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Magpie — USDA Agricultural Data for AI Agents

get_crop_condition

Get current NASS crop condition ratings (% excellent/good/fair/poor/very poor)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
commodityNoCommodity (CORN, SOYBEANS, WHEAT)CORN
geographyNoUS for national, or state code (IA, IL, etc.)US

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.2/5.0
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 behavioral burden, and it discloses little beyond a bare read. It does not say whether the data is latest-only vs historical, how frequently NASS updates it, or whether any auth/rate constraints apply. 'current' is the only behavioral hint.

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?

One front-loaded sentence with zero filler that names the source, the metric, and the value categories. Nothing could be trimmed without losing information.

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?

For a simple two-parameter read tool with fully documented schema and no output schema, the description says what the tool returns well enough to call it. Only minor gaps remain, such as the lack of any note on freshness or comparison against sibling condition/progress tools.

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

Parameters3/5

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

Schema coverage is 100% — both optional parameters (commodity, geography) with their allowed values and defaults are fully documented in the schema. The description adds no additional meaning about the parameters, so the baseline 3 is appropriate.

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 (Get) and resource (NASS crop condition ratings) and even specifies the data shape (% excellent/good/fair/poor/very poor), which helps distinguish it from nearby siblings like get_crop_stats and get_crop_progress. It does not explicitly name a sibling to route against, so it falls just short of a 5.

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?

There is no when-to-use guidance, no prerequisites, and no mention of the alternatives (get_crop_stats, get_crop_progress) that an agent might confuse this with. Usage must be inferred entirely from the name.

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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