What are the different swarm topologies supported?

The skill supports Mesh (peer-to-peer), Hierarchical (commander-subordinate), Star (centralized coordinator), and Ring (sequential processing) topologies.

Can I use this for complex research projects?

Yes, the Research Swarm pattern is specifically designed for parallel data gathering, academic analysis, and automated report synthesis.

What are the prerequisites for using this skill?

You need the Claude Flow framework installed via npm and the associated MCP server configured to enable multi-agent orchestration.

Does this skill help with software testing?

Absolutely. It includes a Testing Swarm architecture that coordinates specialized agents for unit, integration, E2E, and performance testing.

How does this skill handle agent communication?

It uses the Claude Flow framework and MCP tools to manage agent communication, task delegation, and shared memory namespaces.

Advanced Swarm Orchestration

Name: Advanced Swarm Orchestration
Author: ricable

byricable

•

Collaboration Tools

Orchestrates multi-agent swarms for distributed research, full-stack development, and automated testing using the Claude Flow framework.

About

This skill enables Claude to manage complex distributed workflows by coordinating specialized AI agents through advanced swarm topologies such as Mesh, Hierarchical, Star, and Ring. Whether you are conducting deep research with a network of analysts, executing full-stack development via a structured command chain, or performing high-scale parallel testing, this skill provides the patterns and MCP tools necessary to scale AI capabilities. It streamlines the entire agent lifecycle, from spawning and task orchestration to cross-agent memory management and quality assessment.

Key Features

Parallel task execution with built-in dependency and priority management
2 GitHub stars
Automated multi-agent spawning with specialized roles and capabilities
Comprehensive QA workflows for code review, security audits, and testing
Multi-topology orchestration including Mesh, Hierarchical, Star, and Ring patterns
Integrated knowledge graph management and persistent cross-agent memory

Use Cases

Coordinated full-stack software development featuring specialized architect and coder roles
Distributed deep research involving parallel information gathering and automated synthesis
High-concurrency automated testing swarms for unit, integration, and performance validation

About

Key Features

Parallel task execution with built-in dependency and priority management
2 GitHub stars
Automated multi-agent spawning with specialized roles and capabilities
Comprehensive QA workflows for code review, security audits, and testing
Multi-topology orchestration including Mesh, Hierarchical, Star, and Ring patterns
Integrated knowledge graph management and persistent cross-agent memory

Use Cases

Coordinated full-stack software development featuring specialized architect and coder roles
Distributed deep research involving parallel information gathering and automated synthesis
High-concurrency automated testing swarms for unit, integration, and performance validation