ulta_product

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

With no annotations, the description carries the full behavioral disclosure burden. It explains that an invalid or omitted sku still resolves to the base product's default variant and that an unrecognized productId returns 404; this is valuable beyond the semantic basics. It does not mention authentication, rate limiting, or additional error types, but for a simple detail-retrieval call these are not critical.

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 operation and return field list, then moves to parameter provenance, variant behavior, and error handling. Every sentence is informative and contains no filler, even though the phrase 'full detail' appears twice.

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 two-parameter read tool with no output schema and no annotations, this description is sufficient: it lists the return contents, explains both parameters including optional sku behavior, gives an example id, and states the 404 error case. Nothing essential for calling the tool correctly is missing.

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 input schema already documents both parameters, so the baseline is 3, but the description adds meaningful context beyond the schema. It specifies the exact source of productId, gives an example value, and explains the optional behavior and fallback semantics for sku.

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 the tool returns a single Ulta Beauty product's full detail and enumerates the fields included. It differentiates the tool from search/review/category siblings by the phrase 'full detail' plus the field list, but it does not explicitly name or contrast it with sibling tools like ulta_search or ulta_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 concrete guidance on where to obtain productId, namely from a search result's product_id field or a product page URL, which implies use alongside search tools. It provides a real-world example and explains sku's optional role, but it does not explicitly state when not to use this tool or point to alternative tools such as ulta_product_reviews.

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