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create_addon_product

Create a new add-on product for Shopline checkout. Define name, price, and quantity to offer customers additional items at checkout.

Instructions

[WRITE] 建立新加購商品。

【用途】 在 Shopline 商店中建立一個新的加購商品(Addon Product),可於結帳時讓顧客選購。

【呼叫的 Shopline API】

  • POST /v1/addon_products

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

【副作用】

  • 在商店加購商品列表中新增一筆記錄

  • 建立後需於促銷或商品設定中啟用才會顯示給顧客

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
addon_dataYes加購商品資料,例如 {name, sku, price, quantity, ...}
Behavior4/5

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

With no annotations provided, the description carries full burden. It explicitly states it is a WRITE operation, calls the POST /v1/addon_products API, and describes the return structure. It also discloses side effects: adds a record and requires enabling. This is adequate behavioral context.

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 organized into clear sections (purpose, API, return structure, side effects). It is front-loaded with the essential WRITE tag. While somewhat lengthy, every sentence adds value, and it is efficiently structured.

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?

Given there is no output schema and only one parameter, the description covers the return structure, API endpoint, and side effects. It is fairly complete for a creation tool, though it lacks error handling or validation details.

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 schema has 100% coverage with a description for the single parameter. The description adds meaningful example fields (name, sku, price, quantity), enhancing understanding beyond the schema's generic '加購商品資料' (addon product data).

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 purpose with specific verb and resource: '建立新加購商品' (create new addon product). It distinguishes from sibling tools like update_addon_product and list_addon_products by explaining its role in creating products for checkout selection.

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 clear context for when to use: to create an addon product for customer selection at checkout. It also notes the side effect that the product needs to be enabled separately, implying when-not-to-use. However, it does not explicitly name alternatives or exclusions, but the context is sufficient given the sibling list.

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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