Find nearby Costco warehouses by latitude and longitude, with names, addresses, and distance sorted closest first.
Find nearby Costco warehouses. Returns Costco warehouses near a latitude/longitude, sorted by distance: name, address, and distance for each. Public data sourced from Costco's own warehouse locator backend.
| Name | Required | Description | Default |
|---|---|---|---|
| latitude | Yes | Latitude | |
| longitude | Yes | Longitude |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It discloses output fields (name, address, distance), sorting behavior (by distance), and that the data is public and sourced from Costco's backend. This goes beyond a simple purpose statement, though it omits details like distance units, result limits, or error behavior, preventing a perfect score.
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 three concise sentences with no fluff. Each sentence adds value: purpose, return details, and data source. There is minor redundancy (repeating 'near a latitude/longitude') but it is not distracting and the overall structure is efficient and front-loaded.
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 the tool's simplicity (2 parameters, no output schema, no nested objects), the description is largely complete. It explains what the tool does, the inputs, and the return fields. The lack of distance unit specification is a minor gap but not critical for a straightforward lookup tool. A perfect score would require more explicit output structure or edge-case handling.
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?
The input schema already provides descriptions for both parameters ('Latitude' and 'Longitude'), giving 100% schema coverage. The description adds the context that these coordinates are used for a nearby search, but does not add extra detail such as decimal degrees format, valid ranges, or coordinate system. This matches the baseline score of 3 when schema coverage is high.
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 'Find nearby Costco warehouses,' which is a specific verb+resource statement. It further clarifies the tool's scope by specifying it returns warehouses near a latitude/longitude, sorted by distance, with name, address, and distance fields. This clearly distinguishes it from sibling tools like costco_search or costco_product_availability, which serve different purposes.
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 clearly implies when to use the tool: when a user needs Costco warehouse locations near a given coordinate. It explicitly states the input is a latitude/longitude pair, which indicates the required context. However, it does not name alternative tools or provide explicit exclusion criteria, so it falls short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.