/cofin/flow --skill beads-cofin

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill provides persistent task memory that survives AI context window limitations and session resets, ensuring continuity and deep project awareness across development cycles.

Core Features & Use Cases

Cross-Session Memory: Stores task details, notes, and learnings that are not lost when the AI's context window is cleared.
Dependency Tracking: Manages task dependencies, allowing for intelligent prioritization and workflow management.
Use Case: As an AI agent working on a complex software feature over multiple days, Beads ensures that all the nuances, decisions, and intermediate findings from previous sessions are available, preventing repetitive questions and maintaining project momentum.

Quick Start

Initialize Beads for your project by running the command br init.

Frequently Asked Questions about beads

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

FAQPage Schema

How do I maintain AI agent context and memory across session resets?▼

To maintain AI agent context across session resets, you need persistent task memory that stores task details, notes, and learnings independently from the AI's context window. This ensures project continuity and prevents repetitive questions in subsequent development cycles.

What happens to task management state when AI context compaction occurs?▼

During AI context compaction, standard task state is typically lost. Persistent task memory prevents this by saving task updates, status tracking, and notes externally, ensuring your development workflow and intermediate findings survive the context window limitations.

How do I track task dependencies for a complex software feature using AI?▼

Tracking task dependencies for complex software features requires a persistent memory system that manages task creation and dependency links. This allows intelligent prioritization and maintains workflow state across multiple days of AI agent interactions.

Can I initialize persistent task memory for an existing development workflow?▼

Yes, you can initialize persistent task memory for an existing development workflow by running the initialization command in your project directory. This sets up the necessary references to start tracking tasks, dependencies, and notes for your AI agent.

Why does my AI agent keep asking repetitive questions about previous development sessions?▼

AI agents ask repetitive questions when previous session context is lost due to context window clearing. Implementing persistent task memory makes all prior nuances, decisions, and intermediate findings available, preventing this loop and maintaining project momentum.

What is the best way to ensure deep project awareness for AI agents over multiple days?▼

The best way to ensure deep project awareness for AI agents over multiple days is using a persistent memory system that handles dependency management and notes. This maintains state across agent interactions, preserving all task details and learnings despite context limitations.