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

No annotations are provided, so the description carries the full burden. It discloses key behavioral traits: 'first-release vs latest value with a revised flag (revisions never pose as print-day numbers)', 'surprise vs a labeled expectation', and includes a next release date. This proactively addresses data reliability and provenance. It does not mention rate limits or authentication (though it notes pricing via x402).

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 front-loaded with the core purpose: 'Real GDP growth (BEA, quarterly): latest print, revisions, surprise.' It then elaborates with necessary details and ends with HTTP method, price, and docs link. It is appropriately sized for its complexity, though the parenthetical sentence is slightly dense. Every sentence adds value.

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 no annotations, no output schema, and 0 parameters, the description does a thorough job of explaining what the tool returns (first-release vs latest, revised flag, surprise, next release, 12-observation series) and how it relates to the generic econ_series. It includes access details (GET endpoint, price, docs). It lacks explicit authentication info, but pricing via x402 implies a payment flow.

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?

Parameter count is 0, so baseline is 4. The description does not add parameter semantics (none needed), but it does clarify the output structure: 'same shape as /v1/econ/:series' and lists returned fields (first-release vs latest, revised flag, surprise, next release date, 12-observation mini-series). This adds value beyond the empty schema.

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+resource: 'Latest Real GDP growth print from the BEA via FRED/ALFRED'. It names the source (BEA via FRED/ALFRED), the metric (Real GDP growth), and the frequency (quarterly). It also explicitly distinguishes itself from the sibling econ_series with 'Same shape as /v1/econ/:series bound to gdp-growth', making clear it is not the generic series tool.

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 clearly indicates when to use this tool: for the latest real GDP growth print with revisions, surprise, next release date, and mini-series. It references the sibling econ_series to clarify scope. However, it does not provide explicit when-not-to-use guidance or name alternative tools for other economic indicators (though sibling names like econ_series_cpi imply alternatives).

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