BEA — US Real GDP Growth

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is fully covered. The description adds useful context about the data being official BEA national accounts data and the specific NIPA table, but does not disclose behaviors like default year range behavior (LAST5), whether quarterly data is seasonally adjusted, or how missing years are handled. With annotations covering safety, a 3 is appropriate.

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 and front-loads the core action and data source. The first sentence is dense but informative; the second lists available series; the third gives use cases. It is slightly verbose with the use-case sentence, but every sentence earns its place. No wasted words.

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 read-only data retrieval tool with 2 fully documented parameters, an output schema, and safety annotations, the description is nearly complete. It covers what data is returned (percent-change series for major GDP components), the source, and use cases. It could mention the default behavior (LAST5 years, annual frequency) but the schema already documents defaults. The output schema covers return values, so nothing critical is missing.

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 both parameters (year and frequency) are fully documented in the schema. The description adds the context that the data is percent change at annual rate and lists the series available, but does not add parameter-specific meaning beyond the schema. Baseline 3 is correct when the schema does the heavy lifting.

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 ('Retrieve'), a precise resource (BEA NIPA Table T10101 Fisher Quantity Index percent change at annual rate), and enumerates the exact series available (total GDP, PCE, investment, exports, imports, government spending). It also names the data source (BEA) and use cases, making it clearly distinguishable from sibling tools like bea.national.personal_income or abs.economy.gdp.

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 for when to use this tool ('Use for macro analysis, economic forecasting, and recession detection') and specifies the data source and table. However, it does not explicitly state when NOT to use it or name alternative tools (e.g., bea.regional.state_gdp for state-level data, or abs.economy.gdp for Australian GDP). The use-case guidance is helpful but lacks explicit exclusions.

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