memos-memory-guide
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_timelin
npx skills add MemTensor/MemOS --skill memos-memory-guide --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# 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 - **What it does:** Search
- How memory is provided each turn
- Tools — what they do and when to call
- memorysearch
- memoryget
- memorywritepublic
- memoryshare
- memoryunshare
- tasksummary
- skillget
- skillsearch
- skillinstall
- skillpublish
- skillunpublish
- networkmemorydetail
What does the memos-memory-guide skill do?
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_timelin
How do I install it?
Run `npx skills add MemTensor/MemOS --skill memos-memory-guide --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From MemTensor/MemOS, a repository with 10,587 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.