US Government Open Data MCP

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

Annotations already declare readOnlyHint=true, so the agent knows this is a safe read operation. The description adds useful context about data frequency options (A=annual, QSA=quarterly seasonally adjusted, QNSA=not adjusted) and indicator examples, which helps understand what data is available. However, it doesn't disclose behavioral traits like rate limits, authentication needs, or data freshness that would be valuable beyond the annotations.

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 well-structured and appropriately sized. It starts with the core purpose, expands with scope details, provides indicator examples, and ends with frequency codes. Every sentence adds value, though the indicator examples could be slightly more concise. The information is front-loaded with the most important details first.

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 that annotations cover the read-only nature and the schema provides 100% parameter documentation, the description does a good job of providing additional context about what data is available and how it's structured. However, without an output schema, the description could benefit from mentioning what the return data looks like (time series format, units, etc.). The indicator examples help compensate for this gap.

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 all parameters are well-documented in the schema itself. The description adds some value by providing indicator examples (BalGds, BalServ, etc.) and frequency codes that complement the schema, but doesn't add significant semantic meaning beyond what's already in the parameter descriptions. The baseline of 3 is appropriate given the comprehensive 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 U.S. international transactions (balance of payments) data.' It specifies the exact resource (U.S. international transactions data) and verb (get/retrieve). It distinguishes from siblings like 'bea_international_investment' and 'bea_intl_services_trade' by focusing specifically on balance of payments transactions rather than investment positions or services trade details.

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 clear context about what data is tracked ('all transactions between U.S. and foreign residents') and gives indicator examples that help users understand when to use specific parameters. However, it doesn't explicitly state when to use this tool versus alternatives like 'bea_dataset_info' (mentioned in schema) or other BEA siblings, nor does it provide exclusion criteria for when not to use it.

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