按 HS 编码查询中国出口退税率。支持 8/10 位海关编码；4/6 位前缀返回该章/品目所有当前有效商品。示例：query_rebate_rate("85171300")
Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.
{
"id": 1,
"jsonrpc": "2.0",
"method": "tools/call",
"params": {
"arguments": {
"hs_code": "<hs_code>"
},
"name": "query_rebate_rate"
}
}| Name | Required | Description | Default |
|---|---|---|---|
| hs_code | Yes |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the behavioral transparency burden. It discloses meaningful behavior: accepted code lengths, prefix expansion to all current valid commodities, and a concrete example. It doesn't mention error handling or output structure, but for a read-only query this is reasonably transparent.
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 two concise sentences plus an example, with no wasted words. The key action and object are stated first, followed by essential format details and a concrete usage illustration.
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 single-parameter tool with no annotations and no output schema, the description covers purpose, input format, prefix behavior, and an example. It could explicitly state return-value structure or error cases, but overall it is sufficiently complete for typical usage.
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 schema only defines a required string 'hs_code' with zero description coverage. The tool description fully compensates by explaining valid input formats (8/10 digits), prefix behavior (4/6 digits return all items), and providing an example value. This makes the parameter's meaning and constraints clear.
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 a specific verb and resource: '按 HS 编码查询中国出口退税率' (query China export rebate rate by HS code), clearly stating what the tool does. It distinguishes itself from siblings by focusing on HS code lookup rather than statistics or name-based search.
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?
It gives clear usage context: supports 8/10-digit codes, while 4/6-digit prefixes return all current valid commodities. This conveys when to use the tool, though it doesn't explicitly name alternatives or exclusion cases. The context is strong enough to infer appropriate use.
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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