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Swarm Orchestration — Claude Code skill: multi-agent coordination

Skill for managing agent swarms with parallel execution, dynamic topology, and automatic load balancing. Use when a single agent is not enough and you need to orchestrate specialists of different types.

Install into Claude Code · Skills CLI (Vercel) All methods and platforms ↓
npx skills add ruvnet/ruflo --skill swarm-orchestration -a claude-code
Open on GitHub

What Swarm Orchestration does

Swarm Orchestration uses agentic-flow to coordinate multiple agents on complex tasks. Three topology modes are available: mesh (equal peers), hierarchical (central coordinator with workers), and adaptive (automatically switches based on task complexity). Tasks run in parallel or as a pipeline—architect designs, coder implements, tester writes tests, reviewer checks.

Agents share state through a common memory layer, exchanging schemas, context, and results. Built-in load balancing monitors each agent's capacity and redistributes work. If an agent fails, the system reassigns its task automatically. Requires agentic-flow v1.5.11+ and Node.js 18+.

Setup is done via npx agentic-flow hooks commands: choose topology, spawn agents by type, run orchestrate. Metrics track throughput, latency, success rate, and resource use. Pre-task and post-task hooks enable automatic coordination and session recovery.

What it helps with

  • Run independent stages in parallel (frontend, backend, tests at the same time)
  • Distribute a complex task across specialized agents
  • Recover a swarm after one agent fails without losing progress
  • Balance load between agents with different capabilities
  • Merge results from multiple agents into a single system

Example prompts for the agent

  • Start a swarm with three agents and build API, frontend, and tests in parallel
  • Initialize hierarchical topology with architect as the central coordinator
  • Run autoOrchestrate with goal 'Build production-ready API' and 3600-second limit

How to install Swarm Orchestration

1Skills CLI (Vercel)

npx skills add ruvnet/ruflo --skill swarm-orchestration -a claude-code

2Manually: put the files in place

~/.claude/skills/swarm-orchestration/SKILL.md

Copy the whole skill folder; for one project use .claude/skills/swarm-orchestration/

From the same set104

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Questions about Swarm Orchestration

How do I install Swarm Orchestration in Claude Code?

Run npx skills add ruvnet/ruflo --skill swarm-orchestration -a claude-code, then check the installation at ~/.claude/skills/swarm-orchestration/SKILL.md.

What does Swarm Orchestration do?

It manages agent swarms: distributes tasks in parallel or as a pipeline, balances load, recovers from agent failures, and synchronizes shared state through memory.

What topologies are supported?

Mesh (agents communicate directly), hierarchical (central coordinator with workers), and adaptive (the system chooses topology based on task complexity).

Source text

SKILL.md · MIT
---
name: "Swarm Orchestration"
description: "Orchestrate multi-agent swarms with agentic-flow for parallel task execution, dynamic topology, and intelligent coordination. Use when scaling beyond single agents, implementing complex workflows, or building distributed AI systems."
---

# Swarm Orchestration

## What This Skill Does

Orchestrates multi-agent swarms using agentic-flow's advanced coordination system. Supports mesh, hierarchical, and adaptive topologies with automatic task distribution, load balancing, and fault tolerance.

## Prerequisites

- agentic-flow v1.5.11+
- Node.js 18+
- Understanding of distributed systems (helpful)

## Quick Start

```bash
# Initialize swarm
npx agentic-flow hooks swarm-init --topology mesh --max-agents 5

# Spawn agents
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 task
npx agentic-flow hooks task-orchestrate \
  --task "Build REST API with tests" \
  --mode parallel
```

## Topology Patterns

### 1. Mesh (Peer-to-Peer)
```typescript
// Equal peers, distributed decision-making
await swarm.init({
  topology: 'mesh',
  agents: ['coder', 'tester', 'reviewer'],
  communication: 'broadcast'
});
```

### 2. Hierarchical (Queen-Worker)
```typescript
// Centralized coordination, specialized workers
await swarm.init({
  topology: 'hierarchical',
  queen: 'architect',
  workers: ['backend-dev', 'frontend-dev', 'db-designer']
});
```

### 3. Adaptive (Dynamic)
```typescript
// Automatically switches topology based on task
await swarm.init({
  topology: 'adaptive',
  optimization: 'task-complexity'
});
```

## Task Orchestration

### Parallel Execution
```typescript
// Execute tasks concurrently
const results = await swarm.execute({
  tasks: [
    { agent: 'coder', task: 'Implement API endpoints' },
    { agent: 'frontend', task: 'Build UI components' },
    { agent: 'tester', task: 'Write test suite' }
  ],
  mode: 'parallel',
  timeout: 300000 // 5 minutes
});
```

### Pipeline Execution
```typescript
// Sequential pipeline with dependencies
await swarm.pipeline([
  { stage: 'design', agent: 'architect' },
  { stage: 'implement', agent: 'coder', after: 'design' },
  { stage: 'test', agent: 'tester', after: 'implement' },
  { stage: 'review', agent: 'reviewer', after: 'test' }
]);
```

### Adaptive Execution
```typescript
// Let swarm decide execution strategy
await swarm.autoOrchestrate({
  goal: 'Build production-ready API',
  constraints: {
    maxTime: 3600,
    maxAgents: 8,
    quality: 'high'
  }
});
```

## Memory Coordination

```typescript
// Share state across swarm
await swarm.memory.store('api-schema', {
  endpoints: [...],
  models: [...]
});

// Agents read shared memory
const schema = await swarm.memory.retrieve('api-schema');
```

## Advanced Features

### Load Balancing
```typescript
// Automatic work distribution
await swarm.enableLoadBalancing({
  strategy: 'dynamic',
  metrics: ['cpu', 'memory', 'task-queue']
});
```

### Fault Tolerance
```typescript
// Handle agent failures
await swarm.setResiliency({
  retry: { maxAttempts: 3, backoff: 'exponential' },
  fallback: 'reassign-task'
});
```

### Performance Monitoring
```typescript
// Track swarm metrics
const metrics = await swarm.getMetrics();
// { throughput, latency, success_rate, agent_utilization }
```

## Integration with Hooks

```bash
# Pre-task coordination
npx agentic-flow hooks pre-task --description "Build API"

# Post-task synchronization
npx agentic-flow hooks post-task --task-id "task-123"

# Session restore
npx agentic-flow hooks session-restore --session-id "swarm-001"
```

## Best Practices

1. **Start small**: Begin with 2-3 agents, scale up
2. **Use memory**: Share context through swarm memory
3. **Monitor metrics**: Track performance and bottlenecks
4. **Enable hooks**: Automatic coordination and sync
5. **Set timeouts**: Prevent hung tasks

## Troubleshooting

### Issue: Agents not coordinating
**Solution**: Verify memory access and enable hooks

### Issue: Poor performance
**Solution**: Check topology (use adaptive) and enable load balancing

## Learn More

- Swarm Guide: docs/swarm/orchestration.md
- Topology Patterns: docs/swarm/topologies.md
- Hooks Integration: docs/hooks/coordination.md

© ruvnet · MIT · ruvnet/ruflo

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