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tzangms

shopline-mcp

by tzangms

bulk_update_product_reviews

Batch update multiple product reviews at once to publish or hide comments, with immediate changes to product ratings.

Instructions

[WRITE] 批次更新多筆商品評論。

【用途】 一次性批次審核或修改多筆評論狀態,適用於管理員批次公開或隱藏評論。

【呼叫的 Shopline API】

  • PATCH /v1/product_review_comments

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

【副作用】

  • 批次更新多筆評論,變更立即生效

  • 若有評論狀態變更,相關商品的平均評分可能同步更新

  • 部分評論若 id 不存在,整批可能失敗或僅失敗該筆(視 API 實作而定)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
updatesYes批次更新資料列表,每筆須含 id 欄位,例如 [{"id": "C001", "status": "published"}, {"id": "C002", "status": "hidden"}]
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 and does well by disclosing side effects: changes are immediate, product average ratings may sync, and partial failure behavior depends on API implementation. It also states the return structure. However, it does not mention authentication requirements or rate limits, which would make it more complete.

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 clear sections: purpose, API call, return structure, and side effects. It is concise, every sentence adds value, and the key purpose is front-loaded in the first line.

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?

The description is complete for a single-parameter batch update tool: it provides the API endpoint, a high-level return structure (since no output schema exists), and important side effects including partial failure. The schema covers the parameter, so the combined information is sufficient for an agent to select and invoke the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The only parameter 'updates' is fully described in the schema (100% coverage) with an example and the requirement that each item contain an id field. The tool description adds no additional parameter syntax or field details beyond the schema, so baseline 3 is appropriate.

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 does a batch update of multiple product reviews, with a specific purpose of admin batch publishing or hiding comments. The verb '批次更新' (batch update) and resource '商品評論' (product reviews) are explicit, and it distinguishes from siblings like update_product_review (single) and bulk_create/delete_reviews.

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 identifies a clear use case: '適用於管理員批次公開或隱藏評論' (suitable for administrators to batch publish or hide comments). It provides context for when to use the tool, but does not explicitly mention alternatives or when not to use it, such as using update_product_review for single updates.

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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