キュレーション済みセット提案（バンドル/ルームプリセット/インフルエンサーPick/ハックセット）

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

With no annotations, the description must disclose safety, permissions, and response traits. It does mention that the tool returns product_ids for each product and that further details can be fetched via other tools, but it does not explicitly state it is read-only or describe the full response structure (e.g., set metadata, pagination). It adds behavioral context (four types, follow-up usage) but has gaps.

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 compact, with three sentences covering examples, type definitions, and integration with other tools. Every sentence provides useful information without fluff, and the structure is front-loaded with relatable examples.

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 6 parameters and absence of annotations or an output schema, the description should explain return structure thoroughly. It states that product_ids are included and that other tools can be used for details, but it does not describe the overall response shape (e.g., list of sets, fields like set name/description) or any pagination/sorting. The examples and type definitions make it minimally viable but with these gaps.

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, so the baseline is 3. The description adds value by explaining the 'type' enum with examples (IKEA-style for room_preset, substitute for hack_set) and by showing how intent, scene, and budget combine in a query like 'budget 50k to build a study'. This enriches parameter semantics beyond the schema's one-line descriptions.

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 explicitly states it returns curated set proposals and names four types (bundle, room preset, influencer pick, hack set). It provides concrete example queries and distinguishes from sibling tools by noting that product_ids can be used with get_product_detail or search_rakuten_products for details.

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 clear context on when to use: when the user asks for a set of items like 'everything needed for a new life' or 'YouTuber desk tour products'. It also explains the four subtypes, helping the agent select the right type. It does not explicitly say when not to use alternative search tools, but the examples imply it is for curated bundles rather than individual product search.

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