/swarm-orchestration
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.
$ npx -y skills add ruvnet/claude-flow --skill swarm-orchestration --agent claude-codeHow it fires
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- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
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- Slash command
/swarm-orchestration
Context preview
The summary Claude sees to decide when to auto-load this skill.
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.
SKILL.md
swarm-orchestration.SKILL.mdname: "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
# 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)
// Equal peers, distributed decision-making
await swarm.init({
topology: 'mesh',
agents: ['coder', 'tester', 'reviewer'],
communication: 'broadcast'
});2. Hierarchical (Queen-Worker)
// Centralized coordination, specialized workers
await swarm.init({
topology: 'hierarchical',
queen: 'architect',
workers: ['backend-dev', 'frontend-dev', 'db-designer']
});3. Adaptive (Dynamic)
// Automatically switches topology based on task
await swarm.init({
topology: 'adaptive',
optimization: 'task-complexity'
});Task Orchestration
Parallel Execution
// 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
// 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
// Let swarm decide execution strategy
await swarm.autoOrchestrate({
goal: 'Build production-ready API',
constraints: {
maxTime: 3600,
maxAgents: 8,
quality: 'high'
}
});Memory Coordination
// 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
// Automatic work distribution
await swarm.enableLoadBalancing({
strategy: 'dynamic',
metrics: ['cpu', 'memory', 'task-queue']
});Fault Tolerance
// Handle agent failures
await swarm.setResiliency({
retry: { maxAttempts: 3, backoff: 'exponential' },
fallback: 'reassign-task'
});Performance Monitoring
// Track swarm metrics
const metrics = await swarm.getMetrics();
// { throughput, latency, success_rate, agent_utilization }Integration with Hooks
# 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
Read more
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
# 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)
// Equal peers, distributed decision-making
await swarm.init({
topology: 'mesh',
agents: ['coder', 'tester', 'reviewer'],
communication: 'broadcast'
});2. Hierarchical (Queen-Worker)
// Centralized coordination, specialized workers
await swarm.init({
topology: 'hierarchical',
queen: 'architect',
workers: ['backend-dev', 'frontend-dev', 'db-designer']
});3. Adaptive (Dynamic)
// Automatically switches topology based on task
await swarm.init({
topology: 'adaptive',
optimization: 'task-complexity'
});Task Orchestration
Parallel Execution
// 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
// 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
// Let swarm decide execution strategy
await swarm.autoOrchestrate({
goal: 'Build production-ready API',
constraints: {
maxTime: 3600,
maxAgents: 8,
quality: 'high'
}
});Memory Coordination
// 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
// Automatic work distribution
await swarm.enableLoadBalancing({
strategy: 'dynamic',
metrics: ['cpu', 'memory', 'task-queue']
});Fault Tolerance
// Handle agent failures
await swarm.setResiliency({
retry: { maxAttempts: 3, backoff: 'exponential' },
fallback: 'reassign-task'
});Performance Monitoring
// Track swarm metrics
const metrics = await swarm.getMetrics();
// { throughput, latency, success_rate, agent_utilization }Integration with Hooks
# 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
An agent meta-harness for Claude Code and Codex. Agent = Model + Harness. The model writes; the harness gives it tools, memory, loops, sandboxes, and controls so it can actually work.
Repo: ruvnet/claude-flow
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