Agent skill

Agent Swarm Memory Manager

Agent skill for swarm-memory-manager - invoke with $agent-swarm-memory-manager

Install Agent Swarm Memory Manager

skills CLI

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

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI

$ gh skill install ruvnet/ruflo agent-swarm-memory-manager --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy

$ git clone --depth 1 https://github.com/ruvnet/ruflo.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/agent-swarm-memory-manager .claude/skills/agent-swarm-memory-manager && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Paste into Claude Code

Install the "agent-swarm-memory-manager" agent skill from https://github.com/ruvnet/ruflo/tree/main/.agents/skills/agent-swarm-memory-manager into .claude/skills/agent-swarm-memory-manager/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "agent-swarm-memory-manager", then confirm the skill loads.

Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

$skill-installer

$skill-installer install https://github.com/ruvnet/ruflo/tree/main/.agents/skills/agent-swarm-memory-manager

Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.

skills CLI

$ npx skills add ruvnet/ruflo --skill agent-swarm-memory-manager -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install ruvnet/ruflo agent-swarm-memory-manager --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/ruvnet/ruflo.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.agents/skills/agent-swarm-memory-manager .agents/skills/agent-swarm-memory-manager && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "agent-swarm-memory-manager" agent skill from https://github.com/ruvnet/ruflo/tree/main/.agents/skills/agent-swarm-memory-manager into .agents/skills/agent-swarm-memory-manager/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "agent-swarm-memory-manager", then confirm the skill loads.

Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add ruvnet/ruflo --skill agent-swarm-memory-manager -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install ruvnet/ruflo agent-swarm-memory-manager --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/ruvnet/ruflo.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.agents/skills/agent-swarm-memory-manager .cursor/skills/agent-swarm-memory-manager && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "agent-swarm-memory-manager" agent skill from https://github.com/ruvnet/ruflo/tree/main/.agents/skills/agent-swarm-memory-manager into .cursor/skills/agent-swarm-memory-manager/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "agent-swarm-memory-manager", then confirm the skill loads.

Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

gemini skills install

$ gemini skills install https://github.com/ruvnet/ruflo.git --path .agents/skills/agent-swarm-memory-manager

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add ruvnet/ruflo --skill agent-swarm-memory-manager -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install ruvnet/ruflo agent-swarm-memory-manager --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/ruvnet/ruflo.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.agents/skills/agent-swarm-memory-manager .gemini/skills/agent-swarm-memory-manager && rm -rf skills-src

Use ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "agent-swarm-memory-manager" agent skill from https://github.com/ruvnet/ruflo/tree/main/.agents/skills/agent-swarm-memory-manager into .gemini/skills/agent-swarm-memory-manager/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "agent-swarm-memory-manager", then confirm the skill loads.

Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

GitHub CLI

$ gh skill install ruvnet/ruflo agent-swarm-memory-manager

Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).

skills CLI

$ npx skills add ruvnet/ruflo --skill agent-swarm-memory-manager -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/ruvnet/ruflo.git skills-src && mkdir -p .github/skills && cp -r skills-src/.agents/skills/agent-swarm-memory-manager .github/skills/agent-swarm-memory-manager && rm -rf skills-src

Use ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "agent-swarm-memory-manager" agent skill from https://github.com/ruvnet/ruflo/tree/main/.agents/skills/agent-swarm-memory-manager into .github/skills/agent-swarm-memory-manager/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "agent-swarm-memory-manager", then confirm the skill loads.

GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add ruvnet/ruflo --skill agent-swarm-memory-manager -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install ruvnet/ruflo agent-swarm-memory-manager --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/ruvnet/ruflo.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.agents/skills/agent-swarm-memory-manager .opencode/skills/agent-swarm-memory-manager && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "agent-swarm-memory-manager" agent skill from https://github.com/ruvnet/ruflo/tree/main/.agents/skills/agent-swarm-memory-manager into .opencode/skills/agent-swarm-memory-manager/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "agent-swarm-memory-manager", then confirm the skill loads.

OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

Facts

Skill name: agent-swarm-memory-manager
GitHub stars: 74k
Used in: 2 other repos
Token cost: ~1.2k tokens
SKILL.md length: 224 words
Files: 1
Skills in repo: 264
Repo updated: Oct 9, 2026
First seen: Oct 7, 2026
Licence: MIT

At a glance

Agent skill for swarm-memory-manager - invoke with $agent-swarm-memory-manager

Works in 4 steps: Distributed Memory Management → Cache Optimization → Synchronization Protocol → …
Tasks that involve Multi-agent orchestration
SKILL.md covers Core Responsibilities, Memory Operations, Performance Metrics and Integration Points, plus 2 more sections
Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Agent Swarm Memory Manager is an agent skill from ruvnet/ruflo. Agent skill for swarm-memory-manager - invoke with $agent-swarm-memory-manager

Its SKILL.md is about 1.2k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Agent Workflows, covering Multi-agent orchestration. The repository describes itself as: 🌊 The original agent harness. Deploy intelligent multi-player swarms, coordinate autonomous workflows, and build conversational AI systems. Features adaptive memory…. The licence is MIT.

When your agent uses it

Tasks that involve Multi-agent orchestration

Example prompts

“/agent-swarm-memory-manager”

Workflow steps

4 steps, taken from the step headings in SKILL.md.

Distributed Memory Management
Cache Optimization
Synchronization Protocol
Conflict Resolution

What it can do on your machine

Read from SKILL.md and the folder at commit 58e0ae7. It shows what the files ask for, not the result of running them.

Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md (its code samples are javascript).
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Agent Swarm Memory Manager loads about 1.2k tokens when it runs. Until then it costs about 26 tokens; SKILL.md has 224 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~26
When it runs · the whole SKILL.md, loaded when a task matches: ~1.2k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from ruvnet/ruflo at commit 58e0ae7, republished under its MIT licence (© ruvnet). 224 words, ~1,236 tokens.

Download SKILL.mdSave it as .claude/skills/agent-swarm-memory-manager/SKILL.md (or your agent's skills folder).

name: agent-swarm-memory-manager
description: Agent skill for swarm-memory-manager - invoke with $agent-swarm-memory-manager

name: swarm-memory-manager description: Manages distributed memory across the hive mind, ensuring data consistency, persistence, and efficient retrieval through advanced caching and synchronization protocols color: blue priority: critical

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

javascript

// 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"
  })
}

// CREATE memory index for fast retrieval
mcp__claude-flow__memory_usage {
  action: "store",
  key: "swarm$shared$memory-index",
  namespace: "coordination",
  value: JSON.stringify({
    agents: {},
    shared_components: {},
    decision_history: [],
    knowledge_graph: {},
    last_indexed: Date.now()
  })
}

2. Cache Optimization

Implement multi-level caching (L1/L2/L3)
Predictive prefetching based on access patterns
LRU eviction for memory efficiency
Write-through to persistent storage

3. Synchronization Protocol

javascript

// SYNC memory across all agents
mcp__claude-flow__memory_usage {
  action: "store", 
  key: "swarm$shared$sync-manifest",
  namespace: "coordination",
  value: JSON.stringify({
    version: "1.0.0",
    checksum: "hash",
    agents_synced: ["agent1", "agent2"],
    conflicts_resolved: [],
    sync_timestamp: Date.now()
  })
}

// BROADCAST memory updates
mcp__claude-flow__memory_usage {
  action: "store",
  key: "swarm$broadcast$memory-update",
  namespace: "coordination", 
  value: JSON.stringify({
    update_type: "incremental|full",
    affected_keys: ["key1", "key2"],
    update_source: "memory-manager",
    propagation_required: true
  })
}

4. Conflict Resolution

Implement CRDT for conflict-free replication
Vector clocks for causality tracking
Last-write-wins with versioning
Consensus-based resolution for critical data

Memory Operations

Read Optimization

javascript

// BATCH read operations
const batchRead = async (keys) => {
  const results = {};
  for (const key of keys) {
    results[key] = await mcp__claude-flow__memory_usage {
      action: "retrieve",
      key: key,
      namespace: "coordination"
    };
  }
  // Cache results for other agents
  mcp__claude-flow__memory_usage {
    action: "store",
    key: "swarm$shared$cache",
    namespace: "coordination",
    value: JSON.stringify(results)
  };
  return results;
};

Write Coordination

javascript

// ATOMIC write with conflict detection
const atomicWrite = async (key, value) => {
  // Check for conflicts
  const current = await mcp__claude-flow__memory_usage {
    action: "retrieve",
    key: key,
    namespace: "coordination"
  };
  
  if (current.found && current.version !== expectedVersion) {
    // Resolve conflict
    value = resolveConflict(current.value, value);
  }
  
  // Write with versioning
  mcp__claude-flow__memory_usage {
    action: "store",
    key: key,
    namespace: "coordination",
    value: JSON.stringify({
      ...value,
      version: Date.now(),
      writer: "memory-manager"
    })
  };
};

Performance Metrics

EVERY 60 SECONDS write metrics:

javascript

mcp__claude-flow__memory_usage {
  action: "store",
  key: "swarm$memory-manager$metrics",
  namespace: "coordination",
  value: JSON.stringify({
    operations_per_second: 1000,
    cache_hit_rate: 0.85,
    sync_latency_ms: 50,
    memory_usage_mb: 256,
    active_connections: 12,
    timestamp: Date.now()
  })
}

Integration Points

Works With:

collective-intelligence-coordinator: For knowledge integration
All agents: For memory read$write operations
queen-coordinator: For priority memory allocation
neural-pattern-analyzer: For memory pattern optimization

Memory Patterns:

Write-ahead logging for durability
Snapshot + incremental for backup
Sharding for scalability
Replication for availability

Quality Standards

Do:

Write memory state every 30 seconds
Maintain 3x replication for critical data
Implement graceful degradation
Log all memory operations

Don't:

Allow memory leaks
Skip conflict resolution
Ignore sync failures
Exceed memory quotas

Recovery Procedures

Automatic checkpoint creation
Point-in-time recovery
Distributed backup coordination
Memory reconstruction from peers

Files

Just SKILL.md in .agents/skills/agent-swarm-memory-manager of ruvnet/ruflo.

Open the folder on GitHubat commit 58e0ae7

Used in 2 other repositories

We found 2 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 2 other GitHub owners. This page covers the copy in ruvnet/ruflo, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Agent Swarm Memory Manager next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Agent Swarm Memory Manager compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
Agent Swarm Memory Manager this skillruvnet/ruflo	74k	2 repos	~1.2k	Automated safety check: Pass	MIT	today
Orca CLIstablyai/orca	88k	2 repos	~593	Automated safety check: Pass	MIT	today
Paseo Advisor Second Opiniongetpaseo/paseo	20k	1 repos	~756	Automated safety check: Pass	Custom licence	today
O2 Review Loopopenobserve/openobserve	22k	—	~3.7k	Automated safety check: Pass	AGPL-3.0	today
Paseo Committeegetpaseo/paseo	20k	1 repos	~496	Automated safety check: Pass	Custom licence	today
Mission Control Agent APIbuilderz-labs/mission-control	6.3k	—	~2.1k	Automated safety check: Pass	MIT	11 days ago

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Questions about Agent Swarm Memory Manager

What does Agent Swarm Memory Manager do?

Agent skill for swarm-memory-manager - invoke with $agent-swarm-memory-manager. Agent Swarm Memory Manager is an agent skill from ruvnet/ruflo.

When should I use Agent Swarm Memory Manager?

Agent Swarm Memory Manager fits situations like: tasks that involve Multi-agent orchestration.

How do I install Agent Swarm Memory Manager in Claude Code?

Run `npx skills add ruvnet/ruflo --skill agent-swarm-memory-manager -a claude-code`. Or copy the skill folder (.agents/skills/agent-swarm-memory-manager in ruvnet/ruflo) into .claude/skills/agent-swarm-memory-manager in your project. Claude Code loads it when a task matches its description.

How do I install Agent Swarm Memory Manager in Codex?

Run `npx skills add ruvnet/ruflo --skill agent-swarm-memory-manager -a codex`. Or copy the skill folder (.agents/skills/agent-swarm-memory-manager in ruvnet/ruflo) into .agents/skills/agent-swarm-memory-manager in your project. Codex loads it when a task matches its description.

Can I use Agent Swarm Memory Manager in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add ruvnet/ruflo --skill agent-swarm-memory-manager -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/agent-swarm-memory-manager, .gemini/skills/agent-swarm-memory-manager, .github/skills/agent-swarm-memory-manager and .opencode/skills/agent-swarm-memory-manager in your project.

What does Agent Swarm Memory Manager need to run?

SKILL.md names no scripts, command-line tools or credentials: Agent Swarm Memory Manager is instructions for the agent only.

Does Agent Swarm Memory Manager access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Agent Swarm Memory Manager safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Agent Swarm Memory Manager use?

Agent Swarm Memory Manager is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Agent Swarm Memory Manager use?

About 1.2k tokens (SKILL.md is roughly 4.9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Agent Swarm Memory Manager?

Skills that share tags, products or a category with Agent Swarm Memory Manager: Orca CLI (stablyai/orca, 88k stars), Paseo Advisor Second Opinion (getpaseo/paseo, 20k stars), O2 Review Loop (openobserve/openobserve, 22k stars) and Paseo Committee (getpaseo/paseo, 20k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Agent Swarm Memory Manager?

ruvnet (a GitHub user) maintains it in ruvnet/ruflo, which has 74,159 GitHub stars. The repository holds 264 skills in this directory. The repository was last updated on October 9, 2026.

Source: ruvnet/ruflo on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install Agent Swarm Memory Manager

Facts

At a glance

What it does

When your agent uses it

Example prompts

Workflow steps

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

name: swarm-memory-manager description: Manages distributed memory across the hive mind, ensuring data consistency, persistence, and efficient retrieval through advanced caching and synchronization protocols color: blue priority: critical

Core Responsibilities

1. Distributed Memory Management

2. Cache Optimization

3. Synchronization Protocol

4. Conflict Resolution

Memory Operations

Read Optimization

Write Coordination

Performance Metrics

Integration Points

Works With:

Memory Patterns:

Quality Standards

Do:

Don't:

Recovery Procedures

Files

Used in 2 other repositories

Compare with similar skills

Similar skills

More from ruvnet/ruflo

Related

Questions about Agent Swarm Memory Manager