US Government Open Data MCP

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It adequately describes the data scope (quarterly, FDIC-insured banks) and unit conventions (dollar values in thousands), but lacks details on rate limits, authentication requirements, error conditions, or response format. The description doesn't contradict any annotations (none exist), but leaves significant behavioral aspects unspecified.

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 efficiently structured in three sentences: purpose statement, data field enumeration, and key operational details (filtering and units). Every sentence adds essential information with zero wasted words, making it easy to parse and understand 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 moderate complexity (6 parameters, no output schema, no annotations), the description provides adequate coverage of purpose and basic usage but lacks details on behavioral constraints, response format, and error handling. It's complete enough for basic understanding but would benefit from additional context about limitations or typical use cases.

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%, providing detailed documentation for all 6 parameters. The description adds marginal value by mentioning filter types (CERT, STALP) and data fields in a summary format, but doesn't provide additional syntax, format, or semantic details beyond what's already in the schema descriptions. This meets the baseline expectation when schema coverage is complete.

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 verb ('Get') and resource ('quarterly Call Report financial data for FDIC-insured banks'), and distinguishes it from sibling tools by focusing on FDIC financial data rather than BEA, BLS, or other agency datasets. It explicitly lists the data fields included (assets, deposits, net income, ROA, ROE, loan loss reserves).

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 context by mentioning filtering capabilities (CERT number or STALP) and data format (dollar values in thousands), but does not explicitly state when to use this tool versus alternatives. No sibling tool comparisons or exclusion criteria are provided, leaving usage decisions to inference.

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