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get_product_review_detail

Retrieves the full details of a single product review, including rating, text, images, and store reply. Use to examine specific reviews for customer service or quality audit.

Instructions

取得單一商品評價的完整內容,包含圖片與店家回覆。

【用途】 查閱特定評價的詳細資料:完整評論文字、評分、附圖、顧客資訊及店家回覆。 適用於客服處理評價問題、追蹤店家回應進度,或人工審核評價內容。

【呼叫的 Shopline API】

  • GET /v1/product_review_comments/{comment_id}

【回傳結構】 dict 包含:

  • id:評價 ID

  • product_id / product_name:商品資訊

  • rating:評分(通常 1–5)

  • content:完整評論文字

  • images[]:附圖 URL 列表

  • reviewer_name:評價者姓名

  • status:評價審核狀態(如 published, pending)

  • reply:店家回覆內容(若有)

  • created_at, updated_at

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
comment_idYes評價 ID(由 list_product_reviews 回傳的 id 欄位)
Behavior3/5

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

No annotations provided, so the description carries the full burden. It discloses the HTTP method (GET) and return structure, but does not explicitly state it is a read-only operation or mention any authorization or rate limit requirements. The API endpoint and return fields are given, but behavioral traits beyond the obvious are absent.

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 concise and well-structured with sections for purpose, usage, API endpoint, and return structure. Every sentence adds value, and the information is front-loaded for quick understanding. No fluff.

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 tool has no output schema, so the description compensates by listing all expected return fields (id, product info, rating, content, images, reviewer, status, reply, timestamps). Parameter is well-documented. For a simple read tool, this is fully contextual and sufficient.

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?

Only one parameter 'comment_id' with full schema description. The description mentions 'comment_id' in the API path but adds no extra semantic beyond what the schema already provides. Schema coverage is 100%, 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's purpose: retrieving detailed content of a single product review, including images and merchant replies. It uses specific verbs and resources ('取得單一商品評價的完整內容') and distinguishes itself from sibling tools like 'list_product_reviews' (which lists reviews) and 'get_product_subscription_detail' (different domain).

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 provides usage context: customer service, tracking reply progress, manual review. It does not explicitly state when NOT to use it or list alternatives, but the context makes it clear this is for detailed individual review rather than listing. Lacking explicit exclusions for sibling tools, but still clear.

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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