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Kyrodata — Brazil Trade, Crop & Commodity Data

by com.kyrodata
OverviewDiscussionsAdmin

Climate reading and physical crop loss

kyrodata_get_climate_reading
Read-onlyIdempotent

Current climate reading for a commodity: risk level, the measured production shock in % of the harvest, and the projected physical loss in tonnes per horizon (1, 3, 6 and 12 months) with its range. scope sets the geographic cut — 'br' (the default) reads the country, 'region:SE' a macro-region (N, NE, CW, SE, S), 'uf:MG' a single state — and moves only the risk level and the shock: the loss in tonnes stays national at any scope. A commodity without a validated model returns a descriptive reading with no verdict, and a season not yet measurable returns the previous one, each flagged in the caveats. Climate here predicts PRODUCTION. The price question for the same hub is kyrodata_get_hub_summary, and the published season-by-season balance sheet is kyrodata_get_supply_demand_balance. Credit class: level (any level tool in a 60-second session = 2 credits; a session is capped at 3).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
hubYesWhich commodity hub to read. Climate forecasts PRODUCTION, never price.
scopeNoGeographic cut: `br` for the whole country, `region:<N|NE|CW|SE|S>` for a macro-region, or `uf:<XX>` for a state. Defaults to the country.
response_formatNoHow much of the answer to return. `concise` (the default) carries the headline figures; `detailed` adds the row-level series behind them and counts against the export quota.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYesRaw numbers behind the text.
memoYestrue = identical call in the last 10 min, served again: 0 credits.
rowsNoTable rows; detailed only, capped per tool.
errorNoFailure message when status = error.
linksYesscreen = product page with these numbers.
deniedNoWhen status = denied: reason, feature, upgradeUrl.
statusYesok = data; denied = plan; error = failure or timeout.
windowNoLike-for-like window: from, to (YYYY-MM), label, months, crossesSeason.
caveatsYesReading caveats.
creditsYescharged, balance (null = unlimited), resetAt, session {charged, endsAt} of the 60-s billing session.
sourcesYesPer source: label, nameable, asOf.
dataVersionYesIdentity of the data that answered.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / hub / enum
      Previous value: -[
-  "sugar",
-  "beef",
-  "coffee",
-  "ethanol",
-  "chicken",
-  "corn",
-  "soybean",
-  "pork",
-  "cotton",
-  "cocoa",
-  "orange-juice",
-  "wheat",
-  "rice"
-]New value: +[
+  "sugar",
+  "beef",
+  "ethanol",
+  "chicken",
+  "pork",
+  "cocoa",
+  "orange-juice",
+  "wheat"
+]
  2. Changed3 schema fields changed
    • addedInput schema / properties / hub / description
      Added value: +"Which commodity hub to read. Climate forecasts PRODUCTION, never price."
    • addedInput schema / properties / response_format / description
      Added value: +"How much of the answer to return. `concise` (the default) carries the headline figures; `detailed` adds the row-level series behind them and counts against the export quota."
    • addedInput schema / properties / scope / description
      Added value: +"Geographic cut: `br` for the whole country, `region:<N|NE|CW|SE|S>` for a macro-region, or `uf:<XX>` for a state. Defaults to the country."
  3. First observed

TDQS

A4.9/5.0
Behavior5/5

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

Beyond the readOnlyHint/idempotent/destructive annotations, the description reveals important behaviors: scope changes only the risk/shock but not national loss tonnage, missing validated models yield a descriptive reading with no verdict, and an unmeasurable season falls back to the previous one with caveats. It also discloses the credit cost cap, which annotations do not provide.

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 core output is front-loaded in the first sentence, followed by scope semantics, edge cases, production clarification, alternatives, and credit class. Each sentence earns its place and there is no filler despite the length needed to explain a nuanced tool.

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

Completeness5/5

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

With an output schema present, return values are already covered. The description fills the remaining gaps: parameter interactions, edge cases, fallback behavior, sibling routing, and cost semantics. A calling 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.

Parameters4/5

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

Schema coverage is 100%, so the baseline is 3. The description goes further by explaining subtle behavior of the scope parameter—moving only risk level and shock while loss stays national—and reinforcing that hub is about production, not price. This adds real meaning beyond the schema descriptions.

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 opens with a specific verb and resource: 'Current climate reading for a commodity', then enumerates the concrete outputs: risk level, production shock in % of harvest, and projected physical loss in tonnes per horizon. It also distinguishes itself from siblings by explicitly naming kyrodata_get_hub_summary and kyrodata_get_supply_demand_balance, so an agent can tell what this tool is not.

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

Usage Guidelines5/5

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

It states the core use case—climate-driven production reading—and explicitly gives alternatives for price questions (kyrodata_get_hub_summary) and the balance sheet (kyrodata_get_supply_demand_balance). It also says 'Climate here predicts PRODUCTION', effectively telling the agent when not to use this tool. This is explicit when/when-not guidance.

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

All Kyrodata — Brazil Trade, Crop & Commodity Data toolsInspect
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