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xmemo

XMemo

作者 XMemo · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ 安全检测通过
24
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1
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0
当前安装
1
版本数
在 OpenClaw 中安装
/install xmemo
功能描述
Persistent, user-owned memory for AI agents over hosted MCP. Remember decisions, recall project context, manage TODOs, and govern memory lifecycle across ses...
使用说明 (SKILL.md)

\r \r

XMemo Memory\r

\r Give your agent durable memory that survives across sessions, projects, and tools. XMemo is a hosted MCP memory service — no local database, no self-hosting required.\r \r

When to use\r

\r

  • The task depends on prior decisions, preferences, or project context.\r
  • The user asks to remember something for later.\r
  • You need to recall conventions, architecture notes, or past fixes before acting.\r
  • The user wants TODOs, reminders, or follow-ups tracked across sessions.\r \r

Workflow\r

\r

  1. Recall before assuming. Search or recall XMemo context before making decisions that prior memory could inform.\r
  2. Save what matters. Store durable facts: decisions, conventions, preferences, architecture notes, action items. Skip transient chat.\r
  3. Keep it concise. One clear memory per concept. Prefer structured facts over verbose narratives.\r
  4. Confirm before destroying. Always confirm the exact target before delete, forget, or overwrite operations.\r
  5. On auth failure, tell the user: "Visit https://xmemo.dev to sign in and get your token, or run xmemo login if the CLI is installed. Set XMEMO_KEY environment variable." Never request raw tokens in chat.\r \r

Available tools\r

\r Core memory operations provided by the XMemo MCP server:\r \r | Tool | Purpose |\r |------|---------|\r | remember | Save a new memory |\r | recall / recall_context | Retrieve relevant memories before answering |\r | search_memory | Search by query |\r | update_memory | Revise existing memory |\r | forget / forget_memory | Delete a memory |\r | redact_memory | Remove sensitive content while keeping audit trail |\r | explain_memory | Show why a memory exists or matched |\r | create_memory_todo | Create a follow-up task |\r | list_memory_todos | List pending TODOs |\r | complete_memory_todo | Mark a TODO done |\r | record_event | Log a milestone or decision |\r | get_timeline | Show recent events |\r | add_expense | Record a ledger entry |\r \r

Good memory candidates\r

\r

  • Repository conventions, build/test/deploy commands.\r
  • Architecture decisions and their rationale.\r
  • Coding style preferences approved by the user.\r
  • Release procedures and deployment notes.\r
  • TODOs and follow-ups for future sessions.\r
  • Bug fix context that might recur.\r \r

Never save\r

\r

  • Secrets, tokens, API keys, OAuth codes, cookies.\r
  • Private customer data or sensitive PII.\r
  • Temporary debugging output.\r
  • Large code blocks (link to files instead).\r
安全使用建议
Install only if you intend to let the agent help with Convex and ClawHub maintainer workflows. Review the moderation and autoreview commands before running them, use --no-yolo for autoreview when you do not want a nested reviewer to have full local access, and avoid sending sensitive uncommitted diffs to fallback review CLIs.
能力标签
requires-oauth-tokenrequires-sensitive-credentials
能力评估
Purpose & Capability
The artifacts provide Convex setup, auth, migration, performance, ClawHub moderation, PR-maintainer, UI-proof, and autoreview workflows that match their stated purposes.
Instruction Scope
Some workflows can perform high-impact actions, including moderation commands, PR comments, publishing UI proof, and code review through external CLIs, but the instructions include explicit target, confirmation, auth, audit-log, and verification requirements where appropriate.
Install Mechanism
No installer or startup hook was found; files are static skill instructions plus one helper script for autoreview.
Credentials
The autoreview helper discloses that nested Codex review runs with full sandbox bypass by default and offers --no-yolo/AUTOREVIEW_YOLO=0 to opt out; this is broad for review work but not hidden or automatically triggered.
Persistence & Privilege
No background persistence, credential harvesting, profile modification, or automatic privilege escalation was found; temporary files are cleaned and optional output is user-selected.
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 xmemo
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /xmemo 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
v1.0.0
- Initial release of xmemo-memory. - Provides persistent, user-owned memory for AI agents via the hosted XMemo MCP service. - Supports durable storage and retrieval of decisions, project context, TODOs, and architecture notes. - Includes a suite of core memory management tools: save, recall, search, update, forget, redact, and explain memories, as well as TODO and event tracking. - Guides on what to remember, what not to store, and privacy best practices. - Requires authentication via OAuth or XMEMO_KEY environment variable.
元数据
Slug xmemo
版本 1.0.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
常见问题

XMemo 是什么?

Persistent, user-owned memory for AI agents over hosted MCP. Remember decisions, recall project context, manage TODOs, and govern memory lifecycle across ses... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 24 次。

如何安装 XMemo?

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

XMemo 是免费的吗?

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

XMemo 支持哪些平台?

XMemo 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 XMemo?

由 XMemo(@xmemo)开发并维护,当前版本 v1.0.0。

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