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Long-Term Memory

Long-Term Memory

by ihwooMil
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

memory_pin

Pin a memory by ID to protect it from the forgetting pipeline, ensuring its retention.

Instructions

Pin a memory to protect it from the forgetting pipeline.

Args: memory_id: The ID of the memory to pin.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "memory_id": "<memory_id>"
    },
    "name": "memory_pin"
  }
}

Input Schema

NameRequiredDescriptionDefault
memory_idYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.4/5.0
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It discloses the primary effect (protection from forgetting) but does not mention reversibility, permissions, or error cases; however for a simple pin operation this is sufficient transparency.

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 two short sentences, front-loaded with the action and purpose, and the parameter explanation is minimal and relevant.

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

Completeness5/5

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

The tool is simple – one required parameter. The description fully explains what the tool does and what the parameter means. Since an output schema is indicated as present, return values need not be described.

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

Parameters5/5

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

The schema only specifies memory_id as a required string, but the description adds 'The ID of the memory to pin', giving clear meaning to the parameter and explaining what value to provide.

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

Purpose5/5

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

The description clearly states the action ('Pin a memory') and the purpose ('protect it from the forgetting pipeline'), differentiating it from the sibling memory_unpin which reverses this action.

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

Usage Guidelines3/5

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

The description implies the use case (protect a memory from forgetting) but does not explicitly contrast with alternatives like memory_unpin or mention conditions for use, leaving the guidance implicit rather than explicit.

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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