US Government Open Data MCP

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states 'Get livestock data,' implying a read-only operation, but doesn't clarify if it's a query, API call, or data retrieval with specific constraints (e.g., rate limits, authentication needs, data freshness). For a tool with no annotations and four parameters, this lack of behavioral context is a significant gap, though not contradictory.

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?

The description is extremely concise and front-loaded, with two sentences that directly state the tool's function and commodities. Every word earns its place, with no wasted text or redundancy. It's appropriately sized for a straightforward data retrieval tool, making it easy for an agent to parse quickly.

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?

Given the tool's complexity (4 parameters, no output schema, no annotations), the description is incomplete. It lacks information on return values, error handling, data formats, or any behavioral traits. While the schema covers parameters well, the absence of output details and behavioral context makes it insufficient for an agent to fully understand how to use the tool effectively, especially compared to more detailed sibling tools in the list.

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?

Schema description coverage is 100%, so the schema already documents all parameters with descriptions and constraints. The description adds minimal value by listing commodities ('CATTLE, HOGS, CHICKENS, MILK, EGGS'), which partially overlaps with the 'commodity' parameter's schema description. It doesn't explain parameter interactions (e.g., how 'state' and 'year' affect results) or provide examples, so it meets the baseline for high schema coverage without enhancing understanding.

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?

The description clearly states the tool's purpose with specific verbs ('Get') and resources ('livestock data — inventory, slaughter, production'), and lists the commodities covered. It distinguishes itself from sibling tools by focusing on USDA livestock data, which is distinct from the many BEA, BLS, CDC, and other datasets in the sibling list. However, it doesn't explicitly differentiate from other USDA tools like 'usda_crop_data' or 'usda_prices' beyond the 'livestock' focus.

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?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools (e.g., 'usda_crop_data' for crop data, 'usda_prices' for price data) or other data sources in the list. There's no context about prerequisites, limitations, or typical use cases, leaving the agent to infer usage based on the name and parameters alone.

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