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lululemon_stores

Read-only

lululemon's own complete physical store directory (480 US and 86 Canada locations as of this build), including regular weekly hours and in-store amenities. All filters are optional and applied locally after fetching the full directory. country and state are free-text equality filters against 2-letter codes (e.g. US/CA, NY/CA), not an enforced enum. lat and lng (both required together) filter to stores within radius_miles (1 to 500, defaults to 50), sorted nearest-first.

Input Schema

NameRequiredDescriptionDefault
latNoLatitude, requires lng
lngNoLongitude, requires lat
stateNoFilter to one state/province by its 2-letter code
countryNoFilter to one country by its 2-letter code
radius_milesNoSearch radius in miles, 1 to 500, defaults to 50

Output Schema

NameRequiredDescriptionDefault
dataYesThe tool result payload (shape varies per tool; see each tool's docs resource).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed5 schema fields changed
    • addedInput schema / properties / country / description
      Added value: +"Filter to one country by its 2-letter code"
    • addedInput schema / properties / lat / description
      Added value: +"Latitude, requires lng"
    • addedInput schema / properties / lng / description
      Added value: +"Longitude, requires lat"
    • addedInput schema / properties / radius_miles / description
      Added value: +"Search radius in miles, 1 to 500, defaults to 50"
    • addedInput schema / properties / state / description
      Added value: +"Filter to one state/province by its 2-letter code"
  2. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Beyond the readOnlyHint/openWorldHint annotations, the description discloses the dataset size (480 US, 86 Canada), the fields returned (weekly hours, amenities), and the local-filtering behavior (full directory is fetched then filtered), plus nearest-first sorting for geo queries. These are substantive operational traits not present in the structured fields. It stops short of stating auth or rate-limit behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Four sentences, front-loaded with what the tool is, then filtering model, then coordinate specifics. Dense but every sentence carries information. Slightly packed with parenthetical detail, but nothing is wasted or redundant.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 5 optional params, an output schema (so return format needn't be explained), and the two annotations, the description covers data scope, filter semantics, and coordinate/sorting behavior well. It omits nothing an agent needs to call the tool correctly, though pagination/result-size behavior against the full directory is unstated.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 100% schema coverage the baseline is 3, but the description adds real value by clarifying country/state are 'free-text equality filters against 2-letter codes (e.g. US/CA, NY/CA), not an enforced enum' and that lat and lng are 'both required together' and constrain results to radius_miles sorted nearest-first. This resolves ambiguity the schema alone leaves open.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific resource and scope: 'lululemon's own complete physical store directory (480 US and 86 Canada locations as of this build), including regular weekly hours and in-store amenities.' An agent knows immediately this returns a store directory with hours and amenities, clearly distinct from the product/category/outfit siblings under the lululemon prefix.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explains that 'All filters are optional and applied locally after fetching the full directory,' which tells the agent the filtering model and that no filter is required. It does not name an alternative store tool or state when-not to use it, but within the lululemon sibling set there is no competing store resource, so the absence of explicit routing is a minor gap.

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

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