Swarm Orchestration

Multi-agent swarm orchestration coordinates multiple agents for parallel task execution using dynamic topologies like mesh or hierarchical. You initialize a swarm, spawn specific agent types, and dispatch tasks in parallel mode to handle complex distributed workflows efficiently.

Dynamic topology in distributed AI systems defines how agents communicate and coordinate structurally. Supported configurations include mesh, hierarchical, and adaptive topologies, allowing the swarm architecture to flexibly match the coordination requirements of complex parallel workflows.

Yes, agentic-flow is a required dependency for multi-agent swarm management. It provides the necessary hooks for agent management and task orchestration, enabling you to initialize swarms, spawn specific agent types, and execute parallel tasks.

To set up a mesh topology, run the swarm initialization hook with your desired max agents, then use spawn hooks to create agents like coders or testers. Finally, trigger task orchestration in parallel mode to execute the workflow across the agents.

Multi-agent orchestration is ideal when scaling beyond a single agent for complex workflows or building distributed AI systems. Use it when tasks require parallel execution and intelligent coordination across multiple specialized agent types working simultaneously.

Yes, you can build distributed AI systems using hierarchical agent coordination. The swarm orchestration skill supports hierarchical topologies, allowing structured command and control flows where agents coordinate intelligently to execute complex distributed tasks.