V3 Memory Unification

V3 Memory Unification is a skill for Claude Code, Codex from ruvnet/ruflo. It costs 51 tokens per session (1,172 once invoked), scanned A, a copy of V3 Memory Unification, MIT.

A memory-system migration toolkit that combines several storage systems into AgentDB, a unified database with fast vector search. HNSW is an indexing method for quickly finding similar items.

In plain words
What is it for?
Use it to design the migration, configure vector search, and move SQLite or Markdown-based memory into AgentDB.
Why use it?
It removes duplicated memory backends and gives the application one place to store and search agent memories while preserving existing behavior.

Skill for Claude CodeCodex

Part of the claude-flow plugin — 134 skills, 52 commands, 11 agents, 4 hooks shipped together

About the project

Ruflo is an execution and coordination layer for Claude Code and Codex that equips AI coding agents with tools, memory, control loops, sandboxes, and collaboration mechanisms. Developers use it to organize specialized agents into swarms, coordinate workflows, retain knowledge across sessions, and communicate across machines. The catalogue entries are Ruflo’s skills, commands, agents, hooks, and plugin components.

ruvnet/ruflo · 70,498 stars · on GitHub · cognitum.one

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/ruflo/v3-memory-unification
Any agent
npx skills add ruvnet/ruflo --skill v3-memory-unification
Clone the repo
git clone --depth 1 https://github.com/ruvnet/ruflo

Made for: Claude Code, Codex.

Or install claude-flow, the plugin that ships this one along with the rest of its 134 skills, 52 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 Memory Unification

README.md
[![agentmods](https://agentmods.dev/badge/skills/ruvnet/ruflo/v3-memory-unification.svg)](https://agentmods.dev/skills/ruvnet/ruflo/v3-memory-unification)
Your own site
<a href="https://agentmods.dev/skills/ruvnet/ruflo/v3-memory-unification"><img src="https://agentmods.dev/badge/skills/ruvnet/ruflo/v3-memory-unification.svg" alt="Measured on agentmods" height="20"></a>
Per session 51 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,172 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00051 $0.01172
Opus 5 $0.00026 $0.00586
Sonnet 5 $0.00010 $0.00234
Haiku 4.5 $0.00005 $0.00117

Measured 2d ago against content hash 4853ec2fec84, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-05, from the pricing page.

Security

Grade A, and why

V3 Memory Unification 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 2d 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 Memory Unification — 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/v3-memory-unification/SKILL.md · 174 lines

How it starts

The opening of the file, as written. The whole thing — 174 lines — stays where its author put it; the contents beside it link to each section on GitHub.

V3 Memory Unification

What This Skill Does

Consolidates disparate memory systems into unified AgentDB backend with HNSW vector search, achieving 150x-12,500x search performance improvements while maintaining backward compatibility.

Quick Start

# Initialize memory unification
Task("Memory architecture", "Design AgentDB unification strategy", "v3-memory-specialist")

# AgentDB integration
Task("AgentDB setup", "Configure HNSW indexing and vector search", "v3-memory-specialist")

# Data migration
Task("Memory migration", "Migrate SQLite/Markdown to AgentDB", "v3-memory-specialist")

Systems to Unify

Legacy Systems → AgentDB

┌─────────────────────────────────────────┐
│  • MemoryManager (basic operations)     │
│  • DistributedMemorySystem (clustering) │
│  • SwarmMemory (agent-specific)         │
│  • AdvancedMemoryManager (features)     │
│  • SQLiteBackend (structured)           │
│  • MarkdownBackend (file-based)         │
│  • HybridBackend (combination)          │
└─────────────────────────────────────────┘
                    ↓
┌─────────────────────────────────────────┐
│       🚀 AgentDB with HNSW             │
│  • 150x-12,500x faster search          │
│  • Unified query interface             │
│  • Cross-agent memory sharing          │
│  • SONA learning integration           │
└─────────────────────────────────────────┘

Implementation Architecture

Unified Memory Service

class UnifiedMemoryService implements IMemoryBackend {
  constructor(
    private agentdb: AgentDBAdapter,
    private indexer: HNSWIndexer,
    private migrator: DataMigrator
  ) {}

  async store(entry: MemoryEntry): Promise<void> {
    await this.agentdb.store(entry);
    await this.indexer.index(entry);
  }

  async query(query: MemoryQuery): Promise<MemoryEntry[]> {
    if (query.semantic) {
      return this.indexer.search(query); // 150x-12,500x faster
    }
    return this.agentdb.query(query);
  }
}

HNSW Vector Search

class HNSWIndexer {
  constructor(dimensions: number = 1536) {
    this.index = new HNSWIndex({
      dimensions,
      efConstruction: 200,
      M: 16,
      speedupTarget: '150x-12500x'
    });
  }

  async search(query: MemoryQuery): Promise<MemoryEntry[]> {
    const embedding = await this.embedContent(query.content);
    const results = this.index.search(embedding, query.limit || 10);
    return this.retrieveEntries(results);
  }
}

Read the full file on GitHub · 174 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. 2d ago First seen · 174 lines · 51 tokens per session scan A 4853ec2fec84

Subscribe to this mod's changes

V3 Memory Unification is a skill published in the GitHub repository ruvnet/ruflo (70,498 stars, last pushed today), licensed MIT. It adds 51 tokens to every session and 1,172 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to V3 Memory Unification, differing in 0 lines, and is treated as a copy.