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

The description explicitly states the tool is read-only, idempotent, a live GET against the public IBGE Nomes API, and that it returns a Markdown table. This adds meaningful behavioral context beyond the annotations, and there is no contradiction.

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 well-structured with a purpose statement, feature bullets, examples, and a behavior note. It is front-loaded, uses high-signal examples, and every section earns its place without redundant padding.

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?

Together with the fully described schema, enums, output schema, and annotations, the description covers modes, required parameters, optional filters, examples, API behavior, return format, and safety. An agent has everything needed to select and invoke the tool 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 input schema already describes all six parameters with 100% coverage, including enums, defaults, and constraints. The description adds value by showing cross-parameter usage through examples, clarifying comma-separated names, and documenting the 1930-2010 decade range, which goes beyond the schema.

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 opening sentence, 'Queries name frequency and rankings in Brazil (IBGE),' names the exact verb, resource, and scope. It then enumerates two distinct query modes (frequencia and ranking), which clearly differentiates it from sibling tools that cover censuses, cities, indicators, and other IBGE datasets.

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 provides clear context through mode-specific feature lists and concrete examples for frequency, ranking, and filtering. It does not explicitly name alternatives or say when not to use this tool, so it stops short of a full when-to-use/when-not-to-use guide.

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