lululemon_stores

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

With no annotations, the description compensates by disclosing important behavioral traits: the data is from the endpoint's own research and may be stale, filters are applied locally, and there is no live geo-search API. It also states the return content (weekly hours and amenities). This goes beyond just saying 'stores' and provides useful operational context for the agent.

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, yet each sentence contributes a distinct fact, from directory size to filter behavior to maintenance notes. It could be slightly more structured, but it is not bloated and stays on topic.

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 five parameters, no output schema, and no annotations, this description covers the essential details: what the tool returns, which regions and how many stores, the local filtering behavior, parameter constraints and defaults. The pointer to maintenance notes further aids a cautious agent. Nothing needed to invoke 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 coverage is 100%, so the baseline is 3, but the description adds worthwhile nuance: country and state are free-text equality filters not enum-constrained, lat/lng are required together, and radius_miles has a 1–500 range with a default of 50. It also clarifies that all filters are locally applied after fetching the directory, which is important for interpretation.

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 and resource, 'Browse lululemon's physical store directory,' and clarifies the exact scope by citing 480 US and 86 Canada locations. It clearly distinguishes this tool from other retail store locators by naming the brand and ownership of the data.

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 gives clear filter semantics: all optional, applied locally, and no live geo-search API. It explains constraints like lat/lng required together and radius limits, but it does not explicitly call out a sibling store-locator tool or state when to use this one over alternative directory endpoints, so it falls short of an explicit when-not-to-use guidance.

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