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

With no annotations, the description carries the burden and does well: it discloses the data provenance (POF 2017-2018 do IBGE), the update year (2026), the estimated nature of the figures, and explicitly warns it is not IBGE-published data. It does not describe return shape or precision limits, which keeps it short of a 5.

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?

One dense sentence that front-loads the core purpose, then the returned categories, then the provenance caveat. No filler and nothing repeated from structured fields.

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?

No output schema exists, and the description compensates by listing the returned cost categories; the provenance disclaimer covers the main trust concern. It is complete for calling the tool, though it says nothing about units, currency, or granularity of the returned figures.

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 description coverage is 100% with a single, self-explanatory 'city' parameter (with examples in the schema). The description adds no syntax or format detail beyond the schema, so the baseline 3 applies.

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?

States a specific verb and resource ('Retorna custo de vida ESTIMADO em uma cidade brasileira') and enumerates the exact categories returned (aluguel, alimentação, transporte, saúde, educação, lazer). This distinguishes it cleanly from siblings like get_average_salary or calculate_rent_affordability.

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?

Scope is implied clearly enough (a Brazilian city's cost of living), but there is no explicit when-to-use guidance and no routing to alternatives such as get_average_salary or calculate_rent_affordability, despite a very large sibling set. Usage is inferable but not guided.

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