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

Annotations already declare readOnly, idempotent, openWorld and non-destructive, so the bar is lower; the description still adds real value by defining freshness (when a price was last read), the 7-day read share, median read time, and a staleness flag for catalogs. It also discloses cost behavior (1 credit, no data = no charge), which is useful context not present in 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?

Front-loaded with the core purpose, then freshness semantics, then billing. Dense but each clause carries information; the billing aside is slightly tangential but short.

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?

With no output schema, the description does the heavy lifting on return values and largely succeeds: it enumerates the statistics, the sample payload, and the freshness fields. Only the shape of individual product samples remains unspecified.

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 all three parameters are already documented. The description reinforces that `query` is an optional product-name filter and that `limit` governs the sample, but adds no format or edge-case detail beyond the 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?

States a specific verb+resource: price statistics (min/max/avg/median) plus recent product samples for a brand, with an optional name filter. It is clearly distinguishable from price-adjacent siblings like get_most_discounted_products or get_discount_frequency_and_depth, though it never explicitly names an alternative.

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?

'Optionally filtered by product-name query' implies use, but there is no explicit when-to-use/when-not guidance against the many other pricing and catalog siblings. The plan/credit sentence is billing context, not selection guidance.

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