Orchestration Skill Guidelines

When to Use This Skill

• Parallel multi-agent execution requiring concurrent task processing
• Complex implementation with 6+ independent tasks
• Theater-free development requiring 0% tolerance validation
• Dynamic agent selection from 86+ agent registry
• High-quality delivery needing Byzantine consensus validation

When NOT to Use This Skill

• Single-agent tasks with no parallelization benefit
• Simple sequential work completing in <2 hours
• Planning phase (use research-driven-planning first)
• Trivial changes to single files

Success Criteria

• Agent+skill matrix generated with optimal assignments
• Parallel execution successful with 8.3x speedup achieved
• Theater detection passes with 0% theater detected
• Integration tests pass at 100% rate
• All agents complete with no orphaned workers

Edge Cases to Handle

• Agent failures - Implement agent health monitoring and replacement
• Task timeout - Configure per-task timeout with escalation
• Consensus failure - Have fallback from Byzantine to weighted consensus
• Resource exhaustion - Limit max parallel agents, queue excess
• Conflicting outputs - Implement merge conflict resolution strategy

Guardrails (NEVER Violate)

• NEVER lose agent state - Persist agent progress to memory continuously
• ALWAYS track swarm health - Monitor all agent statuses in real-time
• ALWAYS validate consensus - Require 4/5 agreement for theater detection
• NEVER skip theater audit - Zero tolerance, any theater blocks merge
• ALWAYS cleanup workers - Terminate agents on completion/failure

Evidence-Based Validation

• Check all agent statuses - Verify each agent completed successfully
• Validate parallel execution - Confirm tasks ran concurrently, not sequentially
• Measure speedup - Calculate actual speedup vs sequential baseline
• Audit theater detection - Run 6-agent consensus, verify 0% detection
• Verify integration - Execute sandbox tests, confirm 100% pass rate

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