Retail Forecast

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

The annotations already establish that the operation is read-only, idempotent, and non-destructive. The description adds specific authentication context—explaining the optional API key mechanism, its location (headers or query parameter), and the Pro tier selection behavior—which is valuable behavioral context not present in the structured 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 appropriately brief at only two sentences and avoids verbosity. However, the first sentence is merely a noun phrase without a verb ('Retail sales and...'), which front-loads ambiguity rather than clarity, slightly undermining the structural efficiency.

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?

While the output schema absolves the description from explaining return values, the description inadequately documents the parameters (failing to mention 'timeframe' or explain 'indicator' explicitly) and lacks a clear statement of action. Only the API key information provides complete behavioral context.

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?

With 0% schema description coverage, the description partially compensates by mapping the cryptic enum values to human-readable concepts ('Retail sales' maps to 'advance_retail_and_food_services_sales', etc.). However, it fails to document the 'timeframe' parameter entirely or explicitly link the mentioned concepts to the 'indicator' parameter.

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 provides only a noun phrase listing data sources ('Retail sales and University of Michigan consumer sentiment') without specifying the action performed (retrieve, get, forecast). It fails to distinguish this tool from its 'forecast_' siblings beyond listing specific subject matter, and omits the verb that would clarify the operation.

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?

No explicit guidance is provided regarding when to select this tool versus sibling alternatives like forecast_commodities or forecast_gdp. The description mentions specific indicators but does not clarify selection criteria, prerequisites, or explicit when-to-use conditions.

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