Busca fuzzy por nome de modelo na Tabela FIPE (ex.: 'gol 1.6', 'civic touring'). Retorna candidatos [{ tipo_veiculo, codigo_marca, marca, codigo_modelo, modelo, codigo_fipe? }] para então consultar fipe_anos/fipe_preco.
| Name | Required | Description | Default |
|---|---|---|---|
| q | Yes | ||
| tipo_veiculo | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and idempotentHint, covering safety. The description adds that the search is fuzzy and returns a list of candidates, which is mildly behavioral but not extensively beyond annotations.
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?
The description is a single sentence with a helpful example, making it concise and to the point. It is appropriately sized but could be slightly more structured with separate lines for clarity.
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?
Given two parameters and no output schema, the description provides a reasonable overview of purpose and return structure. However, it lacks detailed parameter explanations and does not specify query syntax or constraints, leaving gaps for an agent to infer.
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?
The input schema has 0% description coverage and the tool description does not explain the parameters 'q' or 'tipo_veiculo' explicitly. The example hints at 'q' being a model name, but no types or formats are mentioned, leaving the agent without sufficient guidance.
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 clearly states a fuzzy search by model name, provides examples, and indicates it returns candidates for subsequent queries. However, it does not explicitly differentiate from sibling tools like fipe_modelos, which might also list models.
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?
The description implies this is a preliminary step before fipe_anos or fipe_preco, giving some usage context. But it lacks explicit when-to-use or when-not-to-use guidance, or mention of alternatives like fipe_marcas.
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.