macys_product

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It explicitly describes a read-only retrieval operation ('Get', 'Returns') and gives a detailed inventory of the returned attributes, including sale detection and per-color variant pricing. It does not cover potential limitations like rate limiting or data freshness, but for a read-style lookup tool the behavioral surface is well exposed.

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 action, then a compact list of return fields, then a parameter note. Every element earns its place; the phrasing is direct and avoids filler. The repetition of 'full detail' is minor and does not detract from the clarity.

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?

There is no output schema, so the description compensates by listing all major return data categories. It also explains the origin of the required productId. The description is sufficient for an agent to decide when to call the tool and how to supply the parameter, though it could optionally mention response structure or error behavior.

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 describes productId as a 'Numeric Macy's product id, from a product page's ?ID= query parameter,' which is 100% schema description coverage. The description repeats this same guidance, so it adds little beyond the schema, but it is consistent and confirms the source of the identifier. Baseline 3 is appropriate.

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 a Macy's product's full detail,' and then enumerates the exact data fields returned (name, brand, description, pricing with sale detection, availability, images, rating, color variants). This makes the tool's purpose immediately distinguishable from sibling tools like macys_product_reviews and macys_suggest, even without explicitly naming them.

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 makes clear this is the tool to use when complete product details are needed, and that the caller must already have a Macy's product ID from a product page. It does not explicitly state when not to use it or name alternatives, but the product-detail context is sufficiently unambiguous given the sibling tools.

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