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tzangms

shopline-mcp

by tzangms

list_customer_groups

Retrieve a list of customer groups, optionally filtered by name, to review segmentation strategies or obtain group IDs for member queries.

Instructions

取得客戶群組列表,支援依名稱搜尋。

【用途】 瀏覽或搜尋已建立的客戶群組(分群)。可用於確認客戶標籤分群策略、 取得群組 ID 後進一步查詢群組成員。

【呼叫的 Shopline API】

  • GET /v1/customer_groups(無搜尋條件時)

  • GET /v1/customer_groups/search(有搜尋條件時)

【回傳結構】 dict 含 total_found, returned, groups[]。 每個 group 包含 id, name, customers_count, created_at。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
max_resultsNo最多回傳筆數
search_keywordNo群組名稱搜尋關鍵字
Behavior4/5

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

With no annotations provided, the description carries the behavioral disclosure burden. It discloses the two underlying API endpoints (GET /customer_groups and /search) and the return structure, which provides meaningful transparency. It does not mention pagination limits or error behavior, but the disclosed info is substantial.

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-organized with sections for purpose, API calls, and return structure. The main summary sentence is front-loaded, and every section earns its place without redundancy.

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?

As a simple list tool with no output schema, the description fully compensates by explaining the return structure (total_found, returned, groups[]) and the group fields. It also covers use cases and API behavior, making it complete for an agent to invoke 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?

Schema coverage is 100% for both parameters, so the baseline is 3. The description adds value by clarifying that search_keyword determines which API is called (search endpoint vs. list endpoint), giving behavioral context beyond the schema's simple field descriptions.

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: '取得客戶群組列表,支援依名稱搜尋' (Get customer group list, supports searching by name). It distinguishes itself from sibling tools like get_customer_group_members by noting it provides group IDs for further member queries.

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 explains when to use the tool (browse/search groups, confirm segmentation strategy, get group ID for member lookup). It implies a workflow but does not explicitly name alternatives or state when not to use 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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