V3 Swarm Coordination

Orchestrates a 15-agent hierarchical mesh swarm for parallel v3 implementation across security, core, and integration domains.

Updated May 8, 2026
One-click install
npx skills add https://github.com/FrekiManagarm/d-chambaud --skill v3-swarm-coordination-frekimanagarm
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: V3 Swarm Coordination
Source: https://github.com/FrekiManagarm/d-chambaud/tree/main/.agents/skills/v3-swarm-coordination
Command: npx skills add https://github.com/FrekiManagarm/d-chambaud --skill v3-swarm-coordination-frekimanagarm

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Coordinating a large multi-agent implementation effort across security, core systems, integration, and release domains is error-prone, with risks of deadlocks, idle agents, and missed dependencies. This Skill provides a structured 15-agent hierarchical mesh coordination plan with defined phases, dependencies, and success metrics for the Codex-flow v3 implementation. ## Core Features & Use Cases - 15-Agent Hierarchical Mesh: Defines a queen coordinator plus security, core, integration, quality, performance, and deployment agents with explicit roles and phases. - Dependency-Aware Parallel Execution: Includes a dependency graph and coordination logic that runs ready agents in parallel while detecting deadlocks. - GitHub and Communication Integration: Provides milestone/epic issue creation, hourly progress tracking, and a QUIC-based swarm communication bus. - Use Case: A team lead kicking off a 14-week v3 rewrite can initialize the swarm, run phase-based execution (security foundation, core systems, integration, release), and monitor parallel efficiency against targets like >85% agent utilization. ## Quick Start Initialize the 15-agent v3 swarm by tasking the queen coordinator with setting up the hierarchical mesh for the complete v3 implementation.

Frequently Asked Questions about V3 Swarm Coordination

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

FAQPage Schema
How do I coordinate multiple AI agents on a large software project?▼

Use a hierarchical mesh topology with a queen coordinator agent managing domain-specific worker agents. Define explicit dependencies between agents, execute ready agents in parallel, and track progress through GitHub milestones and issues.

What is a hierarchical mesh agent topology?▼

A hierarchical mesh combines a central queen coordinator with domain clusters such as security, core, and integration teams. Agents communicate through a shared message bus while the coordinator manages dependencies, timeline, and load balancing.

How do I prevent deadlocks in multi-agent task dependencies?▼

Model agent dependencies as a directed graph and only execute agents whose dependencies have completed. If no agents are ready while work remains, the coordination loop detects the deadlock and raises an error instead of blocking indefinitely.

Can I integrate agent swarm progress with GitHub issues?▼

Yes, the coordination pattern creates a v3 milestone and epic issues labeled per agent, then posts hourly progress updates automatically. Each epic maps to the agents responsible for that workstream.

What are the limitations of a 15-agent swarm approach?▼

Coordination overhead grows with agent count, so parallel efficiency must be monitored against a target like 85% utilization. Overloaded agents require work redistribution, and poorly defined dependencies can still cause bottlenecks.