AIDISH — AIエージェントから受取注文できる飲食店

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

With no annotations provided, the description carries the full behavioral burden. It usefully discloses the return contents (availability status, earliest pickup time, contact info), which is valuable given there is no output schema, but it says nothing about error cases, whether the result is cached, or any permission requirements.

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?

A single, front-loaded sentence that packs the three return values without filler. It is efficient, though cramming three distinct outputs into one clause slightly reduces scannability.

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, low-risk read tool with no annotations and no output schema, the description covers the essential return values and the sole parameter is fully documented in the schema. What is missing is usage routing, which is a guidance gap rather than a completeness gap.

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%, with tenant_id documented (including the default-store behavior when omitted). The description adds no further meaning about tenant_id, so the baseline of 3 applies since the schema does the work.

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?

States a specific verb (返す) with concrete resources: whether the store currently accepts pickup orders, the earliest pickup time, and contact info. This is clear and non-tautological, though it does not explicitly distinguish itself from siblings like place_pickup_order or find_stores.

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?

There is no explicit when-to-use or when-not-to-use guidance, nor any mention of alternatives. The name hints it is a pre-order availability check, but the description never routes the agent relative to place_pickup_order or find_stores, so usage is left entirely to inference.

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

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

No annotations are provided, so the description carries the full behavioral burden. It doesn't mention whether this is a read-only search, what the return format looks like (e.g., list of stores with IDs), or any rate limits or side effects. The only behavioral hint is that it returns stores for user selection, but that's more about usage flow than behavior.

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 two concise sentences, front-loaded with the core purpose and followed by a usage instruction. No wasted words, though the parenthetical filter list is slightly redundant with the parameter descriptions.

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 basic purpose and usage context, but with no annotations and no output schema, it should do more to explain what the tool returns (e.g., list of store objects with tenant_id) and any limitations. It's adequate but missing key details for an agent to call it confidently.

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 fully. The description adds no syntax or format details beyond what the schema provides, so a baseline 3 is appropriate.

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 Japanese description clearly states the purpose: finding stores that accept AI-originated orders, filterable by store name, cuisine type, and area. It's a specific verb+resource, though the description doesn't explicitly contrast with siblings like check_pickup_availability or list_menu, which are clearly different operations.

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 states when to use it: 'When you don't know tenant_id, call this first and have the user select a store.' This provides clear upfront context and a workflow step, leaving no ambiguity about when to invoke it.

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

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

No annotations are provided, so the description carries the full disclosure burden. It usefully reveals scope (only publicly visible items, tax-included pricing) and implies that menu_id values are the key output needed downstream, but says nothing about pagination, result size, auth/tenant resolution, or limits.

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?

Two short sentences: one declaring the returned content, one stating the ordering precondition. Nothing is padded, and the precondition is placed after the payload so the reader gets capability first, then action.

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?

With no output schema, the description must convey return content, and it does (products, prices, descriptions, options) plus the downstream menu_id purpose. It still omits how tenant scoping affects results and whether the list is complete or paginated, which are minor gaps for a simple read tool.

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 single tenant_id parameter is fully documented in the schema (店舗ID, defaulting to the server's default store), and the description adds no additional meaning about it. With schema coverage at 100%, the schema does the work and a baseline 3 is appropriate.

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?

States a specific verb and resource ('returns the store's menu') and enumerates the payload (publicly available products, tax-included prices, descriptions, options), so an agent knows exactly what it fetches. It does not, however, explicitly contrast itself with siblings like find_stores or place_pickup_order, so differentiation is left to the workflow hint rather than stated in the purpose itself.

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?

Gives an explicit precondition tied to the ordering workflow: 'before ordering, always verify menu_id with this,' which effectively routes the agent here ahead of place_pickup_order. It stops short of naming the alternative tool or any when-not conditions, so it is clear context without full exclusion guidance.

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

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

アノテーションがないためdescriptionが挙動説明の全責任を負う。支払いは受取時に店頭で行われること、氏名と電話番号が本人確認と連絡に使われること、注文前に確認すべきことなど、重要な行動特性を開示している。ただしキャンセル可否や注文確定後の流れには触れていない。

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?

4つの短い文で、注文の実行、支払い、必須情報の目的、事前確認事項を過不足なく伝えている。無駄がなく、重要な情報が先頭に配置されている。

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?

出力スキーマはないが、ツールの複雑さ（6パラメータ、ネスト配列）に対して、descriptionは注文の基本的な動作と必須項目の意図をカバーしている。ただし、itemsの形式やpickup_atの省略時の挙動など、スキーマに委ねられている部分もあり、完全とは言えない。

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?

スキーマ記述カバレッジは50%で、スキーマ自体が一部のパラメータ（items、pickup_at、tenant_id、customer_telなど）の説明を提供している。descriptionはitemsの内容やpickup_atの形式には触れておらず、スキーマを超える追加の意味は少ない。ベースライン3が妥当。

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?

同ツール名のピックアップ注文（takeout）を入れるという明確な動詞＋リソースを示しており、支払い方法や必須項目にも触れている。兄弟ツール（list_menu、check_pickup_availability、find_stores）と用途がはっきり区別できる。

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?

注文前に利用者に内容と受取時刻を確認するという前提条件を示しているが、他のツール（例: check_pickup_availability）との使い分けには言及していない。しかし暗黙的にメニュー選択や在庫確認の存在を前提としている。

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