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get_archived_orders

Retrieve a list of archived historical orders by specifying a date range. Returns order details including status, payment, delivery, and customer info for long-term records management.

Instructions

【用途】查詢已封存(archived)的歷史訂單列表,適合調閱長期歸檔的舊訂單資料。

【呼叫的 Shopline API】

  • GET /v1/orders/archived

【回傳結構】 { "total_found": int, # 符合條件的總筆數 "returned": int, # 實際回傳筆數 "orders": [ # 精簡訂單列表 { "id": str, "order_number": str, "status": str, "channel": str, # "POS" 或 "線上" "store_name": str, "total": float, "subtotal": float, "discount": float, "payment_type": str, "payment_status": str, "delivery_type": str, "delivery_status": str, "customer_name": str, "items_count": int, "created_at": str, } ] }

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
start_dateYes起始日期 YYYY-MM-DD
end_dateYes結束日期 YYYY-MM-DD
max_resultsNo最多回傳筆數
Behavior4/5

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

With no annotations provided, the description carries the burden. It discloses the API endpoint, return structure, and fields, indicating a read-only query operation. It does not mention rate limits or permissions, but the return structure and purpose are well-covered.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

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

The description is well-structured with sections for purpose, API call, and return structure. It is somewhat long due to the included output schema, but that adds value. Every part is useful, though it could be slightly more concise without losing clarity.

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 complexity (3 parameters, no output schema), the description fully compensates by detailing the return structure, fields, and types. It also includes the API endpoint, making it complete for agent understanding.

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?

Schema coverage is 100%, with descriptions already provided for start_date, end_date, and max_results. The description adds no additional meaning beyond what the schema offers, so it meets the baseline.

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 explicitly states it queries archived/historical order lists, distinguishing it from siblings like 'query_orders' which likely handles active orders. The verb '查詢' and resource '已封存(archived)的歷史訂單列表' are specific and clear.

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 clearly indicates the tool is for accessing long-term archived orders, implying it is not for current orders. It does not explicitly state when not to use or name alternatives, but the context of siblings and the term 'archived' provide clear 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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