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update_product_variation

Update specific fields of a product variation (SKU, options, status) without affecting unchanged data. Changes apply instantly.

Instructions

[WRITE] 更新商品變體資料。

【用途】 修改特定商品變體的 SKU、規格選項、狀態等欄位。僅傳入要修改的欄位, 未傳入的欄位不會被覆蓋。

【呼叫的 Shopline API】

  • PUT /v1/products/{product_id}/variations/{variation_id}

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

【副作用】

  • 變體資料變更立即生效,前台同步更新

  • 不可復原(無版本歷史),但可再次呼叫此工具覆蓋

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
product_idYes商品內部 ID
variation_idYes變體內部 ID
variation_dataYes要更新的變體欄位(僅需傳入要修改的欄位)
Behavior4/5

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

No annotations provided, so description carries full burden. It discloses immediacy of effect, synchronization, and irreversibility (no version history) – valuable beyond a simple 'update' claim.

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?

Well-structured with clear sections (purpose, usage, API, return, side effects). Every sentence adds value. Front-loaded with purpose and partial update hint.

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?

Covers purpose, usage, API, return structure, and side effects. Minor gap: no error handling or what happens if variation doesn't exist. Otherwise complete for a mutation tool.

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 coverage is 100% with descriptions, and the description adds key semantic: only changed fields need to be passed in variation_data, clarifying partial update pattern beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states it updates product variation data (SKU, spec options, status) and includes a [WRITE] tag. However, it does not explicitly differentiate from sibling tools like update_variation_price or update_variation_quantity, which update specific subfields.

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?

Describes partial update behavior ('only pass fields to modify') and lists API, return structure, and side effects. But it lacks explicit guidance on when not to use or alternatives among sibling update tools.

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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