What is a swarm topology in this context?

A topology defines the communication structure between agents, such as Mesh for peer-to-peer research or Hierarchical for structured development workflows.

Does this skill require external dependencies?

Yes, it is designed to work with the Claude Flow MCP server and the claude-flow CLI tool.

How does the 'Adaptive' strategy work?

The adaptive strategy dynamically adjusts the agent distribution and work intensity based on the specific complexity of the task assigned.

Can I use this for automated testing?

Yes, the Testing Swarm pattern provides specialized agents for unit, integration, E2E, and performance testing.

Advanced Swarm Orchestration

Name: Advanced Swarm Orchestration
Author: ricable

byricable

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Productivity & Workflow

Orchestrates multi-agent AI swarms using advanced topologies for distributed research, development, and testing workflows.

About

Advanced Swarm Orchestration is a sophisticated skill for Claude Code that enables the coordination of multiple specialized AI agents through complex topological patterns. It provides a comprehensive framework for managing distributed workflows, allowing users to switch between mesh, hierarchical, star, and ring topologies depending on the task's complexity. Whether conducting deep research via parallel synthesis, managing full-stack development through specialist hierarchies, or executing rigorous distributed testing, this skill streamlines agent communication and task delegation to maximize efficiency and output quality within the Claude Flow ecosystem.

Key Features

1 GitHub stars
Parallel and sequential task orchestration with adaptive strategies
Dynamic specialized agent spawning with custom roles and capabilities
Integrated quality assessment for code, research, and test coverage
Distributed memory management and knowledge graph construction
Multi-topology support including Mesh, Hierarchical, Star, and Ring patterns

Use Cases

Managing a hierarchical development swarm for full-stack application building
Coordinating a parallel research team for deep information gathering and trend analysis
Executing comprehensive distributed testing across unit, integration, and E2E layers

About

Key Features

1 GitHub stars
Parallel and sequential task orchestration with adaptive strategies
Dynamic specialized agent spawning with custom roles and capabilities
Integrated quality assessment for code, research, and test coverage
Distributed memory management and knowledge graph construction
Multi-topology support including Mesh, Hierarchical, Star, and Ring patterns

Use Cases

Managing a hierarchical development swarm for full-stack application building
Coordinating a parallel research team for deep information gathering and trend analysis
Executing comprehensive distributed testing across unit, integration, and E2E layers