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

Annotations already cover readOnly/openWorld, but the description adds substantial behavior: what the response contains per look, the not-found error on unrecognized pairs, and the crucial caveat that recommended items' own id is a different third-party catalog id reachable only via each item's url.

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?

Front-loads the purpose then layers the id caveats in a logical order; each sentence carries information. Slightly dense but no filler, so it earns its 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?

An output schema exists so return shape needn't be explained, yet the description still frames what is returned, covers the error case, and resolves all id-space ambiguities. Nothing an agent needs to call it 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?

Schema coverage is 100%, so baseline is 3, but the description adds real semantic value: it disambiguates unified_id from lululemon_product's product_id (a different id space) and clarifies color_code is a color's code field, preventing a common id-space mistake.

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?

States a specific verb and resource: 'curated outfit/style recommendations for one product color,' including the scope (every complementary item per styled look plus the anchor product). It clearly distinguishes itself from lululemon_product by explaining the id relationship rather than just restating the name.

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 clear context: IDs must come from lululemon_product's unified_id and a color's code field, and an unrecognized pair returns not-found. It does not explicitly name an alternative tool or say when-not to use it, so it falls short of a full when/when-not specification.

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