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Multi Agent Memory
作者
brucey0017-cloud
· GitHub ↗
· v0.1.0
· MIT-0
342
总下载
0
收藏
1
当前安装
1
版本数
在 OpenClaw 中安装
/install multi-agent-memory
功能描述
多 agent 共享记忆与项目协作架构。支持项目状态隔离、知识库共享、跨项目搜索、版本控制、里程碑跟踪、周报和交接文档。适用于多个 agent 协作开发多个项目的场景。
安全使用建议
This skill appears to be a local project/knowledge-file manager (no network exfiltration in the scripts), but it will read and write many files under /root/.openclaw and ~/workspace-<agent> even though the registry metadata does not declare those config paths. Before installing or enabling it: 1) Review the templates directory and scripts (they are plain shell) to ensure no sensitive data will be overwritten. 2) Run the skill in an isolated or non-root environment first (do not give it access to your real /root or production data). 3) If you expect to keep secrets elsewhere, confirm the skill won't read those paths. 4) Note the SKILL.md has small inaccuracies (uses 'read' where 'cat' would be expected) — test the scripts manually. 5) If you need tighter control, ask the author to declare the required config paths in the manifest and to limit file access to a configurable working directory.
功能分析
Type: OpenClaw Skill
Name: multi-agent-memory
Version: 0.1.0
The skill bundle provides a structured framework for multi-agent collaboration and project memory management. It uses shell scripts (e.g., init-project.sh, daily-check.sh) and markdown templates to automate project initialization, status tracking, and reporting within the /root/.openclaw/ directory. The logic is consistent with its stated purpose, and there is no evidence of data exfiltration, unauthorized network access, or malicious prompt injection.
能力评估
Purpose & Capability
Name/description (multi-agent memory and collaboration) aligns with the included scripts and templates. However, the skill's metadata declares no required config paths or environment variables, while the SKILL.md and scripts clearly expect and manipulate a specific on-disk layout under /root/.openclaw and ~/workspace-<agent> (creating projects, archiving, updating symlinks). The missing declaration of those required paths is an incoherence that affects permission/consent decisions.
Instruction Scope
SKILL.md instructs agents to read and write many local files (context.md, todos.md, status/*.md, knowledge/, archives), run grep/stat/tar/cp/ln/sed and to call the included shell scripts. All operations are local (no external network endpoints), but they give the skill broad read/write scope over the user's ~/.openclaw and project workspaces. The SKILL.md uses commands like 'read /root/.openclaw/...' (which is ambiguous — likely intended cat) and otherwise assumes full access to those paths; that open-ended file access is a security and privacy concern if you don't expect the skill to manage your entire agent workspace.
Install Mechanism
There is no install spec; the package is instruction/script-only plus a package.json. No remote downloads, no extracted archives, and the included scripts are plain shell — low installation risk. The package.json references a GitHub repo, but there is no automated installer pulling code from external URLs.
Credentials
The skill declares no required environment variables or config paths, yet the runtime instructions and scripts expect to read/write specific filesystem locations (e.g., /root/.openclaw/projects, ~/workspace-<agent>/current-project.txt). That disparity means the skill will access local data that was not advertised in its manifests. It does not request credentials or network tokens, and it does not contact external endpoints in the provided code.
Persistence & Privilege
always is false and the skill does not request to be force-enabled. Its behavior is limited to creating and modifying files/directories under the skill/homework tree (~/.openclaw) and project folders; it does not modify other skills' configurations or system-wide agent settings. That level of local persistence is expected for a file-oriented collaboration skill, but should still be consented to explicitly by the user.
如何使用
- 确保已安装 OpenClaw(本地或 Docker 部署)
- 在对话框中输入安装命令:
/install multi-agent-memory - 安装完成后,直接呼叫该 Skill 的名称或使用
/multi-agent-memory触发 - 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v0.1.0
multi-agent-memory 1.0.0
- Initial release introducing a framework for multi-agent shared memory and project collaboration.
- Supports project state isolation, shared cross-project knowledge bases, and cross-project search.
- Includes features for version control (retaining latest 3 file versions), milestone tracking (SMART & RACI), structured weekly reports, and handover documents.
- Provides detailed folder structure and workflow guidelines for daily, weekly, and milestone-based collaboration.
- Designed for scenarios involving multiple agents collaborating on multiple projects.
元数据
常见问题
Multi Agent Memory 是什么?
多 agent 共享记忆与项目协作架构。支持项目状态隔离、知识库共享、跨项目搜索、版本控制、里程碑跟踪、周报和交接文档。适用于多个 agent 协作开发多个项目的场景。 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 342 次。
如何安装 Multi Agent Memory?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install multi-agent-memory」即可一键安装,无需额外配置。
Multi Agent Memory 是免费的吗?
是的,Multi Agent Memory 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。
Multi Agent Memory 支持哪些平台?
Multi Agent Memory 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。
谁开发了 Multi Agent Memory?
由 brucey0017-cloud(@brucey0017-cloud)开发并维护,当前版本 v0.1.0。
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