V3 Swarm Coordination

Orchestrates a 15-agent hierarchical mesh swarm for parallel multi-domain software implementation.

11|Updated Jan 20, 2026
One-click install
npx skills add https://github.com/ishandutta2007/claude-agent-orchestration --skill v3-swarm-coordination-ishandutta2007
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: V3 Swarm Coordination
Source: https://github.com/ishandutta2007/claude-agent-orchestration/tree/main/.claude/skills/v3-swarm-coordination
Command: npx skills add https://github.com/ishandutta2007/claude-agent-orchestration --skill v3-swarm-coordination-ishandutta2007

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Coordinating a large multi-agent implementation effort across security, core, integration, quality, performance, and release domains is error-prone when dependencies, timelines, and parallel execution are managed manually. This Skill structures the claude-flow v3 implementation as a 15-agent hierarchical mesh with defined phases, dependency graphs, and communication patterns. ## Core Features & Use Cases - 15-Agent Swarm Architecture: Defines a queen-led hierarchical mesh with a full agent roster spanning six domains and four implementation phases over a 14-week timeline. - Dependency Coordination: Provides a dependency map and deadlock-detection loop so agents execute in parallel only when their prerequisites complete. - GitHub & Communication Integration: Includes milestone creation, epic issue tracking, hourly progress reporting, and a QUIC-based inter-agent message bus with domain-targeted broadcasts. - Use Case: A team lead kicking off the v3.0.0 release can initialize the full 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 spawning the queen coordinator to set up the hierarchical mesh and begin Phase 1 security and architecture tasks.

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 one software project?

Use a hierarchical mesh topology with a queen coordinator agent that assigns domain-specific tasks to worker agents. Define a dependency map so agents execute in parallel only when prerequisites complete, and track progress through GitHub milestones and issues.

How do I initialize the 15-agent v3 swarm?

Spawn the queen coordinator with a Task call describing the v3 implementation goal, which initializes the hierarchical mesh. Then launch Phase 1 agents for security architecture, CVE remediation, and core DDD design in parallel.

How are dependencies between agents handled in a swarm?

Dependencies are stored in a map linking each agent ID to its prerequisite agents. A coordination loop repeatedly finds agents whose dependencies are complete, runs them in parallel, and throws an error if a deadlock is detected.

What happens when one agent in the swarm is overloaded?

A load balancer analyzes per-agent workloads against capacity thresholds and redistributes tasks from overloaded agents to available ones. Tasks are reassigned to the optimal agent based on current availability.

What are the limitations of a 15-agent hierarchical mesh?

The fixed 15-agent roster and hardcoded dependency map assume a specific 14-week plan, so scope changes require manual restructuring. Coordination also depends on external systems like GitHub and a QUIC message bus being available.