multi-agent-patterns

Design multi-agent systems with Supervisor, Peer-to-Peer, and Hierarchical patterns.

Updated Apr 28, 2026
One-click install
npx skills add https://github.com/lucasFR2/LogiSync --skill multi-agent-patterns-lucasfr2
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: multi-agent-patterns
Source: https://github.com/lucasFR2/LogiSync/tree/main/skills/multi-agent-patterns
Command: npx skills add https://github.com/lucasFR2/LogiSync --skill multi-agent-patterns-lucasfr2

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill addresses the challenges of designing, implementing, and coordinating complex multi-agent systems, streamlining the process and enabling efficient system creation.

Core Features & Use Cases

  • Multi-Agent Design: Offers guidelines for designing multi-agent systems with patterns like Supervisor, Peer-to-Peer/Swarm, and Hierarchical.
  • Context Isolation: Provides principles and mechanisms for achieving context isolation in agents.
  • Coordination Protocols: Includes strategies for consensus, voting, and debate protocols.
  • Use Case: For a project that requires parallel processing of tasks across multiple agents, this Skill can help design an effective multi-agent architecture.

Quick Start

Use the multi-agent-patterns skill to design a multi-agent system using the Supervisor pattern.

Frequently Asked Questions about multi-agent-patterns

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

FAQPage Schema
How do I design a multi-agent system architecture for parallel processing?

To design a multi-agent system for parallel processing, you can implement established patterns like Supervisor, Peer-to-Peer/Swarm, or Hierarchical to structure agent communication and task delegation effectively.

What is context isolation in multi-agent coordination?

Context isolation in multi-agent coordination is a mechanism that separates the operational state and knowledge boundaries of individual agents to prevent interference and maintain system stability.

How do consensus protocols work in multi-agent systems?

Consensus protocols in multi-agent systems work by implementing voting and debate strategies that allow distributed agents to reach a unified agreement on decisions despite decentralized communication.

When should I use a Supervisor pattern versus a Peer-to-Peer swarm in multi-agent design?

Use the Supervisor pattern in multi-agent design for centralized task routing, whereas Peer-to-Peer or Swarm patterns suit scenarios requiring decentralized consensus and autonomous agent coordination.

Do I need prior knowledge of multi-agent system theory to use these coordination patterns?

Yes, understanding multi-agent system theory and coordination mechanisms is required, as this skill focuses on advanced architectural designs and communication strategies for complex production environments.