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

Annotations already declare readOnlyHint and openWorldHint, so the safety profile is covered. The description adds genuinely useful behavioral context beyond that: 'The current source supplies phrases but not per-phrase result counts,' which sets expectations about response content. Only minor gaps remain (e.g., no note on rate limits or suggestion source freshness).

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 the core purpose and each clause carrying distinct value: what it returns, its limitation, and where to route next. No filler.

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 2-parameter suggestion tool with an output schema, the description covers purpose, input nature, source limitation, and the hand-off to gucci_search. Nothing an agent needs to call it correctly is missing.

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 both q and limit are fully documented in the schema, including the default and max for limit. The description adds no parameter detail beyond restating 'partial query,' so the 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 and resource (Gucci search-box suggestions for a partial query) and explicitly distinguishes itself from the sibling result tool with 'Not product data -- pass a suggestion's query into gucci_search for results.' An agent can separate this from gucci_search, gucci_product, and gucci_recommendations 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?

Gives clear usage context (partial query input) and routes the agent onward by naming gucci_search as the tool for actual results. It stops short of stating explicit exclusions, but the 'Not product data' clause effectively tells the agent when this tool is the wrong choice.

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