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lululemon_stores

Browse lululemon's physical store directory, filtering by country, state, or distance. Returns weekly hours and in-store amenities for US and Canada locations.

Instructions

Browse lululemon's physical store directory. Returns lululemon's own complete physical store directory (480 US and 86 Canada locations), including regular weekly hours and in-store amenities. All filters are optional and applied to the full directory. country and state are free-text equality filters against the values this directory actually carries (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

TableJSON 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

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.14.0

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations, the description does useful work: it discloses the return contents (complete directory, weekly hours, amenities), the approximate scope (480 US and 86 Canada locations), free-text equality behavior, lat/lng coupling, radius bounds/default, and nearest-first sorting. It stops short of auth, rate-limit, or error behavior, so it is not fully comprehensive.

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

Conciseness5/5

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

The purpose is front-loaded in the first sentence, followed by return contents and filter behavior. The sentences are dense but each carries useful information without repetition.

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

Completeness5/5

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

For a simple five-optional-parameter store directory with no annotations or output schema, the description covers purpose, return contents, filter semantics, defaults, constraints, and sorting. An agent has enough information to call it correctly.

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?

Schema coverage is 100%, so the baseline is 3. The description adds value beyond the schema by clarifying that country/state are free-text equality filters against actual 2-letter values, not enums, and by reinforcing that lat/lng must be supplied together and that radius defaults to 50 and sorts nearest-first.

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 verb and resource: "Browse lululemon's physical store directory," and clarifies it returns the complete physical store directory rather than products or categories. This makes it readily distinguishable from the other lululemon product/category siblings.

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

Usage Guidelines3/5

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

Explains that all filters are optional and applied to the full directory, and distinguishes country/state filtering from lat/lng radius filtering. However, it does not explicitly say when to use this tool versus other lululemon tools or when not to use it.

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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