territorio_municipio

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

No annotations are present, so the description carries the full disclosure burden. It does a good job by stating that names are matched without accents and partially, that 7-digit IBGE or 6-digit DATASUS/CNES codes are accepted, and that both codes are returned. It stops short of describing result cardinality, ambiguity handling, or data caveats, but the disclosed input/output behaviors are substantially informative.

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 definition is a single dense, front-loaded sentence that leads with the core resource and data contract, then moves to input formats and a batch tip. Every clause adds useful information, and there is no filler or repetition of schema details.

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?

Even without an output schema, the description enumerates the main returned content (regional hierarchy, UF, population, PIB, and both codes) and the accepted identifier variants, which is enough to invoke the tool correctly. The main gap is that output shape and behavior for ambiguous or unknown names are not stated, but these are minor for a lookup tool with clear schema 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?

Schema description coverage is 100%, so the baseline is 3. The description adds real meaning by clarifying accepted canonical forms (unaccented/partial names, 7-digit IBGE, 6-digit DATASUS/CNES) and by framing `codes` as the batch-resolution path, which goes beyond the schema's generic list description. It leaves `uf` and `limit` to the schema, which is acceptable given their clear schema descriptions.

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 names the resource (Brazilian municipality) and specifies its data content: regional hierarchy, UF, population, Census 2022 and municipal PIB. It also makes the lookup behavior explicit by describing accepted identifiers and returning both IBGE and DATASUS/CNES codes, which clearly distinguishes it from sibling tools like territorio_regiao and territorio_data_caveats.

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?

There is a useful usage tip for batching ('Use `codes` para resolver muitos de uma vez'), and the municipality-focused wording implies when to use the tool. However, it never explicitly contrasts this tool with territorio_regiao or territorio_data_caveats, nor states when not to use it, so tool-selection guidance remains implicit rather than explicit.

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