Token导航 LogoToken导航

Agent Skill · 研究检索

seekdb-memory(查找数据库内存)

seekdb-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。

seekdb-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,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 33,102。

总安装 2,421周安装 97GitHub Stars 1下载 784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
0.2.1

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:seekdb-memory(查找数据库内存)
来源仓库:https://github.com/frf12/seekdb-memory
安装命令:
openclaw skills install seekdb-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 seekdb-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 代理的云原生持久化记忆存储组件。自动捕获对话事实并在回复前检索相关上下文。混合搜索机制提升信息召回准确性。seekdb-memory 属于研究检索类 Skill,可作为该场景下的辅助能力补充。通过 clawhub 命令安装并集成至 OpenClaw 系统。记忆内容默认本地存储,敏感信息建议加密处理。

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 seekdb-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

seekdb-memory 怎么安装?

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

seekdb-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。

seekdb-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。

seekdb-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。

seekdb-memory 用的人多吗?

公开数据是累计安装 2,421 次,近一周安装 97 次,下载 784 次,GitHub 1 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。

seekdb-memory 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

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。

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。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 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。

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
seekdb-memory

查找数据库内存 · 本页

2,4211接触敏感数据MIT-0有提醒

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
seekdb-memory
version
0.2.1
description
Cloud-native persistent memory for OpenClaw agents. Auto-captures facts after conversations, auto-recalls relevant context before each reply. Hybrid search (vector + fulltext + RRF + rerank), query rewrite, experience learning — all behind one API key. Use this when the agent needs long-term memory, persistent context, or cross-session recall.
metadata
openclaw
emoji
🧠
requires
env
[]
plugins

SeekDB Memory — Cloud-Native Agent Memory

Persistent long-term memory for OpenClaw agents. Once the m0 plugin is installed, your agent automatically remembers facts across conversations and recalls relevant context before each reply.

What It Does

CapabilityHow It Works
Auto-CaptureAfter each conversation, extracts key facts via LLM and stores them in the cloud
Auto-RecallBefore each reply, searches for relevant memories and injects them as context
Hybrid SearchVector similarity (HNSW) + fulltext (BM25) + RRF fusion + rerank
Query RewriteResolves pronouns, splits compound questions, expands keywords
Experience LearningDistills successful tool-use patterns into reusable recipes
Cross-DeviceCloud-native — memories are available from any device, no sync needed

Memory Tools

Use these tools to manage the agent's long-term memory:

memory_recall

Search memories by semantic similarity. Returns the most relevant memories.

memory_recall query="user's preferred programming language" limit=5

Use when:

  • The user asks about something discussed in a previous conversation
  • You need context about user preferences, past decisions, or facts
  • The user references something with "last time", "before", "remember when"

memory_store

Save an important fact, preference, or decision to long-term memory.

memory_store text="User prefers TypeScript over JavaScript for all new projects" metadata={"category": "preference", "importance": 0.9}

Use when:

  • The user states a preference ("I always use...", "I prefer...")
  • A decision is made ("Let's go with...", "We decided...")
  • The user corrects you ("Actually, it's...", "No, I meant...")
  • Important facts are shared (deadlines, names, project details)

memory_forget

Delete a specific memory by ID.

memory_forget id=42

Use when:

  • The user asks to forget something
  • A memory is outdated or incorrect
  • Cleaning up duplicate memories

Automatic Behavior

With default configuration, the agent does NOT need to call tools manually for basic memory operations:

  1. Before each conversation: The m0 plugin automatically searches for relevant memories based on the user's message and injects them as context. The agent sees them as <relevant-memories> in the prompt.
  1. After each conversation: The m0 plugin automatically extracts key facts from the conversation and stores them. No manual memory_store needed for routine facts.
  1. Manual tools are for explicit user requests ("remember this", "forget that", "what did I say about X?").

Experience System

The m0 plugin tracks successful tool-use patterns and distills them into reusable experiences.

experience_detail

View the full description of a distilled experience.

experience_detail id=7

Experiences are automatically injected alongside memories when relevant. They help the agent avoid repeating mistakes and reuse proven approaches.

Best Practices

  1. Don't over-store: Auto-capture handles routine facts. Only use memory_store for high-importance items the user explicitly wants remembered.
  2. Use metadata: Add category (preference, decision, fact, deadline) and importance (0.0-1.0) to help with retrieval.
  3. Trust auto-recall: Don't call memory_recall at the start of every conversation — the plugin already injects relevant context automatically.
  4. Respect forget requests: When a user says "forget X", use memory_forget immediately.

Setup

If the m0 plugin is not yet installed, run the setup skill:

/openclaw-m0-setup

Or install manually:

openclaw add m0

Then configure in ~/.openclaw/openclaw.json:

{
  "plugins": {
    "entries": {
      "m0": {
        "enabled": true,
        "config": {
          "apiKey": "ak_your_key_here",
          "baseUrl": "https://your-endpoint",
          "autoCapture": true,
          "autoRecall": true,
          "recallLimit": 10
        }
      }
    }
  }
}

Requirements

  • OpenClaw >= 2026.2.2
  • m0 plugin installed and configured with a valid API key

平台分布

OpenClaw

86.22%
按下载量换算676

安全审计

VirusTotal

通过

ClawScan

可疑

Static analysis

通过

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

继续浏览同类 Skills