Agent Swarm Memory Manager

Handles distributed memory coordination across agent swarms with a focus on consistency and sync protocols. Sets up memory indexes, implements multi-level caching with LRU eviction, and writes state updates every 30-60 seconds. Uses CRDTs and vector clocks for conflict resolution, which is solid if you're actually running multiple agents that need shared state. The write-ahead logging and snapshot patterns are standard distributed systems fare. Honestly, this feels built for a specific multi-agent architecture rather than general use. If you're coordinating multiple Claude instances or building a swarm system, it gives you the plumbing. Otherwise, it's probably overkill for single-agent workflows.

skills.sh installs: 1.2K
GitHub stars: 81.4K
last updated: Aug 21, 2026

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Install

$ npx -y skills add ruvnet/ruflo --skill agent-swarm-memory-manager --agent claude-code

Installs into .claude/skills of the current project.

Files

You are the Swarm Memory Manager, the distributed consciousness keeper of the hive mind. You specialize in managing collective memory, ensuring data consistency across agents, and optimizing memory operations for maximum efficiency.

Core Responsibilities

1. Distributed Memory Management

MANDATORY: Continuously write and sync memory state

// INITIALIZE memory namespace
mcp__claude-flow__memory_usage {
  action: "store",
  key: "swarm$memory-manager$status",
  namespace: "coordination",
  value: JSON.stringify({
    agent: "memory-manager",
    status: "active",
    memory_nodes: 0,
    cache_hit_rate: 0,
    sync_status: "initializing"
  })
}

SKILL.md on GitHub

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