［二行程經典車資料庫］用零件型號或名稱（例如火星塞 BR9ES）反查適用的二行程車款。
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": {
"query": "<query>"
},
"name": "twostroke__find_part"
}
}| Name | Required | Description | Default |
|---|---|---|---|
| query | 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 full behavioral burden, yet it discloses no return format, no result-count behavior, no error/empty-result handling, and no auth or rate-limit context. For a pure lookup this is a notable gap, though the read-only nature is inferable.
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?
A single front-loaded sentence bracketed by a database-scope label, with the action and an example inline. No filler; every clause earns its place.
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 one-parameter lookup with no output schema, the description covers the tool's purpose and its input format adequately. It omits any indication of what the response contains (compatible models list) and how results are structured, leaving a modest gap.
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% for the single 'query' parameter, so the description must compensate. It does so well by defining the accepted input as a part model number or name and giving a concrete example (BR9ES), which meaningfully clarifies what 'query' should contain.
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 states a specific verb and direction of lookup: reverse-lookup ('反查') from a part number/name to applicable two-stroke vehicle models, with a concrete example (spark plug BR9ES). It clearly implies the resource (parts → models) which functionally differs from the model-oriented siblings, though it never names them explicitly.
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 phrasing 'use a part number or name to reverse-look-up applicable vehicles' implies the usage context (when you hold a part and want compatible models). It does not, however, state when to prefer this over sibling tools like search_models or get_model_specs, nor any exclusions.
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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