Listing details
get_listing_detailsFatos do próprio anúncio (cor, portas, opcionais, vendedor, fonte, km, link). Use para perguntas diretas sobre este carro específico.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| car_id | Yes |
get_listing_detailsFatos do próprio anúncio (cor, portas, opcionais, vendedor, fonte, km, link). Use para perguntas diretas sobre este carro específico.
| Name | Required | Description | Default |
|---|---|---|---|
| car_id | Yes |
Changes observed during successful MCP inspections.
Input schema / properties / car_id / maximumAdded value: +9223372036854776000Input schema / properties / car_id / minimumAdded value: +1Does 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 adds that the payload is scoped to listing-level attributes rather than vehicle specs, which is useful context, but it says nothing about behavior when the listing is missing or stale.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two compact sentences with the field inventory front-loaded and the usage hint trailing, no filler. Efficient, though the parenthetical field list is doing more work than a structured output description would.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, the description carries the burden of describing return content and does list the returned fields, which is the strongest part. It omits, however, the meaning/units of values (e.g. mileage units, link form) and any failure semantics, so it is only partially complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% and there is one required parameter (car_id) that the description never explains. The phrase "este carro específico" only loosely implies car_id identifies the listing; format, valid range, or error behavior for an invalid id are not addressed, so the description fails to compensate for the schema gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description names a concrete resource (listing facts) and enumerates the fields returned (color, doors, options, seller, source, mileage, link), so the agent knows what comes back. However, it never distinguishes this from sibling tools that sound nearly identical, notably get_vehicle_by_id and get_technical_specs, leaving the agent to guess which one to call.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
"Use para perguntas diretas sobre este carro específico" gives an implied usage context: direct factual questions about one specific car. There is no when-not-to-use guidance and no alternative sibling is named, so the routing decision against get_vehicle_by_id remains unresolved.
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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