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cyntrica

Gov Data MCP

by cyntrica

usda_livestock

Read-only

Retrieve USDA livestock inventory, slaughter, production, and sales data for cattle, hogs, chickens, milk, and eggs. Filter by year, state, or category.

Instructions

Get livestock data — inventory, slaughter, production. Commodities: CATTLE, HOGS, CHICKENS, MILK, EGGS

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
yearNoYear
stateNoState code. Omit for national
categoryNoINVENTORY, PRODUCTION, SALES
commodityYesCATTLE, HOGS, CHICKENS, MILK, EGGS
Behavior3/5

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

Annotations declare readOnlyHint=true, covering the safety profile. The description adds the type of data returned (inventory, slaughter, production) but does not disclose other behavioral aspects such as pagination, output format, or rate limits. With annotations present, this is adequate but not richly transparent.

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 description is extremely concise: two short sentences that front-load the core purpose and immediately list the allowed commodities. Every word earns its place without unnecessary filler.

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 filtered data retrieval tool with full schema coverage and a read-only annotation, the description is mostly sufficient. The main gap is the unresolved discrepancy between the mentioned 'slaughter' and the category enum's 'SALES', plus lack of note about output format, but the essential contexts (commodities, data types) are present.

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%, so the baseline is 3. The description reiterates the commodity list and adds 'slaughter', but the category schema enum is INVENTORY, PRODUCTION, SALES, making 'slaughter' a potential mismatch. It does not clarify parameter formats such as state codes or year ranges beyond what the schema already provides.

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 clearly states the tool's function with a specific verb ('Get') and resource ('livestock data'), enumerates the data types (inventory, slaughter, production), and lists the supported commodities (CATTLE, HOGS, CHICKENS, MILK, EGGS). This distinguishes it from sibling tools like usda_crop_data or usda_prices.

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

Usage Guidelines3/5

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

The description implies usage for any livestock-specific data retrieval but does not explicitly state when to prefer this tool over alternatives or mention exclusions. There is no direct guidance on when not to use it (e.g., for crop data use usda_crop_data), leaving usage context mostly inferred.

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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