Kyrodata — Commodity Price Forecasts & Trade Intelligence

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

Name	Required	Description
`hub`	Yes	Which commodity hub to read. Climate forecasts PRODUCTION, never price.
`scope`	No	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.
`response_format`	No	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.

Output Schema

TableJSON Schema

Name	Required	Description
`data`	Yes	Raw numbers behind the text.
`memo`	Yes	true = identical call in the last 10 min, served again: 0 credits.
`rows`	No	Table rows; detailed only, capped per tool.
`error`	No	Failure message when status = error.
`links`	Yes	screen = product page with these numbers.
`denied`	No	When status = denied: reason, feature, upgradeUrl.
`status`	Yes	ok = data; denied = plan; error = failure or timeout.
`window`	No	Like-for-like window: from, to (YYYY-MM), label, months, crossesSeason.
`caveats`	Yes	Reading caveats.
`credits`	Yes	charged, balance (null = unlimited), resetAt, session {charged, endsAt} of the 60-s billing session.
`sources`	Yes	Per source: label, nameable, asOf.
`dataVersion`	Yes	Identity of the data that answered.

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedOct 18, 2026

changedInput schema / properties / hub / enum

Previous value: -[
-  "sugar",
-  "beef",
-  "ethanol",
-  "chicken",
-  "pork",
-  "cocoa",
-  "orange-juice",
-  "wheat"
-]New value: +[
+  "sugar",
+  "beef",
+  "ethanol",
+  "chicken",
+  "pork",
+  "cocoa",
+  "orange-juice",
+  "wheat",
+  "rice"
+]

Changed1 schema field changedSep 24, 2026

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"
+]

Changed3 schema fields changedSep 7, 2026

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."

First observedSep 6, 2026

TDQS

A4.8/5.0

Behavior5/5

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

Annotations already establish it is a safe, idempotent read, so the description's job is additive context — and it delivers: scope moves only the risk level and shock while tonnage stays national, unvalidated commodities return a descriptive reading with no verdict, unmeasurable seasons return the previous one, each flagged in caveats, plus credit cost (2 credits, 3-credit session cap). That is substantive non-obvious behavior beyond the structured fields.

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-loaded with the operation and its outputs, then scope semantics, then exception handling, then routing and credits — a logical order with essentially no filler. The single dense paragraph is long but every sentence carries operational information; light structural separation (e.g., breaking routing/credits out) would improve scanning.

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?

For a 3-parameter tool with an output schema, the description covers what structured data cannot: scope-dependent field behavior, degraded/fallback responses, caveat flagging, sibling routing, and billing. Nothing an agent needs to select or call it correctly appears to be missing.

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 description coverage is 100%, so the baseline is 3; the description earns above it by explaining that `scope` affects only risk level and shock while the losses remain national, and that `detailed` response_format exposes row-level series and consumes export quota. It stops short of documenting every accepted scope token form beyond the examples given.

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?

Names a specific verb and resource ('current climate reading for a commodity') and enumerates the payload: risk level, production shock in % of harvest, projected physical loss in tonnes per horizon with range. It explicitly separates itself from siblings by naming the price tool (kyrodata_get_hub_summary) and the balance-sheet tool (kyrodata_get_supply_demand_balance), and reinforces that climate predicts PRODUCTION, not price.

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?

Gives explicit routing rules: use kyrodata_get_hub_summary for the price question on the same hub, kyrodata_get_supply_demand_balance for the published season-by-season balance. It also states the fallback conditions (no validated model, unmeasurable season) so the agent knows what to expect rather than seeking another tool.

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

All Kyrodata — Commodity Price Forecasts & Trade Intelligence tools Inspect

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