pp_get_price_forecast

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

Annotations already declare readOnly, idempotent, non-destructive and open-world, so the safety profile is covered. The description adds genuinely non-obvious behavior: a missing forecast still returns HTTP 200 with a null body and the reason in the X-Forecast-Reason header. That is real value beyond the structured fields.

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?

Three short sentences, each carrying distinct information: what the tool does, the null-not-error contract, and the anti-retry instruction. Front-loaded and free of 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?

No output schema exists, and the description covers the one surprising return case (null forecast plus reason header) that an agent would otherwise mishandle. It does not describe the shape of a successful forecast, which is a minor remaining gap for a read tool.

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 0% and the single parameter has no description in the schema. The description says the forecast is for 'one product', which maps loosely to product_id, but adds no format, ID namespace, or validity detail to compensate for the coverage gap.

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?

States a specific verb and resource: 'Server-side backtested price forecast for one product'. The domain (price forecasting) is clearly distinct from the deals/products/categories siblings, though the description never names an adjacent tool to differentiate against.

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?

There is no explicit when-to-use-vs-alternative guidance, but the description does give one actionable usage rule: a null forecast is not an error and should not be retried. That covers the edge case but leaves the general call context implied.

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