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tzangms

shopline-mcp

by tzangms

update_addon_product

Modify an addon product's name, price, image, or other fields by specifying the product ID and the fields to update. The changes take effect immediately and can be revised by calling again.

Instructions

[WRITE] 更新加購商品資料。

【用途】 修改指定加購商品的名稱、價格、圖片等欄位。僅傳入要修改的欄位。

【呼叫的 Shopline API】

  • PUT /v1/addon_products/{addon_product_id}

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

【副作用】

  • 修改指定加購商品的資料,變更立即生效

  • 不可復原,但可再次呼叫此工具覆蓋

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
addon_dataYes要更新的加購商品欄位,例如 {name, price, ...}
addon_product_idYes加購商品 ID
Behavior4/5

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

With no annotations provided, the description carries the full burden. It marks the operation as [WRITE], discloses the exact Shopline API endpoint, return structure, and side effects (immediate effect, irreversible but can be overwritten). This is strong disclosure, though it omits permission requirements and error/failure behavior.

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 uses clear section headers (Purpose, API, Return Structure, Side Effects) with bullets, and each section contributes non-redundant information. It is slightly verbose but well-organized and front-loaded with the [WRITE] tag.

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 two parameters, no output schema, and no annotations, the description covers the essential context: purpose, partial-update semantics, the underlying API call, return structure, and side effects. It does not cover error conditions or permission requirements, but the core information is present.

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?

Schema descriptions cover both parameters (100%), and the description adds the key semantic that addon_data is a partial update object—only fields to change need to be passed—with examples like {name, price, ...}. This clarifies intent beyond the schema's generic object definition.

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 updates addon product data (更新加購商品資料) and specifies the fields that can be modified (name, price, image). It also implies partial updates by saying only the fields to change are passed, distinguishing it from list/create/quantity-specific sibling tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides usage context by noting 'only pass in the fields to modify' (僅傳入要修改的欄位), which clarifies partial update behavior. However, it does not explicitly state when to use this tool over the alternative sibling tools (e.g., update_addon_product_quantity) or when not to use it, so guidance is incomplete.

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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