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Detalhar reserva

get_reservation
Read-onlyIdempotent

Detalhe completo de uma estadia: hóspede, acompanhantes, veículos, lançamentos, pagamentos, saldo, observações, histórico e reservas vinculadas do grupo.

Escopo: reservations:read · Risco: read · Efeitos: Nenhum.

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": {
      "id": "<id>"
    },
    "name": "get_reservation"
  }
}

Input Schema

NameRequiredDescriptionDefault
idYesId ou código da reserva.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so the bar is lower; the description nonetheless adds the auth scope (reservations:read), an explicit risk/effects statement, and — critically, since there is no output schema — a concrete inventory of the data returned. It does not discuss whether some sub-sections are omitted when empty or any size/latency characteristics of this heavyweight detail call.

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?

Two compact blocks: the payload inventory first, then a one-line scope/risk/effects footer. Every element is informative and nothing is padded, though the long comma list of returned fields is dense enough to skim past rather than parse.

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 compensates by listing the returned data, and the scope/risk/effects line covers the safety profile alongside the annotations. For a single-id read tool this is close to sufficient; only error behavior for a missing/invalid id is unaddressed.

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?

There is a single parameter and the schema documents it at 100% coverage ('Id ou código da reserva'), so the description cannot add much. It adds nothing about the accepted formats or what happens on an unknown id, leaving schema coverage to carry the load – the baseline for high-coverage schemas.

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?

States a specific verb+resource ('Detalhe completo de uma estadia') and enumerates exactly what the record contains (hóspede, acompanhantes, veículos, lançamentos, pagamentos, saldo, histórico), which distinguishes it from aggregate siblings like list_reservations. It never names the sibling alternatives explicitly, so differentiation is by implication rather than declaration.

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 implied by 'Detalhe completo' – fetch one reservation by id – but there is no explicit when-to-use / when-not-use guidance and no mention of when an agent should prefer list_reservations or get_guest instead. A competent agent can infer the intent, which lands this at minimum-viable rather than strong.

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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