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Shared Memory for Multi-Agent OpenClaw

by junweiren98-rgb · GitHub ↗ · v1.1.0 · MIT-0
cross-platform ✓ Security Clean
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Install in OpenClaw
/install multi-agent-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...
README (SKILL.md)

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/
│   ├── \x3Cagent-a-id>-latest.md
│   └── \x3Cagent-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 - \x3CAgent A Name> & \x3CAgent 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)

- \x3Cemoji> \x3Cname> — \x3Crole>
- \x3Cemoji> \x3Cname> — \x3Crole>

Each sync file — Initialize with:

# \x3CAgent Name> 最近对话摘要

> 由 \x3CAgent 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 "\x3Cother-workspace>\shared-knowledge" -Target "\x3Chost-workspace>\shared-knowledge"

macOS/Linux:

ln -s \x3Chost-workspace>/shared-knowledge \x3Cother-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 \x3COther Agent Name>)

你有个搭档叫 **\x3COther 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/\x3Cother-agent-id>-latest.md` — \x3COther Agent Name> 最近聊了什么
- `sync/\x3Cmy-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/\x3Cother-agent-id>-latest.md`
2. **每次对话结束**:更新 `sync/\x3Cmy-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/\x3Cother-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:

Trigger Action
Session start Read SHARED-MEMORY.md + all other agents' sync files
Session end Update own sync file with conversation highlights
Important new info Update 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/\x3Cnew-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
Usage Guidance
This skill is coherent but will read and modify your agent workspace files and create a shared directory accessible to multiple agents. Before installing/using: 1) Back up each workspace (AGENTS.md, SOUL.md, memory files). 2) Confirm exact workspace paths and which workspace will host the shared directory. 3) Review the exact text that will be appended to AGENTS.md and approve changes (the skill will edit those files). 4) Do not place credentials, tokens, or other secrets into shared-knowledge; the protocol explicitly forbids it, but the enforcement is manual. 5) On Windows, symlink creation may require admin rights; test on a non-critical workspace first. 6) If you want tighter control, require explicit confirmation before each write/modify step rather than fully automatic operation.
Capability Analysis
Type: OpenClaw Skill Name: multi-agent-shared-memory Version: 1.1.0 The skill implements a shared memory system for multiple OpenClaw agents by creating a centralized directory and using symbolic links to sync data across workspaces. It automates the setup of a 'shared-knowledge' folder and modifies agent configuration files (AGENTS.md) to establish a synchronization protocol. While it utilizes shell commands for symlinking (ln -s / New-Item) and modifies agent instructions, these actions are transparently aligned with the stated goal of multi-agent coordination and lack any indicators of malicious intent or data exfiltration.
Capability Assessment
Purpose & Capability
The name/description match the instructions: the skill only needs filesystem access to create a shared directory, per-workspace symlinks, and update AGENTS.md files. It does not request unrelated credentials, binaries, or installs, which is appropriate for the stated goal.
Instruction Scope
The SKILL.md instructs the agent to perform filesystem operations (create directories, write README/SHARED-MEMORY.md, create symlinks, and append protocol blocks to each AGENTS.md). That is coherent with the goal, but the directive to “Do everything automatically — only ask the user for information you cannot determine yourself” grants broad discretion to read and modify files in multiple workspaces; this can expose personal data or unintentionally change agent configuration. The skill does not instruct contacting external endpoints.
Install Mechanism
Instruction-only skill with no install steps, packages, or downloads. Lowest install risk — nothing is written to disk by an installer beyond the files the agent is instructed to create/modify at runtime.
Credentials
No environment variables, credentials, or external tokens are requested. The only resources accessed are user workspace directories and files, which is proportionate to the purpose. However, the shared memory will store user info and summaries; ensure sensitive data/credentials are not placed there.
Persistence & Privilege
always is false and the skill does not request persistent agent-level privileges. It does instruct modifying other agents' AGENTS.md files and creating cross-workspace symlinks, which is functionally necessary but means it will alter per-agent configuration files — users should expect and approve those changes.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install multi-agent-shared-memory
  3. After installation, invoke the skill by name or use /multi-agent-shared-memory
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.1.0
v1.1.0: Redesigned as agent-executable skill. Agent does all setup automatically - user just says 'set up shared memory'. Removed manual templates. Added prerequisites guide, symlink setup, verification steps, and 3+ agent scaling instructions.
v1.0.0
Initial release: shared memory protocol for multi-agent OpenClaw setups. Includes templates, sync protocol, and AGENTS.md snippet.
Metadata
Slug multi-agent-shared-memory
Version 1.1.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 2
Frequently Asked Questions

What is Shared Memory for Multi-Agent OpenClaw?

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... It is an AI Agent Skill for Claude Code / OpenClaw, with 263 downloads so far.

How do I install Shared Memory for Multi-Agent OpenClaw?

Run "/install multi-agent-shared-memory" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Shared Memory for Multi-Agent OpenClaw free?

Yes, Shared Memory for Multi-Agent OpenClaw is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Shared Memory for Multi-Agent OpenClaw support?

Shared Memory for Multi-Agent OpenClaw is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Shared Memory for Multi-Agent OpenClaw?

It is built and maintained by junweiren98-rgb (@junweiren98-rgb); the current version is v1.1.0.

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