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Glama

estimativa_safra

Current crop season estimate by state (area, production, yield).

Instructions

Current crop season estimate by state (area, production, yield).

    Products: soja, milho, arroz, feijao, trigo, algodao.

    Args:
        produto: Crop name (e.g. "soja", "milho")
        safra: Crop season in "YYYY/YY" format (default: latest season with data)
    

Input Schema

NameRequiredDescriptionDefault
safraNo
produtoYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.2

TDQS

B3.1/5.0
Behavior2/5

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 does not state whether this is a read-only query, whether any auth or rate limits apply, or how large the per-state response is. It discloses the output dimensions (area/production/yield by state), but that overlaps with the output schema and adds little behavioral context.

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

Conciseness4/5

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

Front-loads the core purpose in the first line, then lists products and parameters compactly with no filler. The Args block is a bit boilerplate but each entry carries information.

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

Completeness3/5

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

An output schema exists, so return values needn't be explained, and both parameters are documented. However, for a tool sitting among five other safra/production-related siblings, the absence of any disambiguation guidance leaves a real gap for an agent choosing between them.

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?

Schema coverage is 0%, so the description must compensate, and it does: produto is explained as the crop name with six concrete examples, and safra is given the 'YYYY/YY' format plus its default behavior. The only gap is that the crop list is not framed as a closed enum despite being presented as a fixed set.

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

Purpose4/5

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

States a specific verb+resource ('crop season estimate by state') and names the three measures returned (area, production, yield). The word 'Current' implicitly separates it from serie_historica_safra and producao_anual, but it never names a sibling explicitly.

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

Usage Guidelines2/5

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

No statement of when to use this versus progresso_safra, serie_historica_safra, or producao_anual, and no exclusions or prerequisites. The only usage-ish hint is that safra defaults to the latest season with data, which is a parameter default rather than routing guidance.

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