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V3 Swarm Coordination

Orchestrate a 15-agent hierarchical mesh for v3 implementation workflows.

Updated Apr 12, 2026
Search Tags:#release-management#agent-coordination#parallel-execution#performance-monitoring#dependency-management#github-integration#swarm-orchestration
One-click install
npx skills add https://github.com/softmg/product-tracker --skill v3-swarm-coordination-softmg
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: V3 Swarm Coordination
Source: https://github.com/softmg/product-tracker/tree/main/.claude/skills/v3-swarm-coordination
Command: npx skills add https://github.com/softmg/product-tracker --skill v3-swarm-coordination-softmg

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill solves the challenge of coordinating a complex, multi-domain 15-agent hierarchical swarm to implement a v3 product flow, removing manual orchestration of dependencies, parallel tasks, and timeline enforcement across security, core, integration, testing, performance, and release domains.

Core Features & Use Cases

  • Hierarchical mesh orchestration: Define and run a queen coordinator plus domain agents with explicit roles and phases.
  • Parallel execution with dependency resolution: Run phase-based parallel tasks while detecting and preventing deadlocks in agent dependency graphs.
  • GitHub and CI/CD automation: Initialize milestones, create epic issues, assign agents, and prepare release pipelines for a 14-week delivery.
  • Performance and quality monitoring: Track agent utilization, communication latency, benchmarking targets, and TDD-based test coverage.
  • Use Case: Execute a 14-week v3 implementation that remediates security CVEs, unifies memory systems, integrates agentic-flow, and validates performance targets.

Quick Start

Initialize the 15-agent v3 swarm and begin the phase-based execution using the queen coordinator task.

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 parallel execution across multiple agents without deadlocks?▼

Coordinate parallel execution across multiple agents by using a hierarchical mesh orchestration model with a queen coordinator. This architecture manages phase-based parallel tasks and detects deadlocks in agent dependency graphs to prevent execution stalls.

What is hierarchical mesh orchestration for multi-agent implementation workflows?▼

Hierarchical mesh orchestration is a coordination structure using a queen coordinator plus domain agents with explicit roles. It manages complex multi-agent implementation workflows across security, core, and integration domains while enforcing timeline constraints.

How do I automate GitHub milestones and issue assignment for a multi-agent release pipeline?▼

Automate GitHub milestones and issue assignment by integrating CI/CD automation within the swarm orchestration workflow. The system initializes milestones, creates epic issues, assigns agents, and prepares release pipelines for the 14-week delivery.

Can I use a 15-agent swarm to manage dependencies and enforce a 14-week delivery timeline?▼

Yes, you can use a 15-agent swarm to manage dependencies and enforce a 14-week delivery timeline. The orchestration model satisfies technical requirements for dependency resolution and strict timeline enforcement across all domain agents.

How do I monitor agent utilization and communication latency during parallel task orchestration?▼

Monitor agent utilization and communication latency by tracking performance metrics within the orchestration framework. The system measures communication latency, tracks agent utilization, and validates benchmarking targets during parallel task execution.

When should I use multi-agent swarm orchestration instead of standard release management workflows?▼

Use multi-agent swarm orchestration instead of standard release management workflows when your project requires coordinating complex, multi-domain implementations like security remediation, memory unification, and performance validation across a 14-week delivery lifecycle.

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