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linkfox-amazon-reviewsLinkfox 亚马逊评论

Agent Skill

linkfox-amazon-reviews 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

3,491

周安装

144

GitHub Stars

公开资料未说明

下载量

1,140
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:linkfox-amazon-reviews(Linkfox 亚马逊评论)
来源仓库:https://github.com/linkfox-ai/linkfox-amazon-reviews
安装命令:
openclaw skills install linkfox-amazon-reviews
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install linkfox-amazon-reviews

简介

按 ASIN 获取并分析亚马逊商品评论,支持星级筛选。

  • 适用于差评诊断、产品改进与客户情绪洞察。linkfox-amazon-reviews 属于研究检索类 Skill,可作为该场景下的辅助能力补充。
  • 覆盖15个站点含美国站,区分 Vine 与普通评论。
  • 情感分析结果仅供参考,需人工复核关键意见。
  • 避免仅依赖评分做决策,应结合数量与分布判断。

SKILL.md

name
linkfox-amazon-reviews
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.

API Routing

US and non-US marketplaces use different backend endpoints. Route by marketplace:

  • USscripts/amazon_us_reviews.py, pass marketplace: "US". See references/api_us.md
  • Othersscripts/amazon_reviews.py, pass domainCode: "<code>". See references/api.md

Parameter Guide

ParameterTypeRequiredScopeDescriptionDefault
asinstringYesAllAmazon product ASIN-
star1NumintegerNoAll1-star reviews to fetch (0-100)Non-US: 10, US: 0
star2NumintegerNoAll2-star reviews to fetch (0-100)Non-US: 10, US: 0
star3NumintegerNoAll3-star reviews to fetch (0-100)Non-US: 10, US: 0
star4NumintegerNoAll4-star reviews to fetch (0-100)Non-US: 10, US: 0
star5NumintegerNoAll5-star reviews to fetch (0-100)Non-US: 10, US: 0
sortBystringNoAllrecent (newest) or helpful (most helpful)recent
formatTypestringNoAllcurrent_format or all_formatscurrent_format
domainCodestringNoNon-USMarketplace code (see Supported Marketplaces)ca
filterByKeywordstringNoNon-USFilter reviews by keyword (max 1000 chars)-
reviewerTypestringNoNon-USall_reviews or avp_only_reviews (verified only)all_reviews
mediaTypestringNoNon-USall_contents or media_reviews_onlyall_contents
marketplacestringNoUSFixed value USUS
allStarsNumintegerNoUSReviews across all stars (0-100); active when star1-5Num are all 010
positiveNumintegerNoUS4-5 star positive reviews (0-100)0
criticalNumintegerNoUS1-3 star critical reviews (0-100)0

Supported Marketplaces

MarketplaceCode
United StatesUS
Canadaca
United Kingdomco.uk
Germanyde
Francefr
Italyit
Spaines
Japanco.jp
Indiain
Australiacom.au
Brazilcom.br
Mexicocom.mx
Netherlandsnl
Swedense
United Arab Emiratesae

US uses the marketplace parameter; all others use domainCode. Always confirm the user's intended marketplace.

Usage Examples

1. Fetch US reviews — balanced snapshot

{"asin": "B08N5WRWNW", "marketplace": "US", "allStarsNum": 20, "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"}

Display Rules

  1. Present data clearly: Show reviews grouped by star rating with key fields: rating, title, text, date, verified status, helpful count.
  2. Summarize when appropriate: For many reviews, provide a theme/pain-point summary before listing individuals.
  3. Highlight actionable insights: Call out recurring complaints in negative reviews; note praised features in positive reviews.
  4. Vine and verified labels: Clearly indicate Vine Voice and verified purchase status.
  5. Media indicators: Note when reviews include images or videos.
  6. Response normalization: US reviews return rating as full text (e.g., "5.0 out of 5 stars") and numberOfHelpful as string — extract numeric values for consistent display. US reviews may also include attributes (color, size, etc.) — display them to show which variant was reviewed.
  7. Error handling: When a query fails, explain the reason based on the response message and suggest adjusting parameters.
  8. 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 only available for non-US marketplaces; allStarsNum, positiveNum, criticalNum are only available for the US marketplace.
  • 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 SaysScenario
"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 (non-US)
"Show me reviews with photos"Media-filtered reviews (non-US)
"Verified purchase reviews only"Reviewer-type filtering (non-US)
"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:

  1. The functionality or purpose described in this skill does not match actual behavior
  2. The skill's results do not match the user's intent
  3. The user expresses dissatisfaction or praise about this skill
  4. 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.*

适合场景

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用户想查找某类 Agent Skill 时

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能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

88.34%
按下载量换算1,007

安全审计

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未展示

ClawScan

可疑

Static analysis

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

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