hm_product_related

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

With no annotations, the description carries full responsibility for setting behavioral expectations, and it does this well. It discloses that the recommendation lists genuinely vary by product, that some lists only appear when applicable, and that an unrecognized product_id produces a well-formed empty result rather than an error, which is exactly the kind of non-obvious behavior 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 primary statement is front-loaded and immediately actionable: 'Get an H&M product's related items.' The following examples and edge-case note are genuinely useful rather than filler, though the parenthetical is slightly long relative to this single required parameter.

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 simple one-required-parameter, no-output-schema, no-annotation tool, the description is remarkably complete: it covers what is returned, how the returned lists vary, and how failures are represented as empty results. The main thing absent is a formal response shape, but the prose adequately describes the functional result.

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%: the schema already documents product_id as a numeric H&M product id sourced from a listing/search result's id field. The description adds little parameter-level meaning beyond reiterating that the tool relates to one product, so the baseline score of 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 names a specific verb and resource: 'Get an H&M product's related items.' It goes further by defining the exact scope as every product-detail recommendation list shown in H&M's own app, and the examples ('more from series', 'style with', 'alternatives', 'upsell') clearly distinguish it from a general product-detail or product-search tool.

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 intended use is clear: when the agent has an H&M product_id and wants the related/recommendation lists shown on that product's detail page, this is the tool. It does not explicitly name sibling alternatives or exclusion cases, but the context is strong enough to avoid confusion with hm_product or hm_search.

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