Lista as marcas de um tipo de veículo (1=carro, 2=moto, 3=caminhão). Retorna [{ codigo_marca, marca }]. Primeiro passo do drill-down até o preço.
| Name | Required | Description | Default |
|---|---|---|---|
| tipo_veiculo | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnly, idempotent, and non-destructive. Description adds return format and role in workflow, but no additional behavioral traits beyond what annotations imply.
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 concise sentences that efficiently convey purpose, parameter, output, and context without any wasted words.
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?
Tool has low complexity (1 param, no output schema). Description sufficiently explains input, output, and its place in the workflow.
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 has 0% coverage, but description fully explains the sole parameter (tipo_veiculo) with mapping to vehicle types, compensating completely.
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?
Description clearly states it lists brands for a vehicle type with specific codes (1=carro, 2=moto, 3=caminhão) and return format. Distinguishes from sibling tools like fipe_modelos and fipe_preco.
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?
States it is the first step of a drill-down to price, implying when to use it. However, does not explicitly exclude alternatives or provide when-not scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
The seven fipe_* tools each target a distinct step in the FIPE data lookup (brands, models, years, price, history, search, reference dates), and their names make their purposes clear. However, connect and toolkit_info both report connection status, and marketplace bundles many sub-operations into one tool, creating minor ambiguity.
FIPE tools follow a consistent fipe_<noun> pattern, but the platform tools (authenticate, connect, marketplace, report_bug, show_version, toolkit_info) use generic verbs/nouns without a shared convention, mixing styles within the same server.
13 tools is within the ideal range for a domain-specific data server; the 7 FIPE tools are well-scoped and the 6 platform utilities are justified for authentication, marketplace access, and system status.
The FIPE data surface is complete: marcas → modelos → anos → preco covers the full drill-down, with buscar, historico, and tabelas_referencia adding search, time series, and date selection. No obvious missing operations for the domain.