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Long-Term Memory

Long-Term Memory

by ihwooMil
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

memory_get_related

Retrieve memories connected to a given memory by traversing related links up to a specified depth.

Instructions

Get memories related to a given memory via graph edges (BFS traversal).

Args: memory_id: The starting memory ID. depth: How many hops to traverse (default: 1, max: 3).

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_get_related"
  }
}

Input Schema

NameRequiredDescriptionDefault
depthNo
memory_idYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.2/5.0
Behavior3/5

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

No annotations are provided, so the description carries the burden. It states the tool 'gets' memories, implying a read-only operation, but does not explicitly declare side-effect-free behavior or discuss any potential errors or limitations beyond the depth max. The 'Get' verb provides reasonable transparency for a simple retrieval.

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 concise, using two sentences and a clear parameter listing. It avoids unnecessary detail while providing essential information.

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?

For a straightforward retrieval tool, the description is complete. It explains the purpose, parameters, and traversal depth. No output schema is shown, but the return (related memories) is implicit and sufficient for the tool's simplicity.

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?

Both parameters are clearly explained: memory_id is the starting memory ID, and depth specifies how many hops to traverse with a default of 1 and a max of 3. This fully covers the schema's meaning and constraints.

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 function: retrieving related memories via graph edges using BFS. It specifies the resource (memories) and the operation (get related), distinguishing it from search or save tools by its graph-based traversal focus.

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 explains what the tool does but does not explicitly state when to use it versus alternatives like memory_search or memory_visualize. It implies a use case (having a memory ID and wanting related ones) but lacks direct comparison or conditions.

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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