lululemon_stores

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

With no annotations provided, the description carries the full burden. It honestly discloses that filters are applied locally after fetching the full directory, that country/state are free-text equality filters (not enums), and that lat/lng must be used together. It also notes the radius defaults and range. This is excellent transparency about how the tool behaves beyond just its signature, though it could mention what the output format looks like.

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 a single dense paragraph, but every sentence adds value. It front-loads the core purpose and scope, then explains filtering behavior and parameter specifics. No word is wasted, and it packs a lot of important operational detail into roughly 90 words.

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?

No output schema exists, so the description should indicate what the return value looks like. It says 'Returns lululemon's own complete physical store directory... including regular weekly hours and in-store amenities,' which gives a high-level sense of the output. It doesn't specify the exact structure or whether it returns the full list by default, but for a simple directory lookup, the description is sufficiently complete for an agent to use 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 description coverage is 100%, so the schema already documents all parameters. The description adds important context beyond the schema: free-text equality filters vs enums, lat/lng must be together, radius range/default. It doesn't add much for radius_miles since the schema already states 1 to 500 and default 50, but the behavioral notes about local filtering are a valuable addition.

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 identifies the tool as browsing lululemon's physical store directory, specifies the scope (480 US and 86 Canada locations), and details the returned data (hours, amenities). It also differentiates itself from potential alternatives by noting there is no live geo-search API, making its purpose unmistakable.

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 implicitly but clearly states when to use this tool: when you need lululemon store locations, hours, or amenities. It also explains that filters are optional and applied locally, which guides the agent on when to use filters versus when to request the full directory. It doesn't explicitly name sibling tools, but it provides enough context to avoid confusion with other store tools.

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