search_amazon_productsユーザーがAmazonで買いたい場合や楽天で見つからない場合に呼ぶ。Amazonの検索結果ページへのアフィリエイトURLを生成する（商品データは返さない）。SearchIndexはカテゴリから自動選択。affiliate_urlをユーザーに提示すること。
| Name | Required | Description | Default |
|---|---|---|---|
| sort | No | 並び順 | |
| intent | Yes | 【必須】検索目的 | |
| keyword | Yes | Amazon検索キーワード | |
| price_max | No | 最高価格（円） | |
| price_min | No | 最低価格（円） |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses that the tool returns a URL only, not product data, and that SearchIndex is auto-selected. It also instructs presenting the URL. However, it does not mention potential error cases or behavior for invalid parameters, which would add more transparency. Overall, good but not exhaustive.
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 three concise sentences: when to use, what it does (URL generation, no data), and an instruction. No filler, front-loaded purpose. Every sentence contributes meaning.
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?
The description covers the essential purpose, usage context, and expected output (affiliate_url), which is sufficient for selecting and invoking the tool. However, it does not mention that the tool is specifically for furniture/storage products (though the title does), and it lacks edge-case guidance for empty search results. Minor gaps but overall complete.
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 covers 100% of parameters with descriptions, so the baseline is 3. The description adds context about SearchIndex auto-selection from category, but does not explain sort or price parameters beyond the schema. It does not need to repeat schema details, so it meets the baseline.
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 generates an affiliate URL for Amazon search results and explicitly notes it does not return product data. This distinguishes it from sibling tools like search_products or search_rakuten_products. The verb 'generate' and resource 'Amazon search results page URL' are specific.
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 explicitly says when to use this tool: 'when the user wants to buy on Amazon or when not found on Rakuten'. It also provides an alternative (Rakuten) and instructs to present the affiliate_url to the user. This is clear guidance for selection and invocation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Multiple tools handle product discovery (search_products, search_rakuten_products, search_amazon_products, suggest_by_space, find_replacement), and their boundaries require careful description reading. diagnose_ai_visibility is completely unrelated to furniture, adding confusion. Most tools are distinct, but the search cluster is ambiguous.
Tool names consistently use snake_case with verb prefixes (get_, search_, find_, list_, etc.). While some verbs overlap (search vs find), the pattern is predictable and no mixed styles exist.
18 tools is on the higher side but reasonable for a rich domain. However, several search variants and the unrelated diagnose_ai_visibility tool could be consolidated, making it slightly bloated.
The furniture hub covers the full user journey: search, detail, compare, related, photo measurement, space planning, storage, replacements, and even demand analysis. Missing features like direct purchase are handled via affiliate links. The unrelated AI visibility tool doesn't create a gap in furniture functionality.