Get estimated cost of living for a Brazilian city: rent, food, transport, health, education, leisure. Enter a city name for detailed monthly expenses from IBGE data and 2026 estimates.
Retorna custo de vida estimado em uma cidade brasileira — aluguel, alimentação, transporte, saúde, educação, lazer. Dados IBGE POF + estimativas 2026.
| Name | Required | Description | Default |
|---|---|---|---|
| city | Yes | Nome da cidade (ex: 'São Paulo', 'Curitiba', 'Recife') |
Changes observed during successful MCP inspections.
v1.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavior disclosure. It does add useful context by stating the estimate nature, the categories covered, and the data source (IBGE POF + 2026 estimates). However, it does not disclose what happens for unknown/unrecognized cities, whether values are returned as a breakdown or total, or any other operational behavior.
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 compact sentence that front-loads the main purpose, lists representative categories, and adds the data source. Every part contributes useful information, with no filler or repetition.
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?
For a simple one-parameter lookup with no output schema, the description covers the core behavior, the input scope, and the nature of the returned data. It could be slightly more complete by clarifying the expected response shape or behavior for invalid city names, but it is largely sufficient for an agent to call it correctly.
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 single 'city' parameter is fully documented in the schema with an example, so schema description coverage is 100%. The tool description reinforces that the city must be Brazilian but does not add significant meaning beyond what the schema already provides, so the baseline score of 3 is appropriate.
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 uses a specific verb ('Retorna') and names the resource: estimated cost of living in a Brazilian city, including concrete categories like rent, food, transport, and health. This clearly distinguishes it from the sibling calculators and table-lookup tools, which target different calculations or data.
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 makes the intended context clear: use this tool when the agent needs an estimated cost of living for a Brazilian city. It does not explicitly name alternatives or state when not to use it, but the purpose is specific enough that confusion with sibling tools is unlikely.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.