V3 Deep Integration

V3 Deep Integration is a skill for Claude Code from proffesor-for-testing/agentic-qe. It costs 39 tokens per session (1,712 once invoked), scanned A, a copy of V3 Deep Integration, MIT.

An integration skill that turns claude-flow into a specialized extension of agentic-flow instead of maintaining a parallel implementation.

In plain words
What is it for?
It helps integrate learning modes, Flash Attention, and AgentDB coordination with agentic-flow.
Why use it?
It reduces duplicated code and connects existing capabilities through an adapter layer.

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 — 123 skills, 8 commands, 9 agents shipped together

Good fit It helps integrate learning modes, Flash Attention, and AgentDB coordination with agentic-flow.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/proffesor-for-testing/agentic-qe/v3-integration-deep
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-integration-deep
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 123 skills, 8 commands, 9 agents.

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 Deep Integration

README.md
[![agentmods](https://agentmods.dev/badge/skills/proffesor-for-testing/agentic-qe/v3-integration-deep/github.svg)](https://agentmods.dev/skills/proffesor-for-testing/agentic-qe/v3-integration-deep)
Your own site
<a href="https://agentmods.dev/skills/proffesor-for-testing/agentic-qe/v3-integration-deep"><img src="https://agentmods.dev/badge/skills/proffesor-for-testing/agentic-qe/v3-integration-deep/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 Deep Integration

Your own site · 80×15
<a href="https://agentmods.dev/skills/proffesor-for-testing/agentic-qe/v3-integration-deep"><img src="https://agentmods.dev/badge/skills/proffesor-for-testing/agentic-qe/v3-integration-deep.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 39 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,712 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 $0.00039 $0.01712
Opus 5.5 $0.00016 $0.00685
Sonnet 5.5 $0.00008 $0.00342
Haiku 4.5 $0.00004 $0.00171

Measured 1mo ago against content hash 498e921ffa71, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

V3 Deep Integration 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 1mo 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 Deep Integration — 6 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-integration-deep/SKILL.md · 241 lines

How it starts

The opening of the file, as written. The whole thing — 241 lines — stays where its author put it; the contents beside it link to each section on GitHub.

V3 Deep Integration

What This Skill Does

Transforms claude-flow from parallel implementation to specialized extension of agentic-flow@alpha, eliminating massive code duplication while achieving performance improvements and feature parity.

Quick Start

# Initialize deep integration
Task("Integration architecture", "Design agentic-flow@alpha adapter layer", "v3-integration-architect")

# Feature integration (parallel)
Task("SONA integration", "Integrate 5 SONA learning modes", "v3-integration-architect")
Task("Flash Attention", "Implement 2.49x-7.47x speedup", "v3-integration-architect")
Task("AgentDB coordination", "Setup 150x-12,500x search", "v3-integration-architect")

Code Deduplication Strategy

Current Overlap → Integration

┌─────────────────────────────────────────┐
│  claude-flow          agentic-flow      │
├─────────────────────────────────────────┤
│ SwarmCoordinator  →   Swarm System      │ 80% overlap (eliminate)
│ AgentManager      →   Agent Lifecycle   │ 70% overlap (eliminate)
│ TaskScheduler     →   Task Execution    │ 60% overlap (eliminate)
│ SessionManager    →   Session Mgmt      │ 50% overlap (eliminate)
└─────────────────────────────────────────┘

TARGET: <5,000 lines (vs 15,000+ currently)

agentic-flow@alpha Feature Integration

SONA Learning Modes

class SONAIntegration {
  async initializeMode(mode: SONAMode): Promise<void> {
    switch(mode) {
      case 'real-time':   // ~0.05ms adaptation
      case 'balanced':    // general purpose
      case 'research':    // deep exploration
      case 'edge':        // resource-constrained
      case 'batch':       // high-throughput
    }
    await this.agenticFlow.sona.setMode(mode);
  }
}

Flash Attention Integration

class FlashAttentionIntegration {
  async optimizeAttention(): Promise<AttentionResult> {
    return this.agenticFlow.attention.flashAttention({
      speedupTarget: '2.49x-7.47x',
      memoryReduction: '50-75%',
      mechanisms: ['multi-head', 'linear', 'local', 'global']
    });
  }
}

Read the full file on GitHub · 241 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. 1mo ago First seen · 241 lines · 39 tokens per session scan A 498e921ffa71

Subscribe to this mod's changes

V3 Deep Integration is a skill published in the GitHub repository proffesor-for-testing/agentic-qe (514 stars, last pushed today), licensed MIT. It adds 39 tokens to every session and 1,712 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to V3 Deep Integration, differing in 6 lines, and is treated as a copy.

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