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The LLM context window is temporary. Everything in it disappears when the conversation ends. The memory system is permanent: documents written to memory survive indefinitely and are retrievable via search from any session. This means the agent must be proactive about writing. Before answering a question about prior work, the agent should search memory. Before ending a task that produced useful information, the agent should write a summary.
The agent is instructed to call memory_search before answering questions about past work, prior decisions, or previously stored information. If you feel the agent has forgotten something, try asking it to search memory explicitly.

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Workspace Structure

The workspace uses a filesystem-like path hierarchy. Documents live at paths you define: Paths are arbitrary strings. Use whatever structure makes sense for your workflow. The memory_tree tool shows all paths organized as a directory tree.

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Four Memory Tools

You can configure the memory to be persisted as a vector store, which allows for fast semantic search and retrieval during the initial onboarding. This is ideal for larger workspaces or when you want the agent to have quick access to a large amount of information.