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multi-agent-shared-memory多 Agent 共享内存

Agent Skill

multi-agent-shared-memory 用于补充效率相关能力,适合在 OpenClaw 中需要让 Agent 承接效率相关任务时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

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OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:multi-agent-shared-memory(多 Agent 共享内存)
来源仓库:https://github.com/junweiren98-rgb/multi-agent-shared-memory
安装命令:
openclaw skills install multi-agent-shared-memory
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install multi-agent-shared-memory

简介

在多个 OpenClaw 代理间建立共享内存,保持上下文同步无需重复输入。

  • 适用于多工作区协作且需共享知识库或中间结果的场景。
  • 减少冗余通信开销,提升协作流畅度。
  • 安装命令为 openclaw skills install multi-agent-shared-memory,建议使用持久化存储后端。
  • 使用前应设置读写锁与版本控制,防止并发修改导致数据错乱。

SKILL.md

name
shared-memory
description
Set up shared memory between multiple OpenClaw agents so they stay in sync without the user repeating context. Use when a user has 2+ agents (workspaces) and wants them to share knowledge, sync conversation summaries, and maintain a common long-term memory. Also use when user asks about multi-agent setup, agent sync, or says things like "stop repeating myself to different agents".

Shared Memory for Multi-Agent OpenClaw

What This Solves

When a user runs multiple OpenClaw agents, each agent has no idea what the other discussed with the user. The user becomes a "messenger" repeating the same context. This skill sets up automatic knowledge sharing between agents.

Prerequisites

The user needs 2+ OpenClaw agent workspaces. If they only have one agent, explain:

要用共享记忆,你需要至少两个 Agent(两个 workspace)。在 OpenClaw 里,每个 Agent 是一个独立的 workspace 目录,有自己的 AGENTS.md、SOUL.md 和记忆文件。你可以通过 openclaw 配置多个 workspace,每个绑定不同的身份和职责。

If the user is unsure how to set up multiple agents, help them understand the concept first before proceeding.

Setup Procedure

When the user asks to set up shared memory, follow these steps. Do everything automatically — only ask the user for information you cannot determine yourself.

Step 1: Gather info (ask the user)

Ask these questions in one message:

  1. How many agents do you have, and what are their names/emoji? (e.g. 小爪🦞, 小澜🌊)
  2. Where are their workspace directories? (e.g. ~/.openclaw/workspace, ~/.openclaw/workspace-sister)
  3. Which workspace should host the shared directory? (recommend the primary/main agent's workspace)

Step 2: Create the shared directory structure

In the host workspace, create:

shared-knowledge/
├── SHARED-MEMORY.md
├── README.md
├── sync/
│   ├── <agent-a-id>-latest.md
│   └── <agent-b-id>-latest.md
└── projects/

Use short lowercase IDs for sync filenames (e.g. xiaozhua, xiaolan).

SHARED-MEMORY.md — Initialize with the user's basic info if you know it, otherwise create a skeleton:

# SHARED-MEMORY.md - <Agent A Name> & <Agent B Name> 共享记忆

> 所有参与 Agent 的公共知识库,双方都可以读写。
> 私人人格、独立记忆不放这里,只放大家都需要知道的信息。

---

## 用户基本信息

(fill in what you know)

## 工作上下文

(fill in what you know)

## 重要决定

(leave empty for now)

## 家庭成员(AI Agent)

- <emoji> <name> — <role>
- <emoji> <name> — <role>

Each sync file — Initialize with:

# <Agent Name> 最近对话摘要

> 由 <Agent Name> 自动更新,供其他 Agent 了解最新上下文

(暂无记录)

README.md — Write a brief usage guide covering: directory structure, what goes here / what doesn't, sync protocol.

Step 3: Link the shared directory to other workspaces

For each non-host workspace, create a symlink so all agents access the same physical directory:

Windows (PowerShell, run as admin):

New-Item -ItemType SymbolicLink -Path "<other-workspace>\shared-knowledge" -Target "<host-workspace>\shared-knowledge"

macOS/Linux:

ln -s <host-workspace>/shared-knowledge <other-workspace>/shared-knowledge

Verify the symlink works by reading a file through it.

Step 4: Update each agent's AGENTS.md

Append the shared memory protocol block to each agent's AGENTS.md. Customize the names and paths for each agent's perspective.

The block to add (customize per agent):

## 🤝 共享记忆协议(和 <Other Agent Name>)

你有个搭档叫 **<Other Agent Name>**,是用户的另一个 AI 助手。你们共享一个知识库,避免用户重复描述同样的事情。

### 目录:`shared-knowledge/`
- `SHARED-MEMORY.md` — 共享长期记忆(用户信息、项目、决策)
- `sync/<other-agent-id>-latest.md` — <Other Agent Name> 最近聊了什么
- `sync/<my-agent-id>-latest.md` — **你负责更新这个文件**
- `projects/` — 项目相关共享文档

### 你需要做的:
1. **每次对话开始**:读 `shared-knowledge/SHARED-MEMORY.md` 和 `sync/<other-agent-id>-latest.md`
2. **每次对话结束**:更新 `sync/<my-agent-id>-latest.md`(写你和用户聊了什么要点)
3. **有重要新信息时**:更新 `SHARED-MEMORY.md`(新的决策、项目进展等)

### 边界:
- ✅ 共享:工作上下文、项目进展、用户的偏好和决策、对话摘要
- ❌ 不共享:你的 SOUL.md、IDENTITY.md、私人想法和人格设定

Also add to the "Every Session" checklist in AGENTS.md:

- **读共享记忆**:Read `shared-knowledge/SHARED-MEMORY.md`
- **读搭档动态**:Read `shared-knowledge/sync/<other-agent-id>-latest.md`

Step 5: Verify

  1. Read a file from shared-knowledge/ in each workspace to confirm access works
  2. Write a test line to one agent's sync file
  3. Read it from the other workspace to confirm the symlink is working
  4. Remove the test line

Step 6: Tell the user it's done

Summarize what was set up and explain the behavior they should expect:

设置完成!从现在开始: - 每次我们聊完,我会自动更新我的同步文件 - 下次你的另一个 Agent 上线时,它会先读我写的摘要,自动了解我们聊了什么 - 重要决定会同步到共享记忆里,所有 Agent 都能看到 - 你不用再重复告诉每个 Agent 同样的事情了

Protocol Rules (for the agent using this skill)

After setup is complete, follow these rules in every session:

TriggerAction
Session startRead SHARED-MEMORY.md + all other agents' sync files
Session endUpdate own sync file with conversation highlights
Important new infoUpdate SHARED-MEMORY.md

What goes in shared memory

  • ✅ User info, preferences, decisions
  • ✅ Project context and progress
  • ✅ Conversation summaries
  • ✅ Shared reference documents

What stays private

  • ❌ Agent personality (SOUL.md, IDENTITY.md)
  • ❌ Private memories and persona settings
  • ❌ Credentials, tokens, passwords

Scaling to 3+ Agents

For each additional agent:

  1. Add a sync file: sync/<new-agent-id>-latest.md
  2. Symlink shared-knowledge/ into the new workspace
  3. Add the protocol block to the new agent's AGENTS.md (listing ALL other agents)
  4. Update existing agents' AGENTS.md to also read the new agent's sync file

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

93.19%
按下载量换算2,444

安全审计

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权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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