swarm-advanced

Name: swarm-advanced
Availability: InStock
Author: dzhechko

Orchestrate multi-agent swarms with memory, fault tolerance, and Claude Flow MCP tools.

Updated Aug 23, 2026

Search Tags:#MCP #multi-agent #orchestration #distributed #swarm #Claude Flow

Ready to run

npx skills add https://github.com/dzhechko/stt-rag-app --skill swarm-advanced-dzhechko

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: swarm-advanced
Source: https://github.com/dzhechko/stt-rag-app/tree/main/.claude/skills/swarm-advanced
Command: npx skills add https://github.com/dzhechko/stt-rag-app --skill swarm-advanced-dzhechko

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill enables advanced swarm orchestration patterns to coordinate distributed research, development, and testing tasks across multi-agent systems, reducing coordination overhead and manual effort.

Core Features & Use Cases

Topology-agnostic orchestration: supports mesh, hierarchical, star, and ring patterns to tailor coordination to the task.
Multi-role agent orchestration: supports diverse agent types (researchers, analysts, developers, testers) with memory and task orchestration.
Fault-tolerant and scalable workflows: built-in fault tolerance, monitoring, and auto-scaling mechanisms for large, complex experiments.
Real-world templates: ready-to-run patterns for research swarms, development swarms, testing swarms, and analysis swarms.

Quick Start

Install Claude Flow CLI and MCP tools:
- npm install -g claude-flow@alpha
Initialize a swarm with a mesh topology and up to 6 agents:
- mcp__claude-flow__swarm_init({ topology: "mesh", maxAgents: 6 })
Spawn a team and orchestrate tasks using the provided examples.

Frequently Asked Questions about swarm-advanced

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

FAQPage Schema

How do I coordinate multi-agent workflows for distributed development and testing?▼

Mesh, hierarchical, star, and ring topology patterns are supported. This allows you to tailor swarm coordination to specific distributed tasks, whether you need decentralized peer collaboration or strict hierarchical task delegation.

How do I initialize a multi-agent swarm using Claude Flow?▼

Yes, specialized roles including researchers, analysts, developers, and testers are supported. Each agent type operates with task orchestration and memory management, enabling coordinated, topology-aware execution across complex experiments.

What is topology-aware task execution in distributed multi-agent systems?▼

Topology-aware task execution distributes work across a multi-agent swarm based on a chosen structural pattern like mesh or star. It ensures coordinated task routing, memory management, and fault tolerance for large-scale pipelines.

Does this swarm orchestration approach handle fault tolerance and auto-scaling for complex experiments?▼

Yes, the orchestration framework includes built-in fault tolerance, monitoring, and auto-scaling mechanisms. These features maintain workflow continuity and scalability during rigorous QA scenarios and large-scale development pipelines.