What problem does it solves?
This Skill enables seamless deployment and management of cloud-based AI agent swarms, automating complex event-driven workflows and ensuring intelligent agent coordination with scalable infrastructure, freeing you from manual orchestration.
Core Features & Use Cases
- Multi-topology Swarm Management: Initialize and scale swarms with hierarchical, mesh, ring, or star topologies for optimal task distribution.
- Event-driven Workflow Automation: Create and execute workflows with dependency management, parallel steps, and retry policies, triggered by various events.
- Intelligent Agent Assignment: Utilize AI-powered vector similarity matching for optimal agent selection based on task requirements, workload, and capabilities.
- Use Case: Orchestrate a full-stack development project in the cloud, where specialized agents (coder, tester, analyst) are dynamically assigned to tasks, and the entire CI/CD pipeline is automated with event triggers and auto-scaling.
Quick Start
Initialize a hierarchical swarm with 8 agents for balanced strategy
mcp__flow-nexus__swarm_init({
topology: "hierarchical",
maxAgents: 8,
strategy: "balanced"
})
Spawn a specialized researcher agent with web search and analysis capabilities
mcp__flow-nexus__agent_spawn({
type: "researcher",
name: "Lead Researcher",
capabilities: ["web_search", "analysis", "summarization"]
})
