list_banks
Retrieve the list of banks supported by the buy123 vendor portal. Use this data to populate bank selection fields in your workflows.
Instructions
獲取銀行列表 (GET /v1/common/banks).
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Retrieve the list of banks supported by the buy123 vendor portal. Use this data to populate bank selection fields in your workflows.
獲取銀行列表 (GET /v1/common/banks).
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It only reveals the HTTP method (GET), which implicitly suggests a read-only operation, but it does not mention authentication needs, response format, or any side effects. This is minimal transparency for a tool with no annotation support.
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, front-loaded sentence that conveys the essential action and endpoint. No words are wasted, and the length is appropriate for a tool with no parameters and a straightforward purpose.
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?
Despite its brevity, the description is reasonably complete for a zero-parameter list endpoint. It states the purpose and the HTTP endpoint, which is sufficient for an agent to invoke the tool. There is no output schema to reference, but the return value (a list of banks) is implicitly clear from the tool name and description. Minor gaps remain around response structure, but the low complexity keeps the completeness score high.
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 confirms this. Per the rubric, 0 parameters earns a baseline of 4. The description adds no parameter-specific info because there are none to describe, so this baseline is appropriate.
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 uses a specific verb ('獲取' = get) and resource ('銀行列表' = bank list), clearly stating what the tool does. It includes the API endpoint for additional clarity. However, it does not explicitly differentiate this from sibling list tools, though the resource name itself provides implicit distinction.
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 provides no guidance on when to use this tool versus alternatives. It simply states the function and endpoint, with no mention of prerequisites, context, or exclusions. For a list tool, one might expect a note about typical use cases or relation to other list endpoints.
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/asgard-ai-platform/mcp-buy123-vendor'
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