bea_nipa_underlying_detail

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

Annotations already declare readOnlyHint=true, and the description adds important behavioral context: the BEA caution that 'these detailed estimates are lower quality than published aggregates.' This goes beyond annotations by disclosing data quality concerns.

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 three sentences, each earning its place: purpose, quality warning, and concrete examples. It is front-loaded with the main action and avoids any filler.

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 (3 parameters, no output schema), the description covers purpose, data quality, and discovery path. It could optionally mention output format or typical use cases, but the provided information is sufficient.

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%, but the description adds value by listing common table names, explaining frequency codes (A, Q, M), and clarifying year options (LAST5, ALL, X). This supplements the schema's brief parameter descriptions.

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 starts with 'Get NIPA underlying detail data — more granular national account breakdowns.' This clearly states the verb (Get) and the resource (NIPA underlying detail data), and distinguishes from sibling tools like bea_gdp_national by emphasizing 'more granular' and 'underlying detail'.

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 context by mentioning common tables and directing users to bea_dataset_info for discovery. However, it does not explicitly state when to use this tool vs. alternatives (e.g., when aggregates suffice) or when not to use it, which would strengthen guidance.

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