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markswendsen-code

MCP Connector for Sam's Club

find_clubs

Locate nearby Sam's Club warehouses by entering a zip code or city name. Get store details including address, hours, phone numbers, and available services within a specified radius.

Instructions

Find Sam's Club warehouse locations near a given zip code or city. Returns store details including address, hours, phone, and available services.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
locationYesZip code (e.g. '72712') or city name (e.g. 'Bentonville, AR')
radiusNoSearch radius in miles (default: 25)
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions that the tool returns store details, but does not disclose important behavioral traits such as rate limits, authentication needs, error handling, or whether the search is real-time or cached. The description is functional but lacks depth for safe and effective use.

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 description is appropriately sized and front-loaded, consisting of two concise sentences that efficiently convey the tool's purpose and output. Every sentence earns its place by providing essential information without redundancy or unnecessary details.

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

Completeness3/5

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

Given the tool's moderate complexity (2 parameters, no output schema, no annotations), the description is adequate but has clear gaps. It covers the basic purpose and output, but lacks behavioral context and detailed usage guidelines. Without an output schema, it partially describes return values, but more completeness is needed for optimal agent use.

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

Parameters3/5

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

The schema description coverage is 100%, so the input schema already documents both parameters ('location' and 'radius') with clear descriptions. The description adds minimal value beyond the schema by mentioning 'zip code or city' and 'search radius in miles', but does not provide additional syntax, format details, or constraints. Baseline 3 is appropriate when the schema does the heavy lifting.

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?

The description clearly states the tool's purpose with a specific verb ('Find') and resource ('Sam's Club warehouse locations'), and distinguishes it from siblings by focusing on location search rather than membership or product information. It explicitly mentions the search criteria ('near a given zip code or city') and the type of data returned ('store details including address, hours, phone, and available services').

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?

The description implies usage by specifying the search context ('near a given zip code or city'), but does not explicitly state when to use this tool versus alternatives like 'get_membership_info' or 'search_products'. It provides some guidance on input parameters but lacks explicit exclusions or comparisons to sibling tools.

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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