Swarm Advanced

This is for when you need multiple AI agents working together on complex tasks like deep research, full-stack development, or distributed testing. You get four topology patterns (mesh, hierarchical, star, ring) depending on whether you need peer collaboration or coordinated workflows. The research pattern shows agents gathering info in parallel, validating sources, building knowledge graphs, then synthesizing reports. Development pattern coordinates architects, coders, testers, and reviewers in a hierarchy. It's built on claude-flow MCP tools with CLI fallbacks. Honestly, the orchestration code gets verbose fast, but if you're doing anything that genuinely benefits from parallel specialist agents rather than sequential prompting, the structured approach here beats ad-hoc coordination.

skills.sh installs: 1.2K
GitHub stars: 81.4K
last updated: Aug 21, 2026

View on GitHub

Install

$ npx -y skills add ruvnet/ruflo --skill swarm-advanced --agent claude-code

Installs into .claude/skills of the current project.

Files

Advanced Swarm Orchestration

Master advanced swarm patterns for distributed research, development, and testing workflows. This skill covers comprehensive orchestration strategies using both MCP tools and CLI commands.

Quick Start

Prerequisites

# Ensure Claude Flow is installed
npm install -g claude-flow@alpha

# Add MCP server (if using MCP tools)
claude mcp add claude-flow npx claude-flow@alpha mcp start

Basic Pattern

// 1. Initialize swarm topology
mcp__claude-flow__swarm_init({ topology: "mesh", maxAgents: 6 })

// 2. Spawn specialized agents
mcp__claude-flow__agent_spawn({ agentType: "researcher", name: "Agent 1" })

// 3. Orchestrate tasks
mcp__claude-flow__task_orchestrate({ task: "...", strategy: "parallel" })