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by Renzo-Tognella
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

memory.feedback

Record usage feedback by submitting a score and acceptance status for a memory, improving telemetry and future AI decision recall.

Instructions

Registra feedback de uso para telemetria.

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>",
      "score": "<score>"
    },
    "name": "memory.feedback"
  }
}

Input Schema

NameRequiredDescriptionDefault
scoreYes
acceptedNo
memory_idYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.4/5.0
Behavior2/5

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

With no annotations provided, the description must disclose behavioral traits, but it only states the purpose. It does not mention side effects, authentication needs, or success/failure behavior, leaving the agent uninformed.

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

Conciseness3/5

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

The description is a single concise sentence (6 words), but it is overly simplistic and omits necessary detail. It does not justify its brevity by providing front-loaded key information beyond the core action.

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

Completeness1/5

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

Given the tool has 3 parameters, no output schema, and no annotations, the description is severely incomplete. It does not explain what feedback entails, how to interpret parameters, or what the agent should expect from the tool's execution.

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

Parameters1/5

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

Schema description coverage is 0%, and the description does not explain any of the three parameters (memory_id, score, accepted). It adds no meaning beyond the schema structure, failing to compensate for the lack of schema-level descriptions.

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 states the tool registers usage feedback for telemetry, which clearly identifies the action and resource. However, it does not differentiate from similar siblings like memory.set_weight or other feedback mechanisms, and the use of Portuguese may hinder non-Portuguese agents.

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?

No guidance is given on when to use this tool versus alternatives. The description lacks context about prerequisites, exclusions, or specific scenarios for feedback submission.

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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