hm_product

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

With no annotations provided, the description carries the full transparency burden, and it delivers: it discloses the composite response structure (colors → sizes → price/availability), the conditional presence of ratings/reviews, and the concrete failure mode 'An unrecognized product_id returns 404.' It does not disclose potential review-count limits or how recent 'live' availability is, but the core call behavior and error path are well covered.

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 a single dense passage but front-loads the core operation and then layers detail logically: what is returned, why siblings cannot substitute, how to derive product_id, and the 404 outcome. A few clauses could be tightened or reorganized for scannability, but no sentence is filler and the information hierarchy is sound.

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?

Given a single required parameter, no annotations, and no output schema, the description does a thorough job describing what comes back, how to source the id, and what failure to expect. Minor gaps remain (e.g., review ordering/limits, whether price is current sale or list price), but for a 1-parameter product fetcher this is close to fully sufficient.

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 covers the parameter 100%, so baseline is 3. The description adds genuine meaning beyond the schema: it clarifies that the numeric id can be extracted from the url field's 'productpage.<id>.html' segment—an actionable format hint an agent could otherwise miss when scraping the value. This extra context justifies the above-baseline score.

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 full detail') and then enumerates precisely what 'full detail' means: per-color pricing, per-size availability, aggregate rating, and reviews with specific fields. It explicitly differentiates itself from hm-listing and hm-search, telling the agent this richer data is not available there. There is no ambiguity about what this tool returns versus its siblings.

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 explicitly names the alternatives (hm-listing, hm-search) and the data they lack (per-size price, live availability, reviews), giving the agent a clear condition for selecting this tool. It does not state the inverse—when the lighter hm-listing/hm-search would be the better or cheaper choice—so the guidance is directional rather than fully exclusive.

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