Grid Radar

Sentimiento de mercado

radar_query_market_sentiment

Read-onlyIdempotent

Resumen de las reseñas de un producto canónico de tu organización: cantidad, nota promedio, distribución de sentimiento, aspectos más mencionados y las reseñas negativas más recientes. Sin reseñas responde totalReviews: 0; no se inventa un sentimiento. El productId sale de radar_search_listings.

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": {
      "productId": "<productId>"
    },
    "name": "radar_query_market_sentiment"
  }
}

Input Schema

Name	Required	Description	Default
`source`	No	Acota a una fuente de reseñas.
`productId`	Yes	Identificador del producto canónico (`productId` de `radar_search_listings`).

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 11, 2026

TDQS

A3.7/5.0

Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and a closed-world scope, so the safety profile is covered. The description contributes a genuine behavioral fact not in the annotations: absent reviews yield `totalReviews: 0` rather than a fabricated sentiment. It does not disclose the aggregation time window or result limits, which are the main remaining behavioral unknowns.

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

Conciseness4/5

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

Three sentences, front-loaded with the returned payload, then the empty-state rule, then the identifier source. Nothing is padding, though the first sentence is a long enumeration that could be tightened slightly.

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

Completeness4/5

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

With no output schema, the description does the work of describing the response shape and the zero-review edge case, which is exactly what an agent needs. It is only short of complete because the observation window and any result-size limits for the sentiment summary are unstated.

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?

Schema description coverage is 100%, so the schema already documents both parameters, including the provenance of `productId`. The description largely restates that provenance and adds no syntax or semantics for the `source` enum. Baseline 3 applies.

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 names a specific verb and resource (review summary for a canonical product) and enumerates the returned content: count, average rating, sentiment distribution, top-mentioned aspects and most recent negative reviews. An agent can tell this apart from the sibling price/stock/listing tools without inspecting the schema.

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?

Usage is only implied: it states that `productId` comes from `radar_search_listings`, which establishes the required call chain, but there is no explicit when-to-use/when-not guidance or any reference to an alternative tool. The `source` filter's purpose is left entirely to the schema.

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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