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tzangms

shopline-mcp

by tzangms

execute_order_shipment

Mark a specified order as shipped and trigger the Shopline shipment flow. Updates order shipment status and may send customer notifications.

Instructions

[WRITE] 執行訂單出貨。

【用途】 將指定訂單標記為已出貨,觸發 Shopline 出貨流程,適用於倉庫確認出貨後的狀態更新。

【呼叫的 Shopline API】

  • POST /v1/orders/{order_id}/shipment

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

【副作用】

  • 訂單出貨狀態更新為已出貨

  • 可能觸發客戶出貨通知(取決於商店設定)

  • 訂單需處於可出貨狀態,否則 API 會回傳錯誤

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
order_idYes訂單 ID
Behavior5/5

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

With no annotations provided, the description carries full behavioral disclosure. It lists side effects: order shipment status updates to shipped, may trigger customer notifications, and the order must be shippable or the API returns an error. This is thorough for a write operation.

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 for purpose, API, return structure, and side effects. Every sentence provides useful information with no redundancy. It is appropriately sized for the tool's complexity.

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?

The tool is simple with one parameter, but the description covers all necessary aspects: purpose, API endpoint, return structure (dict with success, resource_id, message), and side effects. Even without an output schema, the return format is explicitly described, making the description complete for an agent to invoke and interpret results.

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

Parameters3/5

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

The schema has 100% coverage for the single parameter order_id, with description '訂單 ID'. The tool description does not add additional meaning beyond this, such as format or how to obtain the ID. However, since the parameter is simple and fully documented, a baseline of 3 is appropriate.

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 states the tool's function: '執行訂單出貨' marks an order as shipped and triggers the Shopline shipment flow. It also specifies the exact API endpoint (POST /v1/orders/{order_id}/shipment), making the operation unambiguous. This distinguishes it from siblings like update_order_status or bulk_execute_shipment.

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 specifies the intended usage context: '適用於倉庫確認出貨後的狀態更新' (for status updates after warehouse confirms shipment). It also mentions the prerequisite that the order must be in a shippable state. However, it does not explicitly contrast with alternatives like bulk_execute_shipment or update_order_status.

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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