bea_nipa_underlying_detail

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds a useful data-quality caution (lower quality than aggregates) and hints at table selection, which goes beyond the annotations. It does not describe response format or pagination, but given the annotations' coverage, this is acceptable.

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 concise and well-organized: it states the core purpose first, adds a caution, then lists common tables and a discovery tip. No filler or redundant sentences, and it is front-loaded with the most important information.

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?

For a tool with 3 optional parameters, no output schema, and a clear sibling set, the description provides enough to call it correctly: it explains the data scope, gives examples, and points to discovery. It could be improved by mentioning the response format, but the absence is not critical given the annotations and the tool's simple parameter set.

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 coverage is 100%, so the schema documents each parameter. The description adds value by listing common tables and instructing users to use bea_dataset_info for discovery, which directly aids the table_name parameter. This extra context raises it above the baseline of 3.

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 states a specific verb ('Get') and resource ('NIPA underlying detail data') and adds a clarifying phrase ('more granular national account breakdowns') that differentiates it from sibling BEA tools like bea_gdp_national which likely provide aggregates. It also lists common tables, making its purpose unmistakable.

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?

It provides clear context by explaining the tool returns underlying detail and warns that these are lower quality than published aggregates, implying that for aggregates one should use other BEA tools. It also directs users to bea_dataset_info for discovering all tables. However, it does not explicitly name alternative tools or state when not to use this tool, so it falls short of a 5.

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