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

Annotations cover only readOnlyHint/openWorldHint, so the description earns credit by disclosing that counts are live, that optional per-product fields (colors, materials, sizes, gender, line) are dropped when the source lacks them, and that a truly empty result returns an empty products list rather than an error. These are real data-completeness guarantees an agent couldn't infer from structured fields.

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?

Three tight sentences, front-loaded with purpose then caveats, with no filler. Slightly dense in the middle sentence but every clause carries information.

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?

With an output schema present, return structure needn't be explained, and annotations cover safety. The description still adds scope, facet behavior, and empty-result semantics — enough for a correct call, though a routing hint to sibling tools would complete it.

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 description coverage is 100%, so the schema already documents q, page, size, and limit, including the size_facets workflow hint. The description adds only that search is keyword-based and that facet counts are live, so baseline 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?

States a specific verb (Search), resource (Gucci's US storefront catalog), and mechanism (by keyword), plus the scope boundary of US-only. An agent can distinguish this from gucci_category, gucci_product, and gucci_suggest without opening a schema.

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?

Usage is implied by the keyword-search framing, and the description notes size filtering feeds off facet counts, but it names no alternatives (e.g., gucci_suggest for autocomplete, gucci_category for browsing) and gives no when-not condition. Nothing steers an agent between this and its eight Gucci siblings.

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