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get_long_term_memory

Retrieve persistent user profiles and preferences to maintain personalized AI interactions across sessions.

Instructions

Retrieve long-term memory for a user

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
userIdYesUser identifier

Implementation Reference

  • The main handler logic for the 'get_long_term_memory' tool. It validates the userId argument, retrieves the long-term memory using memoryStore, and returns it as a JSON-formatted text response.
    case "get_long_term_memory": {
      const { userId } = request.params.arguments as any;
      
      // Validate inputs
      ValidationUtils.validateUserId(userId);
      
      const memory = memoryStore.getLongTermMemory(userId);
      return {
        content: [{
          type: "text",
          text: JSON.stringify(memory, null, 2)
        }]
      };
    }
  • The tool registration entry in the ListTools handler, including name, description, and input schema specification.
    {
      name: "get_long_term_memory",
      description: "Retrieve long-term memory for a user",
      inputSchema: {
        type: "object",
        properties: {
          userId: {
            type: "string",
            description: "User identifier"
          }
        },
        required: ["userId"]
      }
    },
  • The input schema defining the expected arguments for the 'get_long_term_memory' tool: a required userId string.
    inputSchema: {
      type: "object",
      properties: {
        userId: {
          type: "string",
          description: "User identifier"
        }
      },
      required: ["userId"]
    }
  • The core helper method in MemoryStore that retrieves the long-term memory data for a user from the internal Map.
    getLongTermMemory(userId: string): LongTermMemory | null {
      return this.longTermMemory.get(userId) || null;
    }
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It only states the retrieval action without detailing what 'long-term memory' entails (e.g., format, scope, or persistence), whether it requires authentication, or if there are rate limits. This is inadequate for a tool with no annotation coverage.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It is appropriately sized and front-loaded, making it easy to parse quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity of memory retrieval tools and the lack of annotations or output schema, the description is incomplete. It doesn't explain what 'long-term memory' returns, how it differs from other memory types, or any behavioral traits, leaving significant gaps for an AI agent to understand its use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage, with the 'userId' parameter clearly documented. The description adds no additional parameter semantics beyond what the schema provides, such as explaining the user context or memory retrieval specifics. Baseline 3 is appropriate since the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Retrieve') and resource ('long-term memory for a user'), making the purpose understandable. However, it doesn't distinguish this tool from its siblings like 'get_episodic_memory' or 'get_short_term_memory', which also retrieve memory types, so it lacks sibling differentiation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention when to prefer long-term over short-term or episodic memory, nor does it reference sibling tools like 'set_long_term_memory' for updates or 'search_episodic_memory' for queries, leaving usage context unclear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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