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

Annotations already mark the tool read-only; the description adds relevant behavioral context: it covers only apartments, it accepts city or neighborhood scope, and the data is a dated cut ('Recorte publicado em 07/09/2026'). It does not describe the result format, but no output schema exists and the read-only profile reduces the burden.

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?

Three short sentences, each earning its place: the main output and filters, the use case, and the data vintage. It is front-loaded and free of 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 read-only lookup with three parameters and no output schema, the description covers what is returned, the available filters, the apartment-only scope, the use case, and the publication date. Nothing essential is missing 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?

Schema coverage is 100%, but the description earns extra credit by decoding the opaque faixa enum values into understandable ranges (up to 50, 50-70, etc.) and by stating the city/neighborhood scoping. This adds meaning the schema alone does not convey.

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 first sentence states precisely what the tool returns: price per m² and typical apartment by area bracket, at city or neighborhood level. 'Só apartamentos' and the explicit range list differentiate it from general price tools like preco_m2 even without naming siblings.

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?

It gives a clear use case: comparing neighborhoods without mixing apartment sizes, and explains why the faixa dimension matters ('o bairro mais caro por m² muda conforme a faixa'). It does not name alternatives or state when not to use it, so it stops short of a 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.