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create_order

Manually create an order in Shopline for phone orders, customer service orders, or offline transfers. Submit complete order data to generate the order, with optional inventory deduction and customer notifications.

Instructions

[WRITE] 建立新訂單。

【用途】 在 Shopline 商店中手動建立新訂單,適用於電話訂購、客服補單、線下訂單轉入等場景。 order_data 需包含 Shopline 建立訂單 API 所需的完整欄位。

【呼叫的 Shopline API】

  • POST /v1/orders

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

【副作用】

  • 在商店訂單列表中新增一筆訂單

  • 可能觸發庫存扣減(取決於訂單內容與商店設定)

  • 可能觸發客戶訂單確認通知(取決於商店設定)

  • 建立後訂單立即生效,需確認資料正確再執行

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
order_dataYes完整訂單資料,依 Shopline API 規格傳入所有必要欄位
Behavior4/5

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

With no annotations, the description carries the full burden. It discloses side effects (adds order, may trigger inventory deduction and notifications) and warns that the order becomes active immediately. Missing details on authorization, but sufficient for safe usage.

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 (purpose, usage, API, return structure, side effects). Each sentence adds value, no fluff. Concise yet comprehensive.

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 a single parameter, no output schema, and no annotations, the description covers purpose, usage, return structure, side effects, and warnings. It is complete enough for an agent to use the tool correctly.

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?

Only one parameter 'order_data' with 100% schema coverage. The description adds that it must include all required fields per Shopline API, which is helpful but not substantially beyond what the schema provides. Baseline score 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 it creates new orders ('建立新訂單') and specifies the context (manual order creation for phone orders, customer service, etc.). It includes a [WRITE] tag and distinguishes itself from read or update 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?

The description explicitly lists when to use (phone orders, customer service supplement, offline transfers) and provides context for its use. It could be improved by explicitly stating when not to use (e.g., for updates, use update_order), but overall clear.

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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