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 mentions the tool is for 'overview metrics' and implies aggregation, but does not disclose critical behavioral traits such as whether this is a read-only operation, potential rate limits, authentication requirements, or what the output format looks like (especially since there is no output schema). This leaves significant gaps for an agent to understand how to use it effectively.

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 highly concise and well-structured: two sentences that efficiently convey the purpose and usage without any wasted words. The first sentence states what the tool does, and the second provides context for when to use it, making it front-loaded and easy to parse.

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 complexity (6 parameters, no annotations, no output schema), the description is moderately complete. It covers the purpose and basic usage but lacks details on behavioral aspects (e.g., safety, output format) and does not fully compensate for the absence of annotations or output schema. It is adequate for a read-like tool but could be more comprehensive to guide an agent fully.

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?

The input schema has 100% description coverage, with each parameter documented (e.g., filters, fields, sort_by). The description adds minimal value beyond the schema by implying the types of filters (e.g., state/year) and fields (e.g., total banks, deposits, assets), but does not provide detailed syntax or examples beyond what the schema already states. This meets the baseline of 3 for high schema coverage.

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: 'Get aggregate banking statistics — industry totals by state or charter type.' It specifies the verb ('Get'), resource ('aggregate banking statistics'), and scope ('by state or charter type'). However, it does not explicitly distinguish this tool from its sibling tools (e.g., fdic_deposits, fdic_financials), which limits the score to 4 instead of 5.

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 some implied usage context: 'Useful for overview metrics: total banks, deposits, assets by state/year.' This suggests when to use the tool (for overview metrics) but does not explicitly state when not to use it or name alternative tools (e.g., fdic_financials for detailed data). The guidance is helpful but lacks explicit exclusions or comparisons, resulting in a score of 3.

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