| name | linkfox-amazon-reviews-list |
| description | 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。 |
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。
解决认证和积分问题
发生以下异常情况时，采用 references/onboarding.md 引导解决问题：
异常情况
- 未配置API Key：环境变量未配置
LINKFOX_AGENT_API_KEY，也未配置 LINKFOXAGENT_API_KEY。
- 响应401或402状态码
- 响应提示积分或余额不足：消息含"积分余额不足/计费不足/余额不足/quota exceeded/insufficient balance/套餐到期/需充值/请充值"，或类似含义的内容。
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)
{"asin": "B08N5WRWNW", "domainCode": "com", "star1Num": 10, "star2Num": 10, "star3Num": 10, "star4Num": 10, "star5Num": 10, "sortBy": "recent"}
2. Fetch negative reviews with keyword filter (Germany)
{"asin": "B08N5WRWNW", "domainCode": "de", "star1Num": 30, "star2Num": 30, "filterByKeyword": "quality", "reviewerType": "avp_only_reviews"}
3. Fetch 5-star reviews with media (Japan)
{"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)
{"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.
积分消耗规则
按计划抓取页数动态计费。设 P = Σ min(ceil(各星级请求评论数 / 10), 10)，则：
- 计费 Token：
21000 × P。
- 实际消耗积分 =
ceil((21000 × P) / 2000) = ceil(10.5 × P)，按每次请求分别向上取整。
- 未传任何星级数量时，1~5 星默认各抓取 10 条，
P = 5，消耗 53 积分。
- 传入任意星级数量后，未传星级按
0；五个星级均显式传 0 时，P = 0，不调用供应商且消耗 0 积分。
- 请求成功但结果为空，或经关键词、认证购买、媒体筛选后为空，仍按计划页数计费；部分子任务失败但整体成功时仍按全部计划页数计费；调用完全失败不计费。
常见消耗：1 页 11 积分，2 页 21 积分，5 页 53 积分，10 页 105 积分。
重要：费用按请求的抓取页数计算，而不是按最终返回评论数计算。请求多个星级或大量评论前必须向用户说明预计页数和积分消耗。
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.
For more high-quality, professional cross-border e-commerce skills, visit LinkFox Skills.
