ai-furniture-hub

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It adds valuable context beyond basic functionality: it mentions that affiliate URLs are returned for monetization ('返却される affiliate_url をユーザーへの購入リンクとして使用してください'), that related products are automatically suggested ('関連商品（同シリーズ・近いサイズ）も自動で提案されます'), and emphasizes the importance of the intent parameter ('【重要】intentには、なぜこの詳細が必要かを記述してください'). This covers key behavioral aspects like output structure and parameter usage guidance.

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 appropriately sized and front-loaded: the first sentence states the core purpose, followed by important usage notes and behavioral details. Every sentence adds value—none are redundant or wasteful. The structure uses emphasis markers (【重要】, 【収益化】) to highlight key points efficiently.

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?

Given the tool's moderate complexity (2 parameters, no output schema, no annotations), the description is largely complete. It covers purpose, parameter guidance, and behavioral traits like affiliate URLs and related product suggestions. However, it doesn't detail the exact structure of the returned 'フルスペック' (full specs) or potential error cases, which could be helpful for an AI agent. With no output schema, some additional output clarity would improve completeness.

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 schema already documents both parameters (id and intent). The description adds meaningful semantics: it clarifies that 'id' is for a specific product, and provides examples for 'intent' ('購入前の最終確認、サイズの詳細確認、他商品との比較') and marks it as required with importance ('【重要】'). This goes beyond the schema's basic descriptions, offering context and usage guidance for the parameters.

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 purpose: '商品IDを指定して、特定の家具・収納商品のフルスペック（寸法・価格・在庫・素材など）を取得します' (specify a product ID to get full specifications for a specific furniture/storage product). It uses specific verbs ('取得します' - get/retrieve) and resources ('家具・収納商品' - furniture/storage products), and distinguishes itself from siblings like 'get_related_items' or 'search_products' by focusing on detailed specs for a single product.

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 provides clear context for when to use this tool: when detailed specs (dimensions, price, stock, materials) are needed for a specific product ID. It explicitly mentions use cases like '購入前の最終確認、サイズの詳細確認、他商品との比較' (final check before purchase, detailed size confirmation, comparison with other products). However, it doesn't explicitly state when NOT to use it or name specific alternatives among siblings, though the context implies it's for single-product details rather than searching or comparing.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.