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clima

Retrieve recent climate data for Brazilian states, including temperature, precipitation, radiation, humidity, and wind. Specify state abbreviation, year, and daily or monthly aggregation.

Instructions

Recent climate data by state (temperature, precipitation, radiation, humidity, wind).

    Valid states: AC, AL, AM, AP, BA, CE, DF, ES, GO, MA, MG, MS,
    MT, PA, PB, PE, PI, PR, RJ, RN, RO, RR, RS, SC, SE, SP, TO.

    Args:
        uf: State abbreviation (e.g. "MT", "PR", "RS")
        ano: Year (default: current year)
        agregacao: "diario" or "mensal" (default: "mensal")
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ufYes
anoNo
agregacaoNomensal

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations are provided, so the description carries the burden. It describes the data fields and parameters but does not disclose whether the operation is read-only, any limitations on data range, or error behavior. It is minimally transparent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise and well-structured: one line for purpose, a bulleted list of valid states, and a clear parameter section. Every sentence adds value with no redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the presence of an output schema, the description does not need to detail return values. It covers purpose, parameters, and valid inputs adequately. Could mention data coverage (recent years) or output format but overall complete for a simple retrieval tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage, the description fully compensates by explaining each parameter's meaning, including a list of valid state abbreviations, default values, and allowed values for 'agregacao'. This adds significant value beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Recent climate data by state' with specific data types (temperature, precipitation, radiation, humidity, wind), providing a specific verb (retrieve) and resource (climate data) that distinguishes it from siblings.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description lists valid states and default values but does not explicitly mention when to use this tool versus alternatives (e.g., 'desmatamento' or 'balanco'). It implies use for climate queries but lacks exclusions or comparison.

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

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