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amd5

Team Shared Memory

by c32 · GitHub ↗ · v1.0.1 · MIT-0
cross-platform ✓ Security Clean
90
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0
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0
Active Installs
2
Versions
Install in OpenClaw
/install team-shared-memory
Description
多实例记忆共享,多个 Agent 之间同步记忆
Usage Guidance
This skill appears to do what it claims: local syncing of markdown 'memory' files and local secret scanning. Before installing or running it, review and be comfortable with these points: (1) the scripts operate on your filesystem under $HOME/.openclaw/workspace and will read/write files there—ensure you trust the author and that the workspace path is appropriate; (2) secret-scan can be pointed at any directory and will read many file types to detect sensitive tokens—do not run it against system or root-owned directories with elevated privileges unless you intend to; (3) there is no network communication in the included code, so it does not exfiltrate secrets, but you should still inspect and run the scripts in a safe environment first; (4) verify Node.js >=18 and run with least privilege; and (5) the package author is unknown—if you need higher assurance, ask for provenance or a code-signing/source repo before enabling automated runs.
Capability Analysis
Type: OpenClaw Skill Name: team-shared-memory Version: 1.0.1 The skill bundle provides a local memory synchronization mechanism and a security scanner to prevent sensitive data leakage. The scripts (sync.js and secret-scan.js) operate strictly within the user's local workspace (~/.openclaw/workspace), performing file copying and regex-based secret detection without any network activity, external exfiltration, or unauthorized execution logic.
Capability Tags
cryptorequires-walletrequires-oauth-token
Capability Assessment
Purpose & Capability
Name/description (team/shared memory) match the included scripts: sync.js performs local copy/sync of markdown memories under ~/.openclaw/workspace and secret-scan.js looks for common secret patterns. No credentials, external services, or unrelated binaries are required.
Instruction Scope
SKILL.md and scripts limit actions to local filesystem operations (reading/writing under HOME/.openclaw/workspace and scanning user-supplied paths). The secret scanner can be invoked against arbitrary directories (--dir) and will read many text file types—this is expected for a scanner but means it can examine any files you point it at.
Install Mechanism
There is no install spec or remote download; the skill is instruction-only with two included Node.js scripts. Requirement is node >=18. No archives or external installers are fetched.
Credentials
The scripts implicitly use process.env.HOME to locate the workspace, which is proportional to a local-sync tool. The skill requests no environment secrets or config paths. Users should note the implicit reliance on the HOME path and file permissions.
Persistence & Privilege
The skill does not request always:true and does not attempt to modify other skills or global agent configs. It writes state and lock files only under ~/.openclaw/workspace/memory/team, which is consistent with its sync purpose.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install team-shared-memory
  3. After installation, invoke the skill by name or use /team-shared-memory
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.1
团队记忆同步服务,作者改为c32
v1.0.0
多实例记忆共享,多个 Agent 之间同步记忆
Metadata
Slug team-shared-memory
Version 1.0.1
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 2
Frequently Asked Questions

What is Team Shared Memory?

多实例记忆共享,多个 Agent 之间同步记忆. It is an AI Agent Skill for Claude Code / OpenClaw, with 90 downloads so far.

How do I install Team Shared Memory?

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

Is Team Shared Memory free?

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

Which platforms does Team Shared Memory support?

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

Who created Team Shared Memory?

It is built and maintained by c32 (@amd5); the current version is v1.0.1.

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