get_average_income

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

No annotations are provided, so the description carries the full burden. It only states what the tool returns without disclosing behavioral traits such as data freshness, limitations (e.g., only formal workers), or whether it is read-only. The information is minimal.

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, concise sentence that front-loads the core information: what the tool gets and its scope. No unnecessary 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?

For a simple, parameterless tool without an output schema, the description is relatively complete. It specifies the metric, geographic scope, and data source. However, it lacks minor context like the reference year being 2022 in the description (though present in parentheses) and any notes on data coverage.

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 no parameters (100% coverage trivially). The description adds value by explaining what data is returned, which is sufficient for a parameterless tool. There is no need for parameter details.

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 the verb 'Obtém' (gets), the resource 'renda nominal média e mediana mensal do trabalhador', and the scope 'Natal (Censo 2022)'. It is specific and distinguishes from sibling tools like 'get_neighborhood_income' which is per neighborhood.

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 usage for getting city-wide income data in Natal, but provides no explicit guidance on when to use this tool versus alternatives like 'get_neighborhood_income' or when not to use it. No exclusions or context are given.

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