MemOS Lite 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.

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. For example:
  • User sent a long paragraph → extract 1–2 key topics or a short question and search with that.
  • Auto-recall said "no memories" or you see no memory block → call memory_search with a query you derive (e.g. the user's name, a topic they often mention, or a rephrased question).
• When you need more detail: Search results only give excerpts and IDs. Use the tools below to fetch full task context, skill content, or surrounding messages.

Tools — what they do and when to call

memory_search

• What it does: Searches the user's stored conversation memory by a natural-language query. Returns a list of relevant excerpts with chunkId and optionally task_id.
• When to call:
  • The automatic recall did not run or returned nothing (e.g. no <memory_context> block, or a note that no memories were found).
  • The user's query is long or unclear — generate a short query yourself (keywords, rephrased question, or a clear sub-question) and call memory_search(query="...").
  • You need to search with a different angle (e.g. filter by role='user' to find what the user said, or use a more specific query).
• Parameters: query (required), optional minScore, role (e.g. "user").
• Output: List of items with role, excerpt, chunkId, and sometimes task_id. Use those IDs with the tools below when you need more context.

task_summary

• What it does: Returns the full task summary for a given task_id: title, status, and the complete narrative summary of that conversation task (steps, decisions, URLs, commands, etc.).
• When to call: A memory_search hit included a task_id and you need the full story of that task (e.g. what was done, what the user decided, what failed or succeeded).
• Parameters: taskId (from a search hit).
• Effect: You get one coherent summary of the whole task instead of isolated excerpts.

skill_get