flow-nexus-swarm

Deploy and manage cloud-based AI agent swarms for event-driven workflow automation.

6|3|Updated Dec 3, 2025
One-click install
npx skills add https://github.com/pacphi/ampel --skill flow-nexus-swarm-pacphi
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: flow-nexus-swarm
Source: https://github.com/pacphi/ampel/tree/main/.claude/skills/flow-nexus-swarm
Command: npx skills add https://github.com/pacphi/ampel --skill flow-nexus-swarm-pacphi

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Enables cloud-based orchestration of AI agent swarms, with event-driven workflows, template patterns, and scalable agent coordination.

Core Features & Use Cases

  • Swarm Management: Initialize, spawn agents, and scale swarms
  • Workflow Automation: Event-driven steps, triggers, and retries
  • Templates & Patterns: Reusable swarm configurations for common use cases
  • Agent Orchestration: Vector matching and assignment strategies
  • Monitoring & Scale: Real-time metrics and audit trails

Quick Start

mcp__flow - nexus__swarm_init({ topology: 'hierarchical', maxAgents: 8, strategy: 'balanced' }); mcp__flow - nexus__agent_spawn({ type: 'researcher', name: 'Lead Researcher' });

Frequently Asked Questions about flow-nexus-swarm

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I deploy AI agent swarms for event-driven workflow automation?

Event-driven workflow automation with AI agent swarms involves initializing swarm topology, spawning agents with assigned roles, and configuring message-queue processing. This Skill handles cloud-based deployment across hierarchical, mesh, ring, and star topologies, managing agent lifecycle and task orchestration automatically.

What topology options are available for multi-agent swarm configurations?

Multi-topology swarm configurations include hierarchical, mesh, ring, and star topologies. Each topology determines how agents communicate and coordinate tasks. This Skill supports all four patterns, letting you choose based on your workflow complexity, latency requirements, and coordination needs.

Can I scale AI agent swarms on cloud infrastructure with real-time monitoring?

Yes. This Skill manages scalable cloud-based swarms with real-time metrics, audit trails, and automatic agent spawning. Vector similarity-based agent assignment optimizes task routing, and built-in monitoring tracks swarm health, performance, and execution state across all agents.

How does vector similarity-based agent assignment work in swarm orchestration?

Vector similarity-based agent assignment matches incoming tasks to agents by semantic relevance. The Skill compares task embeddings against agent capability vectors to route work efficiently, reducing latency and improving task completion rates in large, diverse swarms.

Do I need templates and patterns to set up swarm configurations?

Templates and patterns are provided for common swarm use cases, reducing setup time and standardizing configurations. You can initialize swarms manually or use reusable templates as starting points, then customize topology, agent count, and orchestration strategy.

What happens when tasks fail or need retry in event-driven workflows?

Event-driven workflows include built-in retry logic and failure handling. The Skill manages step retries, event triggers, and task reassignment automatically, ensuring workflow resilience without manual intervention.