lululemon_outfit

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

Behavioral Transparency: The description carries substantial behavioral detail: it says what is returned (anchor product plus complementary items), clarifies id-space differences, states recommended items have third-party ids, directs users to each item's URL, and warns about 404 on unknown input. No annotations are provided, so this is a strong behavioral disclosure, though it does not cover todos limit, or authentication.

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 text is dense but not bloated; every sentence adds either scope, id-space guidance, or error behavior. It begins with a clear summary and then provides necessary pointer and caveats, so the structure aids quick scanning. It is somewhat lengthy for a two-parameter tool, but the added detail is justified.

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?

The description is complete enough for the tool's scope: it covers what the tool returns, how to source the input ids, the id-space pitfalls, how to reach product pages, and the exact error condition (404). Given that there is no output schema, the description fills all essential gaps for a safe and correct call.

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 fully, so a baseline of 3 applies. The description adds helpful semantic nuance beyond the schema: it defines both the source of unified_id and color_code, and explicitly warns that the id is not the same as lululemon-product's product_id. This meaningfully reduces risk of misuse.

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 uses a specific verb and resource: 'Get lululemon's outfit/style recommendations for a product color.' It clearly narrows the scope to one product color and states the result includes both the anchor product and every complementary item. This distinguishes it from sibling tools like lululemon_product and lululemon_category without ambiguity.

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 provides clear context: it is used with a unified_id and color_code obtained from lululemon-product's response, and an unrecognized pair returns 404. It does not explicitly name alternative tools or say when not to use it, but the context of 'outfit/style recommendations for a product color' makes the intended usage obvious.

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