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openclaw-universal-memoryOpenClaw universal 记忆

Agent Skill

openclaw-universal-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。

总安装

21,380

周安装

909

GitHub Stars

公开资料未说明

下载量

7,490
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

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-universal-memory(OpenClaw universal 记忆)
来源仓库:https://github.com/marcosathanasoulis/openclaw-universal-memory
安装命令:
openclaw skills install openclaw-universal-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-universal-memory

简介

通用 Postgres 和 pgvector 内存层,用于与连接器无关的数据摄取、增量同步以及带有游标历史记录的可搜索块存储。

SKILL.md

name
openclaw-universal-memory
description
Connector-agnostic Postgres + pgvector memory ingestion and retrieval with incremental cursor history.

OpenClaw Universal Memory

This skill provides a generic memory layer for heterogeneous data:

  • canonical entity/chunk schema,
  • connector-style ingestion with cursors,
  • searchable memory in Postgres.

Use Cases

  • Normalize records from multiple systems into one schema.
  • Keep incremental sync history (cursor per connector/account).
  • Build RAG-ready chunk storage in pgvector.

Prerequisites

  • Postgres with vector extension.
  • Local package installed: pip install -e ..
  • Python dependency for DB I/O:

- pip install "psycopg[binary]>=3.2"

  • DSN provided via environment variable (DATABASE_DSN by default).

Security Boundaries

  • Do not pass raw passwords/tokens in command-line arguments.
  • Prefer OS secret store or process environment injection for DSN.
  • This skill only reads/writes your configured Postgres database; it does not call external APIs directly.
  • Use least-privilege DB credentials (SELECT/INSERT/UPDATE/DELETE on um_* tables only).
  • Review and trust any custom connector before running it.

Responsible Use Caveat

  • Use this only for accounts/data you legitimately control or are authorized to process.
  • You are responsible for privacy, retention, and regulatory compliance.
  • This project is provided under Apache 2.0 without operational warranty.
  • This implementation is mostly AI-generated code with experienced engineer oversight; validate before production use.

Commands

Store DB credentials once (recommended):

python skills/openclaw-universal-memory/scripts/run_memory.py \
  --action configure-dsn

Initialize schema:

python skills/openclaw-universal-memory/scripts/run_memory.py \
  --action init-schema \
  --dsn-env DATABASE_DSN

Ingest JSON/NDJSON:

python skills/openclaw-universal-memory/scripts/run_memory.py \
  --action ingest-json \
  --dsn-env DATABASE_DSN \
  --source gmail \
  --account marcos@athanasoulis.net \
  --entity-type email \
  --input /path/to/records.ndjson

Ingest from built-in connectors:

python skills/openclaw-universal-memory/scripts/run_memory.py \
  --action ingest-connector \
  --connector google \
  --account you@example.com \
  --dsn-env DATABASE_DSN \
  --limit 300

Validate connector auth/config before ingest:

python skills/openclaw-universal-memory/scripts/run_memory.py \
  --action validate-connector \
  --connector google \
  --account you@example.com \
  --dsn-env DATABASE_DSN \
  --limit 1

Search:

python skills/openclaw-universal-memory/scripts/run_memory.py \
  --action search \
  --dsn-env DATABASE_DSN \
  --query "Deryk" \
  --limit 20

Recent ingest history:

python skills/openclaw-universal-memory/scripts/run_memory.py \
  --action events \
  --dsn-env DATABASE_DSN \
  --limit 20

Doctor check:

python skills/openclaw-universal-memory/scripts/run_memory.py \
  --action doctor

Scheduling reference:

  • docs/SCHEDULING.md (cron examples, 15-minute default, connector toggles)

Connector Contract (for custom adapters)

A connector returns normalized records + next cursor:

  • external_id
  • entity_type
  • title
  • body_text
  • raw_json
  • meta_json
  • next_cursor

This keeps ingestion generic and supports arbitrary source systems.

Starter connector templates:

  • src/openclaw_memory/connectors/templates.py

Step-by-step setup guide (Gmail/Slack/Asana/iMessage):

  • docs/CONNECTOR_SETUP_WALKTHROUGH.md

Community

We welcome connector contributions via PR. See docs/CONNECTOR_CONTRIBUTING.md for required contract, tests, and setup instructions.

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

87.44%
按下载量换算6,549

安全审计

VirusTotal

可疑

ClawScan

可疑

Static analysis

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权限和风险

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 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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