oldnavy_product_reviews

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

No annotations or output schema exist, so the description carries the full disclosure burden — and it meets it. It discloses a page-limiting behavior (one page, 10 reviews per page), the exact response fields, the default brand value ('on'), and the important edge case that an empty review set returns a well-formed empty result rather than an error. The only omissions are minor (sort order, exact failure mode on brand mismatch).

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?

Four dense sentences, each carrying a distinct payload: scope, return shape, pid semantics and then brand semantics plus empty-result behavior. The purpose is front-loaded and there is no filler, though the brand sentence's parenthetical closures make it longer than strictly necessary.

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 3-parameter tool with no annotations and no output schema, the description is unusually complete: it covers parameter provenance, brand-value enumeration, defaulting behavior, pagination semantics, response structure, and the empty-reviews edge case. An agent can call this tool safely and interpret the result correctly without opening any other resource.

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 100%, so the baseline is 3, but the description adds real value. The schema only says 'Storefront the pid belongs to' for brand, while the description enumerates the allowed codes (`on`, `gap`, `br`, `at`) plus the default and the requirement that it match the pid's origin. It also reinforces the pid nuance with an explicit 'not the bare base product id', which is more precise than the schema's phrasing.

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?

Opens with a specific verb and resource ('Get reviews for an Old Navy, Gap, Banana Republic, or Athleta product') and surfaces the multi-brand scope that the tool name hides. It further enumerates exactly what is returned — six review fields plus a rating summary with average, count, per-star histogram, and recommended ratio — making it unmistakable against sibling review tools like nike_product_reviews or walmart_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?

Provides concrete sourcing guidance: pid must come from oldnavy-search's colors[].id field, is the same pid oldnavy-product accepts, and the description warns that brand must match the storefront the pid was found under. It orients the agent to the correct inputs across the web, but stops short of an explicit when-not-to-use statement or named alternative review tools.

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