V3 Deep Integration

V3 Deep Integration is a skill for Claude Code, Codex from ruvnet/RuView. It costs 39 tokens per session (1,711 once invoked), scanned A, original, MIT.

Deep agentic-flow@alpha integration implementing ADR-001. Eliminates 10,000+ duplicate lines by building claude-flow as specialized extension rather than parallel implementation.

Skill for Claude CodeCodex

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.

agentmods
npx agentmods add skills/ruvnet/ruview/v3-integration-deep
Any agent
npx skills add ruvnet/RuView --skill v3-integration-deep
Clone the repo
git clone --depth 1 https://github.com/ruvnet/RuView

Made for: Claude Code, Codex.

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/ruvnet/ruview/v3-integration-deep.svg)](https://agentmods.dev/skills/ruvnet/ruview/v3-integration-deep)
Your own site
<a href="https://agentmods.dev/skills/ruvnet/ruview/v3-integration-deep"><img src="https://agentmods.dev/badge/skills/ruvnet/ruview/v3-integration-deep.svg" alt="Measured on agentmods" 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 1,711 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin unknown No closer match found 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 $0.00039 $0.01711
Opus 5 $0.00019 $0.00856
Sonnet 5 $0.00008 $0.00342
Haiku 4.5 $0.00004 $0.00171

Measured today against content hash 4e835f83bae3, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, 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 today.

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.

.claude/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. today First seen · 241 lines · 39 tokens per session scan A 4e835f83bae3

Subscribe to this mod's changes

V3 Deep Integration is a skill published in the GitHub repository ruvnet/RuView (92,432 stars, last pushed today), licensed MIT. It adds 39 tokens to every session and 1,711 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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