zara_search

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

With no annotations present, the description carries the full behavioral burden and succeeds impressively. It discloses read-only semantics, return normalization details, 'best-effort relevance' fallback behavior with no reliable indicator of fallback, and the exact pagination edge case where an out-of-range offset returns an empty result with is_last_page true. This 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 description is compact and front-loads the core action and return summary. The opening sentence 'Search Zara products.' is slightly redundant with the immediately following sentence, which costs it a perfect score, but there is no fluff and every remaining detail serves the agent.

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 there is no output schema, the description compensates by summarizing return contents (normalized products, pricing, images, availability, color variants, facets) and by covering the critical edge cases an agent would otherwise discover only through failed calls. It is fully sufficient for correct invocation and result interpretation.

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 documents all parameters with 100% coverage, providing the baseline. The description adds real value by explaining offset semantics ('real offset-based pagination'), the behavior for out-of-range offsets, and the scoping of the section parameter. It does not add much for query or limit, but the offset and section insights go beyond the 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?

The description clearly states the tool 'Searches Zara product listings by keyword within one department section,' giving a specific verb, resource, and scope. It implicitly distinguishes itself from category-browsing or suggest tools, but it never names sibling alternatives like zara_category_products or zara_suggest, so differentiation is not explicit.

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: use this when you need keyword-based product search within a single Zara department, not cross-department or category browsing. It also warns about best-effort relevance and fallback behavior for obscure keywords, which helps an agent decide whether results are trustworthy. However, it does not explicitly state when not to use the tool or name alternative tools.

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