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shared-memory-governor

作者 jiy29104983 · GitHub ↗ · v1.0.2 · MIT-0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install shared-memory-governor
功能描述
Govern a file-based shared-memory layer for OpenClaw multi-agent and subagent systems. Preserve each agent’s private memory while adding a separate, reviewab...
安全使用建议
This is an instruction-only governance skill (no code, no installs, no credentials requested) and appears coherent with its purpose. Before enabling it in your workspace: 1) confirm the intended sharedRoot path — the reference defaults to /root/.openclaw/shared-memory, so change it if your workspace is elsewhere; 2) review schedule settings in the example config (privateMaintenance is enabled in the example) and disable any recurring tasks you do not want running; 3) ensure local SHARED_ATTACH.md and AGENTS.md guidance are accurate for each agent so the read/attach rules are enforced; and 4) remember this is documentation for operator behavior — the safety guarantees rely on the agent implementation following these rules, so audit any runtime that will implement these steps if you need stronger enforcement (e.g., code-level guards or OS permissions).
功能分析
Type: OpenClaw Skill Name: shared-memory-governor Version: 1.0.2 The 'shared-memory-governor' skill is a governance framework designed to manage shared data layers across multiple AI agents within the OpenClaw environment. The skill's logic, defined across SKILL.md and several reference documents, focuses on maintaining strict identity isolation and preventing the accidental promotion of private data or secrets into shared space. It includes explicit safety boundaries that forbid reading credentials, SSH keys, or browser data. While it performs file modifications (e.g., updating AGENTS.md for startup guidance) and manages task schedules for maintenance, these actions are transparently documented and strictly scoped to the stated purpose of memory management, with no evidence of malicious intent, data exfiltration, or harmful prompt injection.
能力评估
Purpose & Capability
Name/description match the content: all files are configuration and governance references for a file-based shared-memory layer. The skill does not request unrelated credentials, binaries, or external services that would be inconsistent with a local shared-file governance tool.
Instruction Scope
SKILL.md and references clearly constrain behavior (operate only inside user-designated workspace paths; never read credentials/secrets; keep shared memory supplemental). The only notable point is that the documented default config path resolves to /root/.openclaw/shared-memory/shared-memory.config.json (explicit in config-reference.md), so users should confirm that the default location matches their intended workspace; otherwise, commands may operate on the workspace under that path. Overall the instructions are specific and scoped to the stated purpose.
Install Mechanism
Instruction-only skill with no install spec, no binaries, and no archives to download. This is the lowest-risk install profile and is proportional to the described governance role.
Credentials
No environment variables, no credentials, and no required config paths beyond the documented workspace-shared path. The included example config explicitly disables shared recurring schedules by default (sharedScan/sharedMaintenance false) and sets sharing flags to disallow secrets and assistant identity; these align with the stated privacy-first goals.
Persistence & Privilege
Skill does not request always:true and does not claim autonomous persistent background execution. Example config contains schedule entries (privateMaintenance enabled, shared schedules disabled) — schedule activation would be a local config choice and is documented; the skill itself does not install persistent agents or services.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install shared-memory-governor
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /shared-memory-governor 触发
  4. 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
v1.0.2
Change default shared-memory path semantics to workspace-parent sibling and update config docs/example.
v1.0.1
Refined skill structure, clarified safety boundaries, reduced high-risk wording, renamed references, and aligned default config examples.
v0.1.0
Initial publish: shared memory governance workflow, attach/detach rules, and reference docs.
元数据
Slug shared-memory-governor
版本 1.0.2
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 3
常见问题

shared-memory-governor 是什么?

Govern a file-based shared-memory layer for OpenClaw multi-agent and subagent systems. Preserve each agent’s private memory while adding a separate, reviewab... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 279 次。

如何安装 shared-memory-governor?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install shared-memory-governor」即可一键安装,无需额外配置。

shared-memory-governor 是免费的吗?

是的,shared-memory-governor 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

shared-memory-governor 支持哪些平台?

shared-memory-governor 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 shared-memory-governor?

由 jiy29104983(@jiy29104983)开发并维护,当前版本 v1.0.2。

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