Amazon Reviews

按ASIN获取并分析亚马逊商品评论，支持15个站点(含美国站)，按星级筛选评论。当用户提到亚马逊评论、美国站评论、商品评价、买家投诉、差评、好评、星级评分、评论分析、评论情感、产品改良建议、Vine评论、已验证购买评论、竞品评论研究、Amazon reviews, US reviews, Amazon.com reviews, product feedback, negative review analysis, positive review analysis, star rating filter, review sentiment analysis, product improvement insights, Vine reviews, competitor reviews, customer feedback时触发此技能。即使用户未明确说"评论"，只要其需求涉及读取、筛选或分析亚马逊商品的买家评论，也应触发此技能。

linkfox-ai@linkfox-ai

Install

openclaw skills install @linkfox-ai/linkfox-amazon-reviews-list

Amazon Product Reviews

Fetch and analyze Amazon product reviews to help sellers extract actionable insights from customer feedback.

Core Concepts

This tool retrieves real customer reviews for a given Amazon ASIN across 15 marketplaces. You can control how many reviews to fetch per star rating (1-5 stars, up to 100 each), sort by recency or helpfulness, and apply various filters. Only one ASIN per request; for multiple ASINs, make separate calls.

调用方式

API 端点：POST /amazon/reviews/list（完整参数/响应/错误码见 references/api.md）
Python 脚本：python scripts/amazon_reviews.py '<JSON 参数>' [--inline]
成本约束：本工具会消耗积分；同一会话同一参数组合默认只调用一次，脚本带 24h 本地缓存。失败/空结果不得自动换关键词、翻页或改邮编连续试探；需要继续检索时先向用户说明会产生额外消耗。

输出策略（脚本默认行为）：

始终将完整响应写入 <cwd>/linkfox/<YYYY-MM-DD>/<session>/data/linkfox-amazon-reviews-list-<timestamp>.json（<cwd> 为脚本执行时的工作目录，在 Claude Code 里即当前项目目录；<session> 取自环境变量 SESSION_ID，按用户任务自动聚合；禁止写入 /tmp，当前目录不可写则报错）
响应体 ≤ 8 KB：落盘后把完整 JSON 打印到 stdout
响应体 > 8 KB：落盘后 stdout 只输出摘要（顶层字段、常见计数如 total/costToken、最大列表字段的长度 + 前 3 条样本）
加 --inline 强制全量打印到 stdout（同样落盘）

读数据建议：先看摘要判断是否足够；需要具体字段时优先用 jq或ConvertFrom-Json 从保存的 json 文件按需抽取，避免整份 JSON 进入上下文。

Parameter Guide

Parameter	Type	Required	Scope	Description	Default
asin	string	Yes	All	Amazon product ASIN	-
star1Num	integer	No	Main endpoint	1-star reviews to fetch (0-100)	10
star2Num	integer	No	Main endpoint	2-star reviews to fetch (0-100)	10
star3Num	integer	No	Main endpoint	3-star reviews to fetch (0-100)	10
star4Num	integer	No	Main endpoint	4-star reviews to fetch (0-100)	10
star5Num	integer	No	Main endpoint	5-star reviews to fetch (0-100)	10
sortBy	string	No	All	`recent` (newest) or `helpful` (most helpful)	`recent`
formatType	string	No	All	`all_formats` or `current_format`	`all_formats`
domainCode	string	No	Main endpoint	Marketplace code (see Supported Marketplaces); use `com` for US	`com`
filterByKeyword	string	No	Main endpoint	Filter reviews by keyword (max 1000 chars)	-
reviewerType	string	No	Main endpoint	`all_reviews` or `avp_only_reviews` (verified only)	`all_reviews`
mediaType	string	No	Main endpoint	`all_contents` or `media_reviews_only`	`all_contents`

Star Count Defaults

If no star count fields are provided, star1Num to star5Num all default to 10.
If any star count field is provided, unspecified star counts default to 0.

Supported Marketplaces

Marketplace	Code
United States	`com`
Canada	`ca`
United Kingdom	`co.uk`
Germany	`de`
France	`fr`
Italy	`it`
Spain	`es`
Japan	`co.jp`
India	`in`
Australia	`com.au`
Brazil	`com.br`
Mexico	`com.mx`
Netherlands	`nl`
Sweden	`se`
United Arab Emirates	`ae`

Use domainCode for every supported marketplace. Always confirm the user's intended marketplace.

Usage Examples

1. Fetch US reviews (Amazon.com)

json

{"asin": "B08N5WRWNW", "domainCode": "com", "star1Num": 10, "star2Num": 10, "star3Num": 10, "star4Num": 10, "star5Num": 10, "sortBy": "recent"}

2. Fetch negative reviews with keyword filter (Germany)

json

{"asin": "B08N5WRWNW", "domainCode": "de", "star1Num": 30, "star2Num": 30, "filterByKeyword": "quality", "reviewerType": "avp_only_reviews"}

3. Fetch 5-star reviews with media (Japan)

json

{"asin": "B08N5WRWNW", "domainCode": "co.jp", "star5Num": 50, "star1Num": 0, "star2Num": 0, "star3Num": 0, "star4Num": 0, "sortBy": "helpful", "mediaType": "media_reviews_only"}

4. Fetch only 3-star reviews (explicit star mode)

json

{"asin": "B0FP5C63HZ", "domainCode": "com", "star3Num": 100}

Display Rules

Present data clearly: Show reviews grouped by star rating with key fields: rating, title, text, date, verified status, helpful count.
Summarize when appropriate: For many reviews, provide a theme/pain-point summary before listing individuals.
Highlight actionable insights: Call out recurring complaints in negative reviews; note praised features in positive reviews.
Vine and verified labels: Clearly indicate Vine Voice and verified purchase status.
Media indicators: Note when reviews include images or videos.
Response normalization: Normalize rating and helpful-count fields for consistent display when the raw response uses marketplace-specific text formats.
Error handling: When a query fails, explain the reason based on the response message and suggest adjusting parameters.
Single ASIN limitation: If the user asks about multiple ASINs, make separate requests for each.

Important Limitations

One ASIN per request: Only a single ASIN can be queried at a time.
Per-star cap: Each star rating returns max 100 reviews per request.
Parameter scope: filterByKeyword, reviewerType, mediaType are available on /amazon/reviews/list, including domainCode: "com".
No historical snapshots: Reviews are fetched in real-time.
Review text language: Reviews are returned in their original language as posted.

User Expression & Scenario Quick Reference

Applicable — Tasks involving Amazon product reviews:

User Says	Scenario
"Show me the reviews for this ASIN"	Direct review lookup
"Get US reviews for B08N5WRWNW"	Marketplace-specific lookup
"What are customers complaining about"	Negative review analysis
"Get me all the 1-star reviews"	Star-filtered retrieval
"Any common issues in the bad reviews"	Pain point mining
"What do people like about this product"	Positive review analysis
"Find reviews mentioning 'battery'"	Keyword-filtered reviews
"Show me reviews with photos"	Media-filtered reviews
"Verified purchase reviews only"	Reviewer-type filtering
"Help me analyze competitor reviews"	Competitor review research
"Product improvement suggestions from reviews"	Actionable insight extraction

Not applicable — Needs beyond product review data:

ABA search term data / keyword research (use ABA Data Explorer instead)
Sales estimation or revenue analysis
Listing copywriting or A+ content creation
Advertising / PPC strategy
Pricing strategy or profit margin calculations

Boundary judgment: If "product research" or "competitor analysis" boils down to reading customer reviews for specific ASINs, this skill applies. If it involves search volume, keyword rankings, sales estimates, or market sizing, it does not.

Feedback:

Auto-detect and report feedback via the Feedback API when any of the following apply:

The functionality or purpose described in this skill does not match actual behavior
The skill's results do not match the user's intent
The user expresses dissatisfaction or praise about this skill
Anything you believe could be improved

Call the feedback API as specified in the references. Do not interrupt the user's flow.

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