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tzangms

shopline-mcp

by tzangms

create_customer

Create a customer record in Shopline with name and optional email, phone, tags, gender, or birthday. Designed for manual entry or batch import; duplicates may fail.

Instructions

[WRITE] 建立新客戶。

【用途】 在 Shopline 商店中建立新的客戶記錄。適合客服手動建檔或批次匯入場景。

【呼叫的 Shopline API】

  • POST /v1/customers

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

【副作用】

  • 在商店客戶列表中新增一筆客戶

  • 如果 email 或 phone 已存在,可能會失敗(Shopline 可能不允許重複)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes客戶姓名
tagsNo標籤列表
emailNoEmail
phoneNo電話
genderNo性別 (male/female/other)
birthdayNo生日 YYYY-MM-DD
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. It discloses that it adds a customer to the store's customer list and that duplicate email or phone may cause failure, plus includes return structure and API endpoint. This is strong behavioral disclosure for a create operation, though it omits authentication requirements.

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 headers and bullet-like sections, covering purpose, API, return structure, and side effects without excessive wordiness. Each section adds useful context and the format is easy to scan.

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?

Given no output schema or annotations, the description compensates with return structure, side effects, and API endpoint. It is complete for a simple create tool, covering the essential operational aspects an agent needs to know.

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 already has 100% parameter descriptions, so the baseline is 3. The description adds value by noting that duplicate email or phone may cause failures, which informs how those parameters should be considered, though it doesn't provide format details beyond the schema.

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 it creates a new customer record in Shopline, using the specific verb '建立' (create) and resource '客戶' (customer). It distinguishes from sibling tools like update_customer and delete_customer by explicitly targeting new customer creation.

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 specifies suitable scenarios (manual customer service entry or batch import) and clearly implies it is for new records. It does not explicitly contrast with update_customer for existing customers, but the context is clear enough for an agent to select it.

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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