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Mnemos Memory

作者 anthony-maio · GitHub ↗ · v0.6.0 · MIT-0
cross-platform ✓ 安全检测通过
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当前安装
2
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在 OpenClaw 中安装
/install mnemos-memory
功能描述
Use when users or OpenClaw/ClawHub agents need to install, configure, self-bootstrap, troubleshoot, or operate Mnemos for persistent scoped agent memory, or...
使用说明 (SKILL.md)

Mnemos Memory

Mnemos is a local-first memory layer for coding agents. Use this skill to guide users or OpenClaw agents onto the supported install path, explain the operating loop, and keep compatibility claims accurate.

Default path

  • Prefer pip install "mnemos-memory[mcp]" and mnemos ui.
  • For OpenClaw / ClawHub, teach the agent to self-install mnemos-memory[mcp], run mnemos ui, then wire mnemos-mcp to the canonical MNEMOS_CONFIG_PATH before relying on memory.
  • Recommend SQLite as the supported persistent store.
  • Recommend a real embedding provider (openclaw, openai, openrouter, or ollama) for production retrieval quality.
  • Validate setup with the control-plane smoke check or mnemos-cli doctor.

Claim discipline

  • Safe to claim: local-first scoped memory, MCP tools, SQLite starter profile, Claude Code plugin flow, documented Codex flow.
  • Be explicit that deterministic auto-memory is shipped for Claude Code via hooks.
  • For Codex, Cursor, OpenClaw, and generic MCP hosts, do not imply automatic capture unless the host has its own automation or the user adds one.
  • Do not present removed legacy backends as available runtime options.

Workflow

  1. Identify the host: Claude Code, Cursor, Codex, OpenClaw, or generic MCP.
  2. If the repo is available locally, read README.md, docs/MCP_INTEGRATION.md, and docs/codex.md before answering.
  3. Give the default install path first. Only fall back to manual config snippets if the user cannot use the control plane.
  4. Explain the operating loop:
    • mnemos_retrieve at task start
    • mnemos_store for durable facts only
    • mnemos_consolidate before finishing substantial work
    • mnemos_inspect when a stored fact looks wrong
  5. Read references/hosts.md for host-specific config snippets and caveats, especially the OpenClaw / ClawHub self-install flow when the agent must bootstrap itself.
  6. Read references/operations.md for automation, capture-mode, storage guidance, and troubleshooting.

Avoid

  • Do not tell users to manually type memories as the primary workflow.
  • Do not recommend SimpleEmbeddingProvider for production retrieval quality.
  • Do not suggest external storage backends for Mnemos. Keep users on the SQLite path.
安全使用建议
This skill is an instructional guide for installing and operating Mnemos and appears coherent with that purpose. Before using it, consider: (1) only allow the agent to self-install if you trust the package source—verify the mnemos-memory package on PyPI/GitHub and the exact version; (2) run installations inside a virtualenv or container to limit system impact; (3) be prepared that MNEMOS_CONFIG_PATH and a SQLite DB will be created/used—check filesystem permissions and back up any important data; (4) embedding providers mentioned require separate API keys—only supply those when you intend production embedding and store them securely; (5) if you do not want an agent to modify your environment autonomously, disable or restrict the skill's model invocation or require explicit user approval before running install commands; (6) after install, run mnemos-cli doctor and inspect installed files to confirm behavior.
功能分析
Type: OpenClaw Skill Name: mnemos-memory Version: 0.6.0 The mnemos-memory skill bundle provides legitimate instructions and configuration for integrating Mnemos, a local-first memory layer, into AI agents. While it encourages the agent to self-bootstrap via 'pip install', this behavior is transparently documented and aligned with the stated purpose of enabling persistent memory. No indicators of data exfiltration, malicious execution, or unauthorized persistence were found across SKILL.md or the reference files.
能力评估
✓ Purpose & Capability
The name/description match the instructions: the skill is an installation/operations guide for Mnemos. It does not request extraneous credentials, binaries, or config paths beyond what is reasonable for a memory/MCP integration.
ℹ Instruction Scope
SKILL.md tells the agent to prefer pip install, run mnemos ui, wire mnemos-mcp to MNEMOS_CONFIG_PATH, and to read repository docs (README.md, docs/MCP_INTEGRATION.md, docs/codex.md) and the included references. These actions are appropriate for an install/ops guide, but they do authorize an agent to perform system actions (install packages, write config files, read repo docs). Users should be aware the agent may run commands that modify the environment when following these instructions.
✓ Install Mechanism
There is no install spec in the registry bundle (instruction-only). The SKILL.md recommends using pip (a standard mechanism). No embedded download URLs or extract/install steps from arbitrary hosts are present in the skill content itself.
ℹ Credentials
The skill itself does not declare required environment variables or credentials. It does reference MNEMOS_CONFIG_PATH (a canonical config environment variable) and recommends using production embedding providers (openclaw, openai, openrouter, ollama) which would require API keys in practice. This is proportionate but means the user/agent will need to supply unrelated provider credentials to achieve production-grade retrieval; those credentials are not requested by the skill directly.
ℹ Persistence & Privilege
always:false (no forced global installation). However, the guidance explicitly instructs agents on self-install and wiring a config path, which will create files (pip packages, config in MNEMOS_CONFIG_PATH, SQLite DB). That behavior is expected for an install/ops skill but is a material system change the user should consent to.
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 mnemos-memory
  3. 安装完成后，直接呼叫该 Skill 的名称或使用 /mnemos-memory 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
v0.6.0
Align the skill to the SQLite-only 0.6.0 release and recall-gated plasticity guidance.
v0.3.0
Added the Mnemos 0.3.0 beta onboarding skill for OpenClaw agents, covering install, self-setup, and daily Mnemos use through MCP. This update also reflects the new Codex and Cursor soft-auto workflows, shared Neo4j-backed persistence guidance, and clearer host compatibility positioning so agents know what is automated today and what still depends on host-specific hooks or rules.
元数据
Slug mnemos-memory
版本 0.6.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 2
常见问题

Mnemos Memory 是什么？

Use when users or OpenClaw/ClawHub agents need to install, configure, self-bootstrap, troubleshoot, or operate Mnemos for persistent scoped agent memory, or... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 262 次。

如何安装 Mnemos Memory？

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

Mnemos Memory 是免费的吗？

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

Mnemos Memory 支持哪些平台？

Mnemos 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 Mnemos Memory？

由 anthony-maio（@anthony-maio）开发并维护，当前版本 v0.6.0。

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