How does the skill handle agent failures?

The skill features built-in fault tolerance with configurable resiliency settings, including exponential backoff retries and automatic task reassignment to healthy agents.

Can agents share information during a swarm session?

Yes, the skill includes a shared memory coordination system that allows agents to store and retrieve data from a common state, ensuring context is maintained across the entire swarm.

Which swarm topologies does this skill support?

It supports Mesh (peer-to-peer), Hierarchical (queen-worker), and Adaptive topologies which dynamically adjust based on the complexity of the task.

What is the main benefit of the Swarm Orchestration skill?

It allows you to scale beyond a single AI agent by coordinating a swarm of specialized agents to work together on complex tasks, significantly increasing efficiency and capabilities.

Swarm Orchestration

Name: Swarm Orchestration
Author: aegntic

byaegntic

•

Data Science & ML

Orchestrates multi-agent AI swarms for parallel task execution and dynamic coordination using the agentic-flow framework.

Swarm Orchestration empowers Claude Code to manage complex, distributed AI workflows by coordinating multiple specialized agents simultaneously. By leveraging the agentic-flow system, it supports various architectural patterns including mesh, hierarchical, and adaptive topologies, allowing for intelligent task distribution, shared memory across agents, and automatic load balancing. This skill is essential for developers building large-scale AI systems that require more than a single agent's capabilities, ensuring fault-tolerant and high-performance execution of multi-step, production-grade projects.

Key Features

01Automatic load balancing and fault tolerance with configurable retry logic

02Comprehensive performance monitoring for tracking throughput and agent utilization

03Centralized memory system for sharing state and context across the swarm

049 GitHub stars

05Multi-agent coordination supporting mesh, hierarchical, and adaptive topologies

06Parallel and pipeline execution modes for optimized task distribution

Use Cases

01Executing complex data processing pipelines that require specialized design and review stages

02Building full-stack applications by concurrently managing backend, frontend, and testing agents

03Scaling AI-driven development workflows through dynamic agent spawning and task delegation

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add aegntic/cldcde swarm-orchestration

For use in Claude.ai and ChatGPT

Download Skill