ai-furniture-hub

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

No annotations are provided, so the description carries full burden. It discloses key behavioral traits: it returns both catalog successors and Rakuten search results, and requires presenting affiliate URLs to users. However, it doesn't mention rate limits, authentication needs, error handling, or response format details, leaving gaps for a tool with no annotation coverage.

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?

Front-loaded with the primary use case, followed by details on what it returns and user instructions. All sentences are necessary, though it could be slightly more structured (e.g., separating behavioral details from usage guidelines).

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 tool with no annotations and no output schema, the description covers purpose and usage well but lacks details on return format, pagination, error cases, or authentication. It's adequate for basic understanding but incomplete for reliable agent invocation without additional context.

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%, providing good documentation for both parameters. The description adds minimal value beyond the schema by implying the 'query' parameter is used for model numbers or product names, but doesn't elaborate on format or constraints. Baseline 3 is appropriate when schema does the heavy lifting.

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 with specific verbs ('探す', '返す') and resources ('カタログの後継候補', '楽天の検索結果'), distinguishing it from siblings like 'search_products' or 'search_rakuten_products' by focusing on finding replacements for discontinued/obsolete products rather than general product searches.

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?

Explicitly states when to use this tool ('「この型番が売ってない」「生産終了した棚の代わり」のときに呼ぶ') and provides clear alternatives for final verification ('最終確認はメーカー公式で'), giving specific guidance on context and limitations.

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