US Government Open Data MCP

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

Annotations provide readOnlyHint=true, indicating a safe read operation. The description adds context about the data coverage (borders, monthly granularity, specific measures) and scope (ports, states), which is useful beyond the annotations. However, it does not disclose behavioral traits like rate limits, authentication needs, or pagination details (though limit parameter hints at result control).

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 front-loaded with the core purpose in the first sentence, followed by clarifying details in two additional sentences. Each sentence adds specific value (data types, borders, granularity) with zero waste, making it efficient and well-structured for quick comprehension.

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 (5 parameters, no output schema), the description adequately covers the data scope and usage context. With annotations indicating read-only access and a detailed input schema, the description provides sufficient context for an agent to understand what the tool does and what data to expect, though it could benefit from more explicit usage guidance.

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%, with detailed descriptions and enums for parameters like 'measure' and 'border'. The description adds minimal semantic value beyond the schema, mentioning 'by port, state, and measure type' which aligns with parameters but does not provide additional syntax or format details. Baseline 3 is appropriate given the comprehensive schema.

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 action ('Get') and resource ('border crossing data'), specifies the scope ('U.S. ports of entry'), and lists the data categories ('trucks, personal vehicles, pedestrians, train passengers, containers'). It distinguishes itself from sibling tools by focusing on border crossing data, unlike other tools that cover topics like GDP, employment, or climate data.

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 implies usage by specifying the data scope ('U.S.-Mexico and U.S.-Canada borders', 'Monthly data by port, state, and measure type'), but does not explicitly state when to use this tool versus alternatives. No exclusions or prerequisites are mentioned, leaving the agent to infer context from the data description alone.

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