gucci_stores

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It clearly states the output structure (a full US store-locator listing with specific fields), the optional department filter as a case-insensitive substring match, and that the authoritative department tags are the response's own departments field. This provides enough behavior context for a read-only listing tool, though it does not mention pagination or data 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?

The description is compact and front-loaded, with the core purpose in the first sentence. It is slightly redundant ('List Gucci store locations' vs 'Returns Gucci's full US store-locator listing') and the phrase 'with department' is awkward, but every sentence earns its place and there is 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 simple list tool with one optional parameter and no output schema, the description is complete: it enumerates the returned fields, explains the filter semantics, tells the agent where to find valid department tags, and scopes the data to the US. An agent has everything needed to invoke it correctly.

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 coverage is 100%, and the department parameter already has a description nearly identical to the tool description ('case-insensitive substring match against the response's own departments field, e.g. jewelry, mens_shoes. Omit for every store'). The description therefore adds no meaning beyond the schema, so the baseline of 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?

The description opens with a specific verb+resource ('List Gucci store locations') and details the return payload (name, address, phone, coordinates, departments, appointment link). It is clear about the tool's scope, but it does not explicitly differentiate itself from sibling tools such as gucci_store or gucci_store_search, so an agent must infer the distinction from the plural name and the phrase 'full US store-locator listing'.

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?

There is no guidance about when to choose this tool over alternatives like gucci_store or gucci_store_search. The description gives parameter-level advice (omit department for every store, filter by tags from the response's departments field), but it does not state use cases, exclusions, or prerequisites for tool selection.

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