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get_order_labels

Get shipping label details for an order, including tracking number, carrier, and label URL. Print logistics labels or check shipment tracking numbers.

Instructions

【用途】取得指定訂單的配送標籤資訊,可用於列印物流面單或查詢寄件單號。

【呼叫的 Shopline API】

  • GET /v1/orders/{order_id}/labels

【回傳結構】 API 原始回應,通常包含: { "labels": [ { "tracking_number": str, # 物流追蹤號碼 "carrier": str, # 物流商名稱 "label_url": str, # 標籤列印 URL ... } ] }

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
order_idYes訂單內部 ID(由 query_orders 回傳的 id 欄位,非 order_number)
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It discloses that the tool calls a GET API and provides the expected response structure with fields like tracking_number and label_url, indicating it is read-only. It does not mention prerequisites or error conditions, but the API call and response are well-documented.

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 (用途, 呼叫的 API, 回傳結構) and is concise. Every sentence adds value, and the key information is front-loaded.

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 description covers the purpose, API call, and output format with a sample response. For a simple read tool with one parameter and no output schema, it is fairly complete. It could mention prerequisites like order existence, but the provided information is sufficient for basic usage.

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 description does not add any information about the order_id parameter beyond what the input schema already provides. However, schema coverage is 100% and the schema description clearly explains that the ID is from query_orders and not the order_number, so the 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 verb (取得/Get), the resource (配送標籤資訊/shipping label info for a specific order), and the purpose (列印物流面單或查詢寄件單號). It distinguishes this tool from other order-related tools like get_order_detail or get_order_delivery, as it specifically deals with labels.

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 implies usage for printing labels or tracking shipments, which gives context. However, it does not explicitly state when not to use this tool or mention alternatives compared to sibling tools. The specific purpose is clear but lacks explicit usage guidance for an agent.

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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