swarm-advanced

What problem does it solve?

This Skill provides the tools to orchestrate complex distributed AI workflows for research, development, and testing, moving beyond basic single-agent tasks to leverage the full power of multi-agent systems.

Core Features & Use Cases

• Advanced Swarm Topologies: Utilize Mesh, Hierarchical, Star, and Ring topologies for tailored coordination in diverse scenarios.
• Specialized Agent Strategies: Employ Adaptive, Balanced, Specialized, and Parallel strategies for dynamic work distribution.
• Research Swarm Pattern: Conduct deep research through parallel information gathering, analysis, and synthesis.
• Development Swarm Pattern: Coordinate full-stack development with specialized agents for architecture, coding, and testing.
• Testing Swarm Pattern: Achieve comprehensive quality assurance through distributed unit, integration, E2E, and performance testing.
• Use Case: Deploy a hierarchical development swarm to "build a REST API with authentication," where an architect designs, multiple coders implement in parallel, and testers validate concurrently.

Quick Start

Initialize a mesh topology swarm with 6 agents: mcp__claude-flow__swarm_init({ topology: "mesh", maxAgents: 6 }) Spawn a researcher agent: mcp__claude-flow__agent_spawn({ type: "researcher", name: "Agent 1" }) Orchestrate a task with parallel execution: mcp__claude-flow__task_orchestrate({ task: "...", strategy: "parallel" })