Historical annual crop production by state (IBGE PAM).
Historical annual crop production by state (IBGE PAM).
Products: soja, milho, arroz, feijao, trigo, algodao, cafe, cacau, cana, mandioca, laranja.
Args:
produto: Crop name (e.g. "soja", "milho")
ano: Reference year (default: previous year)
| Name | Required | Description | Default |
|---|---|---|---|
| ano | No | ||
| produto | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Changes observed during successful MCP inspections.
v0.1.2Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full behavioral burden, and it discloses little beyond the topic and default year behavior. It says nothing about data granularity (state-level only?), geographic filtering, permissions, rate limits, or freshness of the historical series.
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?
Purpose is front-loaded in the first line, followed by the useful enumerated product list and a compact Args section. Every line earns its place, though the inline bullet-style product list makes it slightly longer than strictly necessary for a two-parameter tool.
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?
An output schema exists, so return values do not need explaining, and both parameters are documented. However, for a tool sitting among many crop-related siblings, the missing differentiation and absence of any behavioral or access context leaves gaps relative to the complexity of the surrounding tool set.
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?
With 0% schema description coverage, the description compensates well: it enumerates the eleven accepted crop names for 'produto' and explains that 'ano' is the reference year defaulting to the previous year. One inconsistency remains — the schema declares ano default as 0 while the description says 'previous year' — but the value added over the bare schema is substantial.
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?
States a specific verb and resource: historical annual crop production by state, sourced from IBGE PAM. It is clear what the tool returns, though it does not explicitly distinguish itself from siblings like estimativa_safra, progresso_safra, or serie_historica_safra that inhabit the same crop-data domain.
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?
No when-to-use or when-not-to-use guidance is given, and no sibling is named as an alternative. An agent must infer from the phrase 'historical annual' that this is retrospective annual production rather than the forecast/progress data offered by other crop tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.