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, task_summary, skill_get, skill_search, skill_install, skill_publish, skill_unpublish, memory_timeline, memory_viewer.
This skill describes how to use the MemOS memory tools so you can reliably search and use the user's long-term conversation history, share knowledge across agents, and discover public skills.
memory_search yourself.public. Other agents' private memories are invisible to you.chunkIdtask_idmemory_search(query="...").role='user').query (string, required) — Natural language search query.maxResults (number, optional) — Max results, default 20, max 20.minScore (number, optional) — Minimum score 0–1, default 0.45, floor 0.35.role (string, optional) — Filter by role: 'user', 'assistant', or 'tool'. Use 'user' to find what the user said.memory_search hit looks relevant but you need to see the complete original content, not just the summary/excerpt.chunkId (string, required) — The chunkId from a search hit.maxChars (number, optional) — Max characters to return (default 4000, max 12000).memory_search. Use for shared knowledge, team decisions, or cross-agent coordination information.content (string, required) — The content to write to public memory.summary (string, optional) — Short summary of the content.memory_search returns a hit with a task_id and you need the full story. Preserves critical information: URLs, file paths, commands, error codes, step-by-step instructions.memory_search hit included a task_id and you need the full context of that task.taskId (string, required) — The task_id from a memory_search hit.skillId or by taskId. If you pass a taskId, the system will find the associated skill automatically.task_id and the task has a "how to do this again" guide. Use this to follow the same approach or reuse steps.skillId (string, optional) — Direct skill ID.taskId (string, optional) — Task ID — will look up the skill linked to this task.skillId or taskId must be provided.scope parameter.skill_search to find one first; after finding it, use skill_get to read it, then skill_install to load it for future turns.query (string, required) — Natural language description of the needed skill.scope (string, optional) — Search scope: 'mix' (default, self + public), 'self' (own only), 'public' (public only).skill_get when the skill is useful for ongoing use.skillId (string, required) — The skill ID to install.skill_search.skillId (string, required) — The skill ID to publish.skillId (string, required) — The skill ID to unpublish.chunkId from a search result to read the surrounding conversation messages.memory_search hit is relevant but you need the surrounding dialogue.chunkId (string, required) — The chunkId from a memory_search hit.window (number, optional) — Context window ±N messages, default 2.No memories in context or auto-recall reported nothing
→ Call memory_search(query="...") with a self-generated short query.
Need to see the full original text of a search hit
→ Call memory_get(chunkId="...").
Search returned hits with task_id and you need full context
→ Call task_summary(taskId="...").
Task has an experience guide you want to follow
→ Call skill_get(taskId="...") or skill_get(skillId="..."). Optionally skill_install(skillId="...") for future use.
You need the exact surrounding conversation of a hit
→ Call memory_timeline(chunkId="...").
You need a capability/guide that you don't have
→ Call skill_search(query="...", scope="mix") to discover available skills.
You have shared knowledge useful to all agents
→ Call memory_write_public(content="...") to persist it in public memory.
You want to share/stop sharing a skill with other agents
→ Call skill_publish(skillId="...") or skill_unpublish(skillId="...").
User asks where to see or manage their memories
→ Call memory_viewer() and share the URL.
role='user' when you specifically want to find what the user said.Each memory is tagged with an owner (e.g. agent:main, agent:sales-bot). This is handled automatically — you do not need to pass any owner parameter.
memory_search, memory_get, memory_timeline) automatically scope queries to your agent's own memories.public are visible to all agents. Use memory_write_public to write shared knowledge.