adidas_product_review_topics

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It covers multiple important behaviors: the topic vocabulary is per model (not fixed), a model with no reviews returns an empty list rather than an error, the label field is a display form of topic and not translated across locales, and the locale parameter is accepted but ignored for labels. These are precisely the kind of quirks an agent needs to know.

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 long but every sentence earns its place. It front-loads the core purpose, then walks through usage, parameter clarifications, and edge cases in a logical order. No redundant filler; each clause adds a distinct piece of information an agent needs. It could be slightly tighter, but the density of useful content justifies the length.

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?

Given there is no output schema, the description does not enumerate the exact return structure beyond mentioning topics[].topic and label fields. However, it provides enough for an agent to call the tool correctly and understand how to consume the result. It also covers the edge case of empty lists and the relationship to sibling tools (adidas_search, adidas_product_reviews). The only minor gap is the exact shape of the topics array, but the description implies it contains objects with topic and label fields.

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 descriptions for both parameters (100% coverage), so the baseline is 3. The description adds valuable context beyond the schema: it clarifies that model_number is NOT the SKU, provides a concrete example (SAMBAU2312), and instructs to source it from adidas_search's products[].model_number field. It also explains the locale parameter's effect (or lack thereof) on labels, adding meaning beyond the schema's simple list of allowed values.

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 opens with a specific verb and resource ('Get Adidas review topics') and immediately clarifies what the tool returns (the filter-by-topic chips for a product's reviews). It distinguishes itself from the reviews endpoint by explaining the topics are a precursor to filtering. The purpose is unambiguous and directly tied to the tool's name and behavior.

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 explicit guidance on how to use the output (feed topics[].topic to /adidas/product/reviews) and where to obtain the required model_number (from adidas_search results). It also advises reading the topic vocabulary per model rather than hard-coding. While it doesn't explicitly name alternatives or exclusions, the usage flow is clearly implied and actionable.

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