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tzangms

shopline-mcp

by tzangms

update_order_status

Update Shopline order statuses: modify order, delivery, or payment status in one call. Only provided fields are changed.

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
statusNo訂單狀態(如 confirmed / cancelled)
order_idYes訂單 ID
payment_statusNo付款狀態(如 paid / unpaid)
delivery_statusNo配送狀態(如 shipped / delivered)
Behavior4/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It reveals side effects: immediate status change, impact on frontend/reports, possible customer notifications, and errors for invalid statuses. It also discloses that each non-None parameter invokes a separate API call, adding transparency beyond just saying 'update'.

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 headers (用途, API calls, 回傳結構, 副作用) and bullet lists. Every section delivers distinct information, and there is no redundant or filler content.

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

Completeness4/5

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

The tool is complex due to multiple possible API calls per invocation. The description compensates for lacking an output schema by stating the return dict structure and lists side effects and error conditions. However, it does not address partial success scenarios or permission requirements, leaving some completeness gaps.

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 has 100% description coverage with examples for all four parameters. The description adds significant meaning by explaining the non-None conditional behavior and mapping each parameter to a specific PATCH endpoint, which is not apparent from the schema alone.

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 opens with '[WRITE] 更新訂單狀態(支援同時更新多種狀態)', which clearly identifies the verb (update) and resource (order status). It further distinguishes the three sub-statuses (main, delivery, payment), setting it apart from sibling tools like update_order or cancel_order.

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 【用途】 section explicitly says the tool updates main, delivery, and payment statuses individually or together, giving clear context for when to use it. It also explains that only non-None parameters trigger API calls, but it does not name alternative tools or when not to use it.

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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