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tzangms

shopline-mcp

by tzangms

list_delivery_options

Get all active delivery methods from your store, including home delivery, convenience store pickup, and in-store pickup. Confirm shipping options and analyze customer delivery preferences.

Instructions

取得商店啟用的配送方式清單。

【用途】 查看商店目前設定的所有配送方式,例如宅配、超商取貨、 門市自取等。適合確認可用配送渠道或分析訂單配送偏好。

【呼叫的 Shopline API】

  • GET /v1/delivery_options

【回傳結構】 dict 含 total, delivery_options[]。 每個 delivery_option 包含 id, name, delivery_type, status, fee_type, rates(運費級距), supported_countries, support_cod 等。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

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 of behavioral disclosure. It reveals the underlying API call (GET /v1/delivery_options), which implies a read-only operation, and describes the return structure with fields like id, name, delivery_type, status, fee_type, rates, supported_countries, and support_cod. This exceeds a bare listing but stops short of disclosing pagination, auth requirements, or rate limits.

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 headings: purpose, API call, and return structure. It is front-loaded with a one-sentence summary and then expands with useful details. Every section adds value and nothing is redundant or verbose.

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?

For a simple list tool with no parameters and no output schema, the description covers all necessary aspects: purpose, use cases, the exact API endpoint, and the return structure including key fields. It is self-contained and gives the agent enough to select 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?

The input schema is empty (0 parameters), so there is no parameter detail to clarify. Per the guidelines, 0 params yields a baseline of 4. The description appropriately focuses on output rather than parameters.

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 function: '取得商店啟用的配送方式清單' (get the list of enabled delivery options). It specifies the resource (delivery options), the verb (list/get), and the scope (enabled ones). This distinguishes it from the sibling tool get_delivery_option_detail, which fetches a single option.

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 【用途】section explicitly states suitable use cases: '適合確認可用配送渠道或分析訂單配送偏好' (suitable for confirming available delivery channels or analyzing order delivery preferences). It provides clear context but does not mention exclusions or alternatives, so it earns a 4 rather than a 5.

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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