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update_order_status

Update the main status, delivery status, or payment status of an order. Supports updating multiple statuses simultaneously.

Instructions

[WRITE] 更新訂單狀態(支援同時更新多種狀態)。

【用途】 分別或同時更新訂單的主狀態、配送狀態、付款狀態。 僅傳入非 None 的參數,每個非 None 參數會各自呼叫一支 API。

【呼叫的 Shopline API】

  • PATCH /v1/orders/{order_id}/status(若 status 非 None)

  • PATCH /v1/orders/{order_id}/delivery-status(若 delivery_status 非 None)

  • PATCH /v1/orders/{order_id}/payment-status(若 payment_status 非 None)

【回傳結構】 dict 含 success: bool, resource_id: str, message: str, updated_fields: list。

【副作用】

  • 訂單狀態立即變更,影響前台顯示與後台報表

  • 狀態變更可能觸發客戶通知(取決於商店設定)

  • 非法的狀態值或不合法的狀態轉換會導致 API 回傳錯誤

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
order_idYes訂單 ID
statusNo訂單狀態(如 confirmed / cancelled)
delivery_statusNo配送狀態(如 shipped / delivered)
payment_statusNo付款狀態(如 paid / unpaid)
Behavior5/5

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

With no annotations provided, the description fully discloses behavioral traits: immediate status changes affecting frontend and reports, potential customer notifications, and error conditions for invalid values or transitions. It also explains the separate API calls per parameter.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with clear sections ([WRITE], 用途, 呼叫的 API, 回傳結構, 副作用). Each sentence adds value, and the text is concise yet comprehensive, front-loading the write indicator.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema, the description provides the return structure (dict with success, resource_id, message, updated_fields). It also explains side effects and error conditions, making it complete for a tool with 4 parameters (1 required).

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema already covers all parameters (100% coverage). The description adds operational context: 'only pass non-None parameters' and that each non-None parameter triggers a separate API call, which enhances understanding beyond the schema descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly specifies the tool's function: updating order statuses (main, delivery, payment) simultaneously. It uses a '[WRITE]' prefix and explains that only non-None parameters are processed, distinguishing it from sibling tools like cancel_order or update_order which handle other aspects.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context: use when updating one or more status fields, and only pass non-None parameters. It does not explicitly mention when not to use or contrast with alternatives, but the detailed side effects and API calls offer sufficient guidance.

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

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