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tzangms

shopline-mcp

by tzangms

split_order

Split an order into multiple sub-orders to handle partial shipments or fulfill from different warehouses. Specify sub-order details in the split configuration.

Instructions

[WRITE] 拆分訂單為多個子出貨單。

【用途】 將一筆訂單拆分為多個子單,適用於商品分批到貨或不同倉庫分開出貨的場景。 split_config 為字典,內容依 Shopline API 規格定義各子單。

【呼叫的 Shopline API】

  • POST /v1/orders/{order_id}/split

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

【副作用】

  • 原訂單被拆分為多個子訂單,原訂單狀態可能變更

  • 操作通常不可逆,請確認拆單設定正確後再執行

  • 已出貨的訂單無法拆單

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
order_idYes訂單 ID
split_configYes拆單設定,包含各子單的商品與配送資訊
Behavior5/5

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

With no annotations provided, the description fully carries the burden of behavioral disclosure. It explicitly lists side effects: original order status may change, operation is usually irreversible, and shipped orders cannot be split. It also includes the API endpoint and return structure, providing comprehensive 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.

Conciseness5/5

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

The description is well-structured with clear sections: [WRITE], 用途 (purpose), API call, return structure, and side effects. It is concise, front-loaded with the main action, and every sentence provides meaningful information without redundancy.

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 the tool's complexity (write operation, nested object, no output schema), the description is remarkably complete. It covers purpose, use cases, API endpoint, return structure, side effects, and constraints (shipped orders cannot be split). No critical information is missing for an agent to decide and invoke the tool correctly.

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?

Schema coverage is 100% for both parameters. The description adds value by explaining split_config is a dictionary following Shopline API specifications, and clarifies that it defines each sub-order. It does not detail the internal structure, but the reference to the spec is useful guidance beyond the schema's generic description.

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 purpose: '拆分訂單為多個子出貨單' (split an order into multiple sub-shipments), with a specific verb (split) and resource (order). It distinguishes from siblings by focusing on the split operation, which is unique among the listed tools.

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?

It provides clear context for when to use: '適用於商品分批到貨或不同倉庫分開出貨的場景' (scenarios of goods arriving in batches or separate warehouses). It also gives an exclusion: '已出貨的訂單無法拆單' (shipped orders cannot be split). However, it does not explicitly name alternative tools or provide broader when-not 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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