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name: advanced-coordination description: Advanced multi-agent coordination patterns for complex distributed systems. Use when coordinating 5+ agents with dynamic task dependencies, implementing Byzantine fault tolerance, or managing distributed consensus protocols. Provides RAFT, Gossip, and Byzantine coordination strategies. version: 1.0.0 category: orchestration tags:

• orchestration
• coordination
• swarm author: ruv

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Orchestration Skill Guidelines

When to Use This Skill

• Multi-agent coordination requiring topology-aware task distribution
• Cloud-based orchestration with Flow Nexus platform integration
• Event-driven workflows needing message-based coordination
• Distributed systems spanning multiple execution environments
• Scalable swarms with adaptive topology management

When NOT to Use This Skill

• Single-agent tasks with no coordination overhead
• Local-only execution not using cloud features
• Simple sequential work without event-driven needs
• Static topologies not requiring adaptive scaling

Success Criteria

• Coordination topology established (mesh/hierarchical/star)
• All agents registered in coordination namespace
• Event routing functional with <50ms message latency
• No coordination deadlocks - All agents progressing
• Scalability validated - Handles target agent count

Edge Cases to Handle

• Network partitions - Implement partition tolerance with eventual consistency
• Message loss - Add message acknowledgment and retry logic
• Agent disconnection - Detect disconnects, redistribute work
• Topology reconfiguration - Support live topology changes without restart
• Rate limiting - Handle cloud API rate limits with backoff

Guardrails (NEVER Violate)

• NEVER lose coordination state - Persist topology and agent registry
• ALWAYS validate topology - Check for cycles, orphaned nodes
• ALWAYS monitor message queues - Prevent queue overflow
• NEVER skip health checks - Continuous agent liveness monitoring
• ALWAYS handle failures gracefully - No cascading failures

Evidence-Based Validation

• Verify topology structure - Validate graph properties (connected, acyclic if needed)
• Check message delivery - Confirm all messages reached targets
• Measure coordination overhead - Calculate % time spent on coordination vs work
• Validate agent reachability - Ping all agents, verify responses
• Audit scalability - Test with max agent count, measure performance

Advanced Coordination - Distributed Agent Management

Sophisticated coordination protocols for large-scale multi-agent systems with fault tolerance and consensus requirements.

When to Use This Skill

Use when coordinating complex multi-agent workflows with 5+ concurrent agents, implementing fault-tolerant distributed systems, managing dynamic task dependencies across agents, or requiring consensus protocols (RAFT, Byzantine, Gossip).

Coordination Strategies

RAFT Consensus

• Leader election among agents
• Replicated log consistency
• Fault tolerance for N/2+1 failures
• Strong consistency guarantees

Gossip Protocol

• Peer-to-peer agent communication
• Eventually consistent state sharing
• Highly scalable (100+ agents)
• Network partition resilient

Byzantine Fault Tolerance

• Malicious or faulty agent detection
• 3F+1 redundancy for F failures
• Cryptographic verification
• Critical system integrity

Process

1. Analyze coordination requirements

   • Determine number of agents needed
   • Identify fault tolerance needs
   • Assess consistency requirements
   • Define communication patterns

2. Select coordination strategy

   • RAFT for strong consistency
   • Gossip for high scalability
   • Byzantine for security-critical systems
   • Hybrid for complex requirements

3. Initialize coordination topology

   • Set up agent communication channels
   • Establish leader election if needed
   • Configure heartbeat and timeouts
   • Define state replication rules

4. Monitor coordination health

   • Track agent liveness
   • Detect network partitions
   • Monitor consensus progress
   • Log coordination events

5. Handle failures gracefully

   • Automatic failover
   • State recovery mechanisms
   • Network partition healing
   • Agent replacement strategies

Integration

• Claude-Flow: npx claude-flow@alpha swarm init --topology mesh
• Monitoring: Real-time coordination metrics
• Memory-MCP: Cross-agent state persistence