按商品名称关键词搜索中国出口退税率（中文），自动子串回退。示例：search_rebate_by_name("智能手表")
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": {
"keyword": "<keyword>"
},
"name": "search_rebate_by_name"
}
}| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| keyword | Yes |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations are absent, so the description carries the full burden. It discloses one meaningful behavioral trait: automatic substring fallback ('自动子串回退'), which helps predict matching behavior. However, it does not mention what happens on zero results, output formatting, or rate limits, leaving significant gaps for a tool with no other behavioral documentation.
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 extremely concise, consisting of a single sentence with an illustrative example. Every part adds value, the key capability is front-loaded, and there is zero redundancy.
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 simple two-parameter search tool, the description is adequate but incomplete. It covers the primary purpose and a key behavioral feature (substring fallback), but it does not mention the output structure, default pagination, or edge-case handling. Given the absence of an output schema, a bit more detail would round it out.
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?
Schema description coverage is 0%, so the description is expected to compensate. It provides semantics for the 'keyword' parameter by indicating it is a product name keyword (Chinese), reinforced by the example. However, the 'limit' parameter is completely unexplained, and no default behavior is noted, leaving half the parameters ambiguous.
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's function with a specific verb and resource: search China export rebate rates by product name keyword, with a concrete example. This unambiguously distinguishes it from sibling tools like query_rebate_rate and rebate_rate_stats, which likely serve different querying or statistical 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?
No explicit guidance is provided on when to use this tool versus the alternative sibling tools. The description implies usage for keyword-based product name searches but does not mention situations where a different tool would be more appropriate, nor does it state any exclusions or prerequisites.
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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