中古バイク・原付・スクーターを売りたいユーザーに、車種と車両状態別の出張買取の概算相場（円）を返す。ユーザーが「いくらになる／相場は／売ったらいくら／査定して／高く売りたい／バイクを処分したい／乗らなくなった／不動車や事故車でも売れる?」等と尋ねた時に使う。相場の提示のみで、実際の買取申込は行わない（申込は submit_kaitori_request を使う）。車種が特定できない場合は先に search_models で正式表記を確定すること。
| Name | Required | Description | Default |
|---|---|---|---|
| maker | No | メーカー名（任意。同名車種の絞り込み用。例: ホンダ／ヤマハ） | |
| model | Yes | 車種名（search_modelsの結果の正式表記をそのまま渡す） |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The readOnlyHint annotation already signals a safe, non-destructive operation; the description adds useful context that no purchase application is created and that only a market-price estimate is returned. However, it mentions 「車両状態別」 (by vehicle condition) while the input schema exposes no condition parameter, leaving a behavioral gap about how condition affects the result.
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 front-loaded with the core function and then moves to trigger phrases, non-application behavior, and sibling routing. It is slightly long due to the enumerated user-phrase examples, but those examples genuinely help an agent recognize when to select the tool.
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, read-only lookup with no output schema, the description covers what is returned, when to use it, and how to resolve ambiguous models. The main unresolved issue is the claimed condition-based pricing not being reflected anywhere in the input schema or explained further.
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 100%, so the baseline applies. The description mostly repeats the schema's guidance that model should use the official form from search_models and that maker is optional for narrowing. It adds little beyond what the parameter descriptions already state.
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 resource: it returns approximate purchase prices in yen for used bikes, mopeds, and scooters. It also explicitly differentiates itself from siblings by noting that it only presents estimates and that actual applications go through submit_kaitori_request, while model disambiguation goes through search_models.
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 gives concrete trigger phrases like 「いくらになる」「相場は」「査定して」, clearly limits the tool to price estimation, and tells the agent to use submit_kaitori_request for actual applications and search_models first when the model is not identifiable. This is explicit when-to-use and when-not-to-use guidance.
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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