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tzangms

shopline-mcp

by tzangms

get_archived_orders

Retrieve archived historical order lists from Shopline within a specified date range. Use it to access long-term archived orders that are no longer active.

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
end_dateYes結束日期 YYYY-MM-DD。建議與 start_date 維持較短區間以加快查詢。
start_dateYes起始日期 YYYY-MM-DD。⚠️ 本工具會逐頁掃描區間內所有訂單,區間越大越慢,請只查實際需要的最小區間(如單週或單月),避免一次查詢過長期間。
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, the description carries the burden of behavioral disclosure. It adds valuable context by revealing that the tool scans all orders page by page and that larger date ranges degrade performance, and it provides a detailed return structure. It does not explicitly state read-only behavior, but the verb '查詢' implies a safe read operation, and the performance warning is a meaningful behavioral trait beyond the schema.

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 endpoint, and return structure. It is front-loaded with the purpose and contains no redundant or filler content. The return structure is detailed but necessary for an agent to understand what to expect, and the entire description is compact given the information it conveys.

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?

Despite lacking annotations and an output schema, the description compensates fully by including the exact API endpoint, a complete return structure with field names and types, and performance-related behavior. It gives an agent everything needed to invoke the tool and interpret results, making it contextually complete for a read-only list operation.

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 description coverage is 100%, so the structured parameter descriptions already handle parameter meaning. The tool description itself does not add extra semantic detail about parameters; the useful caveats (short date range, pagination) are already present in the input schema, which is the appropriate place. Baseline 3 is warranted because the schema does the heavy lifting.

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 queries archived historical order lists with a specific verb and resource, and distinguishes it from order-related siblings by focusing on archived data. It explicitly says '查詢已封存(archived)的歷史訂單列表' and notes it is suitable for reviewing long-term archived old orders, leaving no ambiguity about scope.

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 provides a clear use case ('適合調閱長期歸檔的舊訂單資料') and implies it is for archived orders as opposed to regular order queries. However, it does not explicitly name alternatives (e.g., query_orders) or state when not to use this tool, so it stops short of full alternative-driven 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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