zara_search

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

With no annotations available, the description carries the full transparency burden, and it rises to the occasion. It discloses best-effort relevance, fallback to broader results for obscure queries, the lack of a reliable field to detect fallback, and the non-error empty result for out-of-range offsets. There is no annotation contradiction.

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 and dense, avoiding fluff apart from one slight opening repetition. Each of the remaining sentences contributes meaningful caveats or return details that help the agent predict tool behavior.

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 the moderate tool complexity, the description covers pagination, edge cases, fallback semantics, and the result contents. Without an output schema, the description still gives enough behavioral detail for correct invocation, though exact section value examples or error responses are not described.

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?

Parameter descriptions already cover all four parameters at 100%, so the baseline is 3. The description adds meaningful offset behavior and clarifies that searching is scoped to one department section, adding practical context beyond the raw schema.

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?

Clearly identifies a specific action and resource: searching Zara product listings by keyword within a single department section. It further distinguishes itself from potential siblings like zara_suggest or zara_category_products by framing itself as keyword search with product results, pricing, availability, and facets.

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 gives strong context: this is the correct tool when an agent needs keyword-based product search inside one department. It doesn't explicitly name alternatives or exclusion cases, but the content makes the usage scope clear enough to avoid obvious misuse.

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