V3 Swarm Coordination

V3 Swarm Coordination is a skill for Claude Code from proffesor-for-testing/agentic-qe. It costs 40 tokens per session (2,941 once invoked), scanned A, a copy of V3 Swarm Coordination, MIT.

A coordination plan for having 15 specialised agents work together on a version 3 implementation.

In plain words
What is it for?
It is for coordinating large multi-part implementation projects with separate agents and defined work areas.
Why use it?
It organizes parallel work across security, core features, and integrations while keeping dependencies and milestones aligned.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: installed under .agents/ (shared by several agents).

Part of the claude-flow plugin — 134 skills, 46 commands, 11 agents, 4 hooks shipped together

Good fit It is for coordinating large multi-part implementation projects with separate agents and defined work areas.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/proffesor-for-testing/agentic-qe/v3-swarm-coordination
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add proffesor-for-testing/agentic-qe --skill v3-swarm-coordination
Clone the repo
git clone --depth 1 https://github.com/proffesor-for-testing/agentic-qe

Made for: Claude Code.

Or install claude-flow, the plugin that ships this one along with the rest of its 134 skills, 46 commands, 11 agents, 4 hooks.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for V3 Swarm Coordination

README.md
[![agentmods](https://agentmods.dev/badge/skills/proffesor-for-testing/agentic-qe/v3-swarm-coordination/github.svg)](https://agentmods.dev/skills/proffesor-for-testing/agentic-qe/v3-swarm-coordination)
Your own site
<a href="https://agentmods.dev/skills/proffesor-for-testing/agentic-qe/v3-swarm-coordination"><img src="https://agentmods.dev/badge/skills/proffesor-for-testing/agentic-qe/v3-swarm-coordination/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for V3 Swarm Coordination

Your own site · 80×15
<a href="https://agentmods.dev/skills/proffesor-for-testing/agentic-qe/v3-swarm-coordination"><img src="https://agentmods.dev/badge/skills/proffesor-for-testing/agentic-qe/v3-swarm-coordination.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 40 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,941 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 100% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00040 $0.02941
Opus 5 $0.00020 $0.01470
Sonnet 5 $0.00008 $0.00588
Haiku 4.5 $0.00004 $0.00294

Measured 6d ago against content hash 5edfd5e1e675, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

V3 Swarm Coordination scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

100% identical to V3 Swarm Coordination — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

.agents/skills/ruflo/.agents/skills/v3-swarm-coordination/SKILL.md · 340 lines

How it starts

The opening of the file, as written. The whole thing — 340 lines — stays where its author put it; the contents beside it link to each section on GitHub.

V3 Swarm Coordination

What This Skill Does

Orchestrates the complete 15-agent hierarchical mesh swarm for claude-flow v3 implementation, coordinating parallel execution across domains while maintaining dependencies and timeline adherence.

Quick Start

# Initialize 15-agent v3 swarm
Task("Swarm initialization", "Initialize hierarchical mesh for v3 implementation", "v3-queen-coordinator")

# Security domain (Phase 1 - Critical priority)
Task("Security architecture", "Design v3 threat model and security boundaries", "v3-security-architect")
Task("CVE remediation", "Fix CVE-1, CVE-2, CVE-3 vulnerabilities", "security-auditor")
Task("Security testing", "Implement TDD security framework", "test-architect")

# Core domain (Phase 2 - Parallel execution)
Task("Memory unification", "Implement AgentDB 150x improvement", "v3-memory-specialist")
Task("Integration architecture", "Deep agentic-flow@alpha integration", "v3-integration-architect")
Task("Performance validation", "Validate 2.49x-7.47x targets", "v3-performance-engineer")

15-Agent Swarm Architecture

Hierarchical Mesh Topology

                    👑 QUEEN COORDINATOR
                         (Agent #1)
                             │
        ┌────────────────────┼────────────────────┐
        │                   │                    │
   🛡️ SECURITY         🧠 CORE              🔗 INTEGRATION
   (Agents #2-4)       (Agents #5-9)        (Agents #10-12)
        │                   │                    │
        └────────────────────┼────────────────────┘
                             │
        ┌────────────────────┼────────────────────┐
        │                   │                    │
   🧪 QUALITY          ⚡ PERFORMANCE        🚀 DEPLOYMENT
   (Agent #13)         (Agent #14)          (Agent #15)

Agent Roster

ID Agent Domain Phase Responsibility
1 Queen Coordinator Orchestration All GitHub issues, dependencies, timeline
2 Security Architect Security Foundation Threat modeling, CVE planning
3 Security Implementer Security Foundation CVE fixes, secure patterns
4 Security Tester Security Foundation TDD security testing
5 Core Architect Core Systems DDD architecture, coordination
6 Core Implementer Core Systems Core module implementation
7 Memory Specialist Core Systems AgentDB unification
8 Swarm Specialist Core Systems Unified coordination engine
9 MCP Specialist Core Systems MCP server optimization
10 Integration Architect Integration Integration agentic-flow@alpha deep integration
11 CLI/Hooks Developer Integration Integration CLI modernization
12 Neural/Learning Dev Integration Integration SONA integration
13 TDD Test Engineer Quality All London School TDD
14 Performance Engineer Performance Optimization Benchmarking validation
15 Release Engineer Deployment Release CI/CD and v3.0.0 release

Read the full file on GitHub · 340 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 6d ago First seen · 340 lines · 40 tokens per session scan A 5edfd5e1e675

Subscribe to this mod's changes

V3 Swarm Coordination is a skill published in the GitHub repository proffesor-for-testing/agentic-qe (475 stars, last pushed 2d ago), licensed MIT. It adds 40 tokens to every session and 2,941 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to V3 Swarm Coordination, differing in 0 lines, and is treated as a copy.

Related

Other skills, from other repositories

foundry-config-setup

Resolve missing setup caused by a hardcoded Foundry project endpoint or model in a sample. Use when a sample fails because it uses a placeholder/hardcoded projectendpoint (for example "https://your-project.services.ai.azure.com") or a hardcoded model instead of reading them from the environment.

microsoft/agent-framework · 65 tokens

dogfood

Systematically explore and test a mobile app on iOS/Android with agent-device to find bugs, UX issues, and other problems. Use when asked to dogfood, QA, exploratory test, find issues, bug hunt, or test this app on mobile.

callstack/agent-device · 55 tokens

tooluniverse-drug-research

Comprehensive drug profiling — mechanism, primary/secondary targets, drug interactions, clinical-trial status, adverse events (FAERS), pharmacogenomics, and approval history. Use for full drug investigation reports, 'tell me about drug X' queries, and assembling drug profiles for clinicians, researchers, or regulatory…

mims-harvard/ToolUniverse · 71 tokens

monorepo-management

Master monorepo management with Turborepo, Nx, and pnpm workspaces to build efficient, scalable multi-package repositories with optimized builds and dependency management. Use when setting up monorepos, optimizing builds, or managing shared dependencies.

wshobson/agents · 54 tokens

gh-bulk-issues

Orchestrate parallel Mastra Code headless instances to debug and fix multiple GitHub issues simultaneously.

mastra-ai/mastra · 25 tokens

qa-investigation

Investigate a specific test failure to its root cause and document the why. Detects whether a failing test is flaky (intermittent) or a deterministic bug during reproduction. Use when a test fails and you need the real cause, not just to make it green. Execution layer, not strategy review. Keywords: flaky test…

fugazi/test-automation-skills-agents · 94 tokens