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Swarm Orchestration

Orchestrate multi-agent swarms with mesh, hierarchical, or adaptive topologies.

4.4k|580|Updated Nov 19, 2025
Search Tags:#multi-agent#orchestration#swarm#distributed-systems#agentic-flow#task-orchestration
One-click install
npx skills add https://github.com/ruvnet/ruvector --skill swarm-orchestration-ruvnet
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: Swarm Orchestration
Source: https://github.com/ruvnet/ruvector/tree/main/.claude/skills/swarm-orchestration
Command: npx skills add https://github.com/ruvnet/ruvector --skill swarm-orchestration-ruvnet

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Orchestrates multi-agent swarms to enable scalable, coordinated task execution across many agents, removing the bottleneck of single-threaded execution and enabling complex AI workflows.

Core Features & Use Cases

  • Topology patterns: mesh, hierarchical, and adaptive topologies with automatic task distribution.
  • Advanced coordination and memory sharing: cross-agent communication, shared state, and hooks integration.
  • Fault-tolerant orchestration and dynamic load balancing for resilient workflows.
  • Use Case: Orchestrate a team of specialist agents to implement a complex software feature with parallel tasks and dependency management.

Quick Start

Initialize a swarm with mesh topology and up to 5 agents: npx agentic-flow hooks swarm-init --topology mesh --max-agents 5

Spawn agents for roles: npx agentic-flow hooks agent-spawn --type coder npx agentic-flow hooks agent-spawn --type tester npx agentic-flow hooks agent-spawn --type reviewer

Orchestrate tasks in parallel: npx agentic-flow hooks task-orchestrate --task "Build REST API with tests" --mode parallel

Frequently Asked Questions about Swarm Orchestration

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

FAQPage Schema
How do I coordinate multiple AI agents to execute parallel tasks in a distributed workflow?▼

Multi-agent orchestration coordinates distributed AI workflows using mesh, hierarchical, or adaptive topologies with automatic task distribution. It enables cross-agent communication and shared state management to execute parallel tasks across specialized agents.

How do I scale complex AI workflows without hitting single-threaded execution bottlenecks?▼

Scaling complex AI workflows requires a swarm orchestration framework that provides dynamic load balancing and fault tolerance. This approach removes single-threaded execution bottlenecks by distributing work across multiple specialized agents in parallel.

Do I need Node.js and agentic-flow to set up multi-agent task orchestration?▼

Yes, setting up this multi-agent task orchestration requires Node.js 18+ and agentic-flow v1.5.11 or higher. These dependencies provide the foundational hooks needed to initialize swarms and spawn specialized agents like coders and testers.

Can I use mesh topology to distribute tasks across a team of specialist agents for software development?▼

Yes, you can initialize a swarm with mesh topology to distribute tasks across specialist agents for software development. This supports dynamic load balancing and fault-tolerant orchestration for complex, parallel feature implementation.

What is the best way to handle fault tolerance and memory coordination in distributed AI systems?▼

The best way to handle fault tolerance and memory coordination in distributed AI systems is using a dedicated swarm orchestration framework. It provides cross-agent communication, shared state management, and resilient workflow execution across mesh or hierarchical network topologies.

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