週末不賣甜點 Weekend no dessert

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

No annotations are provided, so the description carries the behavioral disclosure burden. It clearly discloses a key trait: the tool only builds a link and does not submit the order; the user submits it themselves. It could add more detail about return value or validation, but the most important side-effect boundary is explicitly stated.

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 with no filler. The core function is front-loaded, and the usage guideline follows immediately. Every sentence contributes information that is not already available from the name or schema.

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 low-complexity tool with no output schema and no annotations, the description covers the purpose, the usage condition, the key non-submission behavior, and all four parameter meanings. The exact return type and potential error behavior are left implicit, but this is a minor gap for a link-builder.

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 0%, so the description compensates by mapping natural-language concepts to parameters: '蛋糕' to cakeSlug, '尺寸' to variantId, '日期' to date, and '時段' to slotId. It does not discuss optionality or formats, but the schema provides the patterns, making the description a meaningful semantic bridge.

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 action (generating a link) on a specific resource (the website order page) and explicitly lists the carried data: cake, size, date, and time slot. It also differentiates itself from placing an order by noting that the user presses submit, which distinguishes it from the sibling place_order.

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?

Provides an explicit usage condition: use this when unsure whether to place the order on the user's behalf. It implies the alternative is place_order, but it does not explicitly name alternative tools or state a clear 'when not to use' rule beyond that uncertainty.

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?

With no annotations provided, the description carries the full burden. It discloses the meaning of statuses (bookable, full, closed) and the default date range (60 days from today if no date is provided). This is useful behavioral context, but it does not explicitly state that the operation is read-only or describe any side effects, though the verb '查' implies a query.

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 concise, using three short sentences that front-load the purpose and then add key behavioral details (status meanings and default range). There is no fluff or repetition. It could be slightly more structured, but it is efficient and easy to parse.

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 tool with two optional parameters and no output schema, the description should explain what from and to mean and what the response looks like. It covers the status values and default range but omits parameter semantics and any return format details. This leaves the agent guessing on how to construct a valid request, especially for the range boundaries.

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 0%, so the description must explain the parameters. It mentions '日期不填' (if date not filled) defaults to today+60 days, which implies the from/to parameters form a date range, but it does not clarify which parameter is the start or end, nor explain the format or meaning beyond the default. The description adds partial value but is insufficient for the two 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 checks which dates are bookable and what 10-minute pickup slots exist, with a specific verb ('查') and resource. It distinguishes itself from siblings like place_order or list_cakes by focusing on availability, though it doesn't explicitly name an alternative. The status definitions (bookable/full/closed) add precision.

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 implies usage: check availability before ordering, and explains that only bookable=true slots can be booked. However, it does not explicitly mention when to use this tool versus alternatives like get_shop_info or list_cakes, nor does it state any exclusions. The context is clear but not explicit.

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 behavioral burden. It discloses the tool's informational scope and implies a read-only lookup, but it does not explicitly state that the tool has no side effects, whether the information is static, or if any authentication or external access is required. For a zero-parameter info retrieval tool this is a minor but real gap.

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 compact sentences: the first front-loads the information categories, and the second gives a concrete usage pointer. Every phrase earns its place, and there is no redundant wording. The phrase '週末不賣甜點的' is slightly ambiguous but does not add significant length.

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 zero-parameter tool with no output schema, the description adequately covers what the tool returns and when to call it. It lists the main content areas and the question types it answers. It does not describe the exact return structure or update frequency, but that is a minor omission given the tool's simplicity.

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 tool has zero parameters, so there is no parameter semantics for the description to clarify. Baseline for 0 params is 4, and the description correctly says nothing about 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 enumerates the resource's content: pickup location, pickup times, payment/ordering flow, reschedule/cancellation rules, and size chart, making it clear this is a shop-info retrieval tool. It distinguishes from siblings by the cue '回答「在哪裡拿、怎麼訂、怎麼付」先呼叫這個', though it doesn't explicitly name the alternative tools. The verb is implied by the tool name rather than stated, but the resource scope is precise.

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?

It explicitly directs the agent to call this tool first when answering questions about where to pick up, how to order, and how to pay. This gives clear invocation context. However, it does not state when not to use it or mention sibling alternatives such as get_availability or place_order.

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?

With no annotations, the description carries the full burden but only discloses the content of the listing. It does not explicitly state that this is a read-only operation or note limitations such as pagination or filtering, though the fields listed provide some behavioral context.

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 sentence that front-loads the scope ('currently available cakes') and packs all relevant fields without any filler. Every word contributes to the tool's purpose.

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 zero-parameter list operation, the description covers the essential return fields and currency, and clarifies it is current availability. It omits minor details such as ordering or whether sold-out items are excluded, but is sufficient for basic use.

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 tool has zero parameters and an empty input schema, so the description correctly focuses on the return content rather than parameter meanings. This aligns with the baseline of 4 for tools with no 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 lists currently available cakes and enumerates the returned fields (name, tea base, size, price in TWD, add-on items). The verb and resource are specific, but it does not explicitly differentiate from sibling tools like get_availability.

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 guidance on when to use this tool versus alternatives. It does not mention conditions, exclusions, or how it relates to siblings such as get_availability or place_order, leaving usage entirely implied.

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 burden. It does disclose an important behavioral prerequisite (OAuth authorization) and clarifies that the data belongs to the connected account. It does not explicitly state that it is a read-only operation or describe error handling for missing authorization, but for a simple zero-parameter query the disclosure is adequate.

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 a single, focused sentence that front-loads the concrete data fields and ends with the essential OAuth requirement. Every word earns its place with no redundancy.

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?

There is no output schema, but the description compensates by naming the exact fields returned. Combined with zero parameters and a clear account-scoping statement, an agent has enough information to invoke the tool correctly. It could add details about the expected data format, but nothing critical is missing.

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 tool has zero parameters, so there is no parameter meaning to clarify. The baseline of 4 applies because nothing about parameters needs explanation.

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 identifies the resource (the connected account's membership) and enumerates the returned data fields: member number, level, points, and year-to-date spending. This distinguishes it from siblings like my_orders and get_shop_info, though it omits an explicit verb such as 'retrieve' or 'get'.

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 phrase '已連接帳號的會員本人' gives clear context that this tool is for the currently authorized member's data, and the OAuth note signals when it applies. However, it does not explicitly mention alternatives or situations where a sibling tool like my_orders would be more appropriate.

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?

With no annotations, the description carries the burden and does disclose the OAuth requirement and the scope limitation to the member's own orders. However, it never explicitly states that this is a read-only retrieval operation and gives no detail on pagination, result format, or potential rate 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?

The description is one compact sentence with the core scope front-loaded ('member's own orders'), followed by the enumerated contents and the OAuth requirement. It is efficient with little wasted text.

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 tool with one optional parameter and no output schema, the description reasonably conveys what the call returns (order fields, ticket link capabilities) and the authorization prerequisite. It is incomplete on how 'limit' applies and what the overall response structure looks like, but these are minor for such a simple 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?

Schema description coverage is 0% and the description does not mention the 'limit' parameter at all. The parameter is a simple self-explanatory limit with numeric constraints in the schema, so it is not severely harmful, but the description still fails to compensate for the coverage gap.

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 identifies the resource clearly: the member's own orders for a connected account, and enumerates the contained data (status, cake, add-ons, pickup time, ticket link). It is distinct from siblings like place_order, list_cakes, and my_membership, though it lacks an explicit verb like 'list' or 'retrieve'.

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 implies when to use it: when an OAuth-connected member needs their own order information and ticket links. It does not explicitly contrast it with sibling tools such as build_order_link or my_membership, nor give exclusions, so some inference is required.

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?

With no annotations provided, the description carries the full disclosure burden and delivers extensively: it discloses the mutating nature (submits an order), the confirmation gate before invocation, the business rules (reservation requires bank transfer + last-5-digits to become valid, no 7-day return for made-to-order cakes, reschedule one week prior, slot change two days prior, 50% refund on cancellation), and the success output (ticket link with transfer info and QR code). Rich behavioral context beyond any structured field.

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 a single dense paragraph, but given the tool's complexity (11 params, no annotations, multiple business rules and a confirmation obligation), every sentence carries necessary safety or business information. It is front-loaded with the core purpose, followed by the confirmation checklist, the policy disclosures, the call condition, and the output. No filler, though it is long by necessity.

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 high complexity (11 params, 9 required, no output schema, no annotations), the description is substantially complete: it covers the confirmation gate, all key business policies, and the success return (ticket link). Remaining gaps are minor – failure/error behavior is not described, and the optional message param is unaddressed. It would merit a 5 if error handling and the message param were covered.

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 only 9% (only userConfirmed carries a description), so the description must compensate. It does: the confirmation checklist maps directly onto the parameters – 蛋糕與尺寸→cakeId/variantId, 取貨日期與時段→pickupDate/slotId, 加購→addonIds, 姓名/手機/Email/Instagram→name/phone/email/igHandle. This adds meaning to otherwise undocumented parameters. Minor gap: the optional message parameter is not addressed, preventing a 5.

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 states a specific action (代使用者送出訂購申請 – submit an order application on behalf of the user) and equates it to the website form, giving a concrete verb+resource. It is implicitly distinguished from siblings: build_order_link only constructs a link, get_availability checks availability, list_cakes lists products, whereas this tool actually submits the order. Purpose is unambiguous and non-tautological.

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 a strong when-to-call gate: '使用者明確同意後才呼叫' (only call after the user explicitly agrees), and enumerates the mandatory pre-confirmation checklist (cake/size, pickup date/slot, add-ons, contact details). However, it does not explicitly state when NOT to use this tool or route to an alternative such as build_order_link for preview/draft use cases. Clear context but no explicit exclusions.

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