sephora_product_questions

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

Annotations are absent, so the description carries the full burden of explaining behavior. It does disclose the response granularity (one page, each question with all answers) and the return fields, which is helpful. However, it omits other behavior an agent might need, such as pagination metadata, rate limits, or whether the response can be empty.

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 compact, efficient, and front-loaded with the core purpose in the first sentence. Every sentence adds unique information: the resource being accessed, the return fields, pagination behavior, and the exact linkage of product_id to another tool's output. There is no redundant or filler content.

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 tool with only two parameters, no annotations, and no output schema, the description covers the most important context: what is returned, the identity of the required parameter, and the new product_group_id mapping. It does not explain the page size or how many results appear per page, which is a minor gap but not a fatal one for an agent to call the tool correctly.

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?

The schema already provides 100% coverage by describing product_id and page with defaults. The description goes beyond the schema by explaining that product_id is the Sephora productGroupID and maps it to the same value returned by /sephora/product as product_group_id, including an example. This removes ambiguity about how to obtain the identifier.

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 clearly states a specific verb-resource pair: it Returns one page of a Sephora product's customer Q&A. It further enumerates exactly what each returned item includes, such as text, author, brand answer status, and helpful votes, which makes the tool's function unambiguous and distinguishes it from related tools like sephora_product_reviews.

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 gives useful context by explaining the one-page behavior and how to obtain product_id, but it does not explicitly explain when to use this tool versus alternatives such as sephora_product_reviews or product search tools. The correct usage is implied rather than stated, so an agent receives guidance but no explicit when-not or exclusion phrasing.

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