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Agent Skill · 研究检索

openclaw-structured-memory(OpenClaw structured 记忆)

openclaw-structured-memory 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

openclaw-structured-memory 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为接触敏感数据;许可证为 MIT-0,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 4,526。

总安装 31,728周安装 1,349GitHub Stars 4下载 11,116核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
2.0.2

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:openclaw-structured-memory(OpenClaw structured 记忆)
来源仓库:https://github.com/singhcoder/openclaw-structured-memory
安装命令:
openclaw skills install openclaw-structured-memory
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install openclaw-structured-memory

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

openclaw-structured-memory 提供结构化持久内存管理能力。支持文档、任务、联系人等多类型数据存储与检索。通过 clawhub 安装,使用 openclaw skills install 命令部署。安装前需确认权限范围、维护状态及是否触发数据库或文件操作。

适用宿主包括 OpenClaw,接入前应确认版本、权限和运行环境要求。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install openclaw-structured-memory;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要接触敏感数据,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

openclaw-structured-memory 怎么安装?

在终端执行 openclaw skills install openclaw-structured-memory。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

openclaw-structured-memory 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

openclaw-structured-memory 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

openclaw-structured-memory 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

openclaw-structured-memory 用的人多吗?

公开数据是累计安装 31,728 次,近一周安装 1,349 次,下载 11,116 次,GitHub 4 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

openclaw-structured-memory 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
openclaw-structured-memory

OpenClaw structured 记忆 · 本页

31,7284接触敏感数据MIT-0通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
qordinate-structured-memory
description
|
compatibility
Requires MCP client support (Streamable HTTP transport)
metadata
author
qordinate
version
0.3
openclaw
requires
env
bins
primaryEnv
QORDINATE_API_KEY

Qordinate - AI-Native Memory & Productivity for OpenClaw Agents

Qordinate is an AI agent platform that becomes durable, structured memory and productivity infrastructure for your users and agents.

Instead of your OpenClaw agent trying to keep all state in its own scratchpad or a custom DB, it can connect to Qordinate via MCP (Model Context Protocol) and use the Qordinate AI agent to:

  • Store and retrieve documents (notes, files, PDFs)
  • Manage contacts (people, companies, leads)
  • Maintain lists and tasks with statuses, due dates, and reminders
  • Search the web for up-to-date information
  • Interact with connected apps the user has linked to Qordinate
  • Create and manage forms and collect submissions
  • Set up automations that run on schedules or triggers

The agent talks to Qordinate's AI agent through a single powerful tool — query_agent — using natural language.


Connection Details

FieldValue
ProtocolMCP (Model Context Protocol) — Streamable HTTP
MCP Server URLhttps://api.qordinate.ai/mcp
Auth MethodBearer token — Authorization: Bearer qk_YOUR_API_KEY
API Key FormatPrefixed with qk_

User Setup (what the agent should tell the user once)

Before the agent can connect, the user needs a Qordinate account and an API key:

  1. Sign up at https://app.qordinate.ai using their phone number + OTP
  2. Go to Profile → API Keys → New API Key to create an API key
  3. Give the API key (starts with qk_) to the agent

The API key is shown only once at creation time. The user can set an expiry (1–365 days) or leave it non-expiring.


MCP Tool: query_agent

Qordinate's MCP server exposes one tool — query_agent — which is a natural-language interface to the full Qordinate AI agent. The agent has access to the user's documents, contacts, lists, web search, and all connected apps.

Input Schema

ParameterTypeRequiredDescription
querystring✅Your question or request for the Qordinate agent
session_idstring❌Optional session ID for multi-turn conversations

How to use session_id

  • Omit session_id for standalone queries
  • To have a multi-turn conversation, capture the session ID from the first response and pass it in subsequent calls
  • This lets the Qordinate agent maintain context across multiple queries

What the agent can do through query_agent

The query_agent tool invokes the full Qordinate AI agent, which can do everything a user interacting directly with Qordinate can do:

Structured Memory (Lists & Tasks)

  • Create, update, and query lists (tasks, contacts, leads, projects, resources, etc.)
  • Set due dates, statuses, and reminders on list items
  • Qordinate manages reminders and notifications over time

Documents

  • Create, read, update, and delete documents
  • Upload and retrieve files (PDFs, images, etc.)
  • Share documents with other users

Contacts

  • Store and retrieve contact information
  • Import contacts (including VCF format)
  • Search contacts by name, company, role, etc.

Web Search

  • Search the web for current information
  • The agent can ask Qordinate to research topics and return results

Connected Apps

  • Interact with third-party apps the user has connected to Qordinate
  • Query data from connected services

Forms & Automations

  • Create forms and collect submissions
  • Set up automations that trigger on schedules or events

Example Interactions

Your OpenClaw agent sends these as the query parameter to query_agent:

Managing tasks

Add a new task: Follow up with ACME about the reorder pilot, due next Tuesday 3pm, status todo, notes: important client meeting

Storing contacts

Save a new contact: Harpinder Singh, Co-founder at qordinate.ai, building Qordinate

Querying information

Show me all my open tasks due this week

Searching the web

Search the web for the latest pricing of OpenAI GPT-4o API

Working with documents

Create a new document titled "Meeting Notes - ACME Q1 Review" with the following content: ...

Updating items

Mark the task "Follow up with ACME" as done

How the agent should think about Qordinate

  • Treat Qordinate as the source of truth for "what needs doing" and "who is who" across time
  • Offload anything the user will care about later — don't keep it in ephemeral memory
  • Use natural language — the query_agent tool understands plain English requests
  • Use session_id for related queries — if you're doing a multi-step workflow (e.g., "list tasks" then "mark task X as done"), use the same session_id
  • Be specific — include list names, field values, dates, and context in your queries

User Channels (optional, for the user)

Users can also interact with Qordinate directly on their preferred messaging platform. This is independent of the agent's MCP connection:

Everything the user does on these channels is reflected in the same account the agent accesses via MCP — they share the same data.

平台分布

OpenClaw

90.64%
按下载量换算10,076

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

未展示

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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