orchestrating-swarms

Orchestrate multi-agent teams with leader-teammate models and JSON messaging.

Updated May 2, 2026
One-click install
npx skills add https://github.com/iliaal/compound-engineering-plugin --skill orchestrating-swarms-iliaal
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: orchestrating-swarms
Source: https://github.com/iliaal/compound-engineering-plugin/tree/main/plugins/compound-engineering/skills/orchestrating-swarms
Command: npx skills add https://github.com/iliaal/compound-engineering-plugin --skill orchestrating-swarms-iliaal

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill provides a robust framework for coordinating multiple AI agents, enabling complex workflows that would be difficult or impossible for a single agent to manage.

Core Features & Use Cases

  • Team Management: Create, manage, and communicate within teams of agents.
  • Task Orchestration: Define, assign, and track tasks with dependencies for sequential or parallel execution.
  • Inter-Agent Communication: Facilitate structured messaging between agents via inboxes and specific message types.
  • Use Case: Coordinate a team of specialized agents (e.g., a security reviewer, a performance analyst, and a code simplicity checker) to perform a comprehensive review of a pull request in parallel.

Quick Start

Use the orchestrating-swarms skill to spawn a team named 'code-review' and assign a 'security' agent to review the current pull request.

Frequently Asked Questions about orchestrating-swarms

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

FAQPage Schema
How do I coordinate multiple AI agents for parallel task execution?

Multi-agent coordination uses a leader-teammate model where a leader agent spawns teammates, assigns tasks, and routes structured JSON messages to agent inboxes for parallel execution across distributed workflows.

What is a leader-teammate model in multi-agent orchestration?

A leader-teammate orchestration model designates a primary agent to manage team creation, distribute tasks with dependencies, and process structured inbox messages to coordinate specialized AI teammates.

How do I set up a pipeline workflow for distributed AI tasks?

Set up a distributed pipeline workflow by creating a team, spawning specialized agents, and defining sequential or parallel tasks with dependencies that communicate through structured JSON-based messaging.

Can I use multi-agent orchestration for parallel code review tasks?

Multi-agent orchestration supports parallel code review by spawning a team of specialized agents, such as a security reviewer and performance analyst, to process distinct review tasks simultaneously.

Do I need dependencies to run a multi-agent swarm?

Multi-agent swarm orchestration requires no external dependencies, relying entirely on structured JSON-based messaging and internal task management to coordinate distributed AI agent execution.

How do agents communicate in a multi-agent swarm?

Agents in a multi-agent swarm communicate via structured JSON-based messages routed to specific inboxes, enabling the leader to assign tasks and teammates to report execution results.