get_warehouses
Get a list of all warehouses and store locations. Use it to manage inventory and fulfill orders across multiple sites.
Instructions
取得所有倉庫/門市據點列表。
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Get a list of all warehouses and store locations. Use it to manage inventory and fulfill orders across multiple sites.
取得所有倉庫/門市據點列表。
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
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 only states that a list is returned, with no mention of data source, ordering, pagination, or edge cases. This is minimal and lacks depth beyond the obvious.
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, concise sentence that delivers the full purpose without any extraneous words. It is front-loaded and easy to parse, making it highly efficient.
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?
For a zero-parameter list with no output schema, the description is essentially complete. It clearly identifies the action and resource. It could add minor details like return format or potential limitations, but given the simplicity, the description suffices.
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 tool has zero parameters, and the schema covers them vacuously at 100%. The description adds no parameter-specific semantics, but none are needed. Baseline 4 is appropriate for a parameterless tool.
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 clearly states the tool retrieves all warehouse/store location lists with the specific verb '取得' and resource '所有倉庫/門市據點'. It is unambiguous and distinguishes itself from sibling tools, none of which list warehouses directly.
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 does not explicitly state when to use this tool versus alternatives, but the use case is implied: when you need a list of all warehouses/store locations. No exclusionary or alternative guidance is provided, making it adequate but not explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/tzangms/shoplinemcp'
If you have feedback or need assistance with the MCP directory API, please join our Discord server