# Memos Memory Guide

Use the MemOS Local memory system to search and use the user's past conversations.

- Repository: https://github.com/MemTensor/MemOS (12221 stars)
- Category: Engineering
- License: Apache-2.0
- Last updated: 2026-10-29
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add MemTensor/MemOS --skill memos-memory-guide -g -a claude-code -y`
Codex: `npx skills add MemTensor/MemOS --skill memos-memory-guide -g -a codex -y`
Cursor: `npx skills add MemTensor/MemOS --skill memos-memory-guide -g -a cursor -y`
Gemini CLI: `npx skills add MemTensor/MemOS --skill memos-memory-guide -g -a gemini-cli -y`

## Description

Use the MemOS Local memory system to search and use the user's past conversations. Use this skill whenever the user refers to past chats, their own preferences or history, or when you need to answer from prior context. When auto-recall returns nothing (long or unclear user query), generate your own short search query and call memory_search. Available tools: memory_search, memory_get, memory_write_public, memory_share, memory_unshare, task_summary, skill_get, skill_search, skill_install, skill_publish, skill_unpublish, network_memory_detail, network_skill_pull, network_team_info, memory_timeline, memory_viewer.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# MemOS Local Memory, Agent Guide

This skill describes how to use the MemOS memory tools so you can reliably search and use the user's long-term conversation history, query team-shared data, share tasks, and discover or pull reusable skills.

Two sharing planes exist and must not be confused:

- **Local agent sharing:** visible to agents in the same OpenClaw workspace only.
- **Team sharing:** visible to teammates through the configured team server.

## How memory is provided each turn

- **Automatic recall (hook):** At the start of each turn, the system runs a memory search using the user's current message and injects relevant past memories into your context. You do not need to call any tool for that.
- **When that is not enough:** If the user's message is very long, vague, or the automatic search returns **no memories**, you should **generate your own short, focused query** and call `memory_search` yourself.
- **Memory isolation:** Each agent can only see its own local private memories and local `public` memories. Team-shared data only appears when you search with `scope="group"` or `scope="all"`.

## Tools, what they do and when to call

### memory_search

The rest: https://github.com/MemTensor/MemOS/blob/HEAD/apps/memos-local-openclaw/skill/memos-memory-guide/SKILL.md