swarm-advanced

Multi-agent coordination is automated by configuring distributed topologies like mesh or hierarchical, enabling parallel task execution across agents. You spawn specialized agents and define orchestrations using task and memory primitives to run concurrently.

Swarm orchestration supports mesh, hierarchical, star, and ring topologies. Choose mesh for peer-to-peer agent communication, hierarchical for structured delegation, star for centralized control, or ring for sequential passing of tasks.

Fault tolerance in distributed multi-agent workflows is managed through monitoring and auto-recovery mechanisms. The orchestration system continuously tracks agent status and automatically handles errors to ensure scalable execution without manual intervention.

Yes, Claude Flow swarms support both sequential and parallel execution modes. You can define orchestrations using task and memory primitives, then switch between modes depending on whether your workflow requires concurrent processing or ordered steps.

Swarm orchestration limitations depend on your configured maximum number of agents and chosen topology. Complex workflows require careful agent spawning and memory management to prevent coordination overhead from outweighing parallel execution benefits.

Memory management across multiple agents is handled through memory primitives defined within the orchestration configuration. These primitives enable cross-agent communication and shared state tracking, ensuring reliable data handoffs during both parallel and sequential execution.