文档

Jiimore-细分市场评论

试用

亚马逊细分市场评论分析与消费者情感洞察。当用户提到细分市场评论分析、消费者情感、用户痛点、客户反馈洞察、评论主题分析、好评差评拆解、细分市场舆情挖掘、产品评论情感分析、niche market reviews, consumer sentiment, customer pain points, review topic analysis, positive/negative reviews, opinion mining, Jiimore data时触发此技能。即使用户未明确提及"细分市场评论",只要其需求涉及分析亚马逊细分市场中的消费者评论或理解细分市场层面的客户情感,也应触发此技能。

它能做什么

亚马逊细分市场评论分析与消费者情感洞察。当用户提到细分市场评论分析、消费者情感、用户痛点、客户反馈洞察、评论主题分析、好评差评拆解、细分市场舆情挖掘、产品评论情感分析、niche market reviews, consumer sentiment, customer pain points, review topic analysis, positive/negative reviews, opinion mining, Jiimore data时触发此技能。即使用户未明确提及"细分市场评论",只要其需求涉及分析亚马逊细分市场中的消费者评论或理解细分市场层面的客户情感,也应触发此技能。

技能文档

Jiimore Niche Review from Keyword

This skill guides you on how to query and analyze Amazon niche market review data powered by Jiimore, helping Amazon sellers uncover consumer sentiment, pain points, and real demand signals from product reviews within niche markets.

Core Concepts

Niche Review Analysis aggregates and categorizes customer reviews across products in an Amazon niche market. Given a keyword, the system identifies the relevant niche markets, extracts review topics, classifies them as positive or negative, and shows how frequently each topic is mentioned. This enables sellers to understand what customers love, what frustrates them, and where product improvement opportunities exist.

Review types: Each review entry is classified as either "positive" or "negative", reflecting the overall sentiment of that review topic.

Mention percentage: The percentOfMentions value (0-1 scale, representing 0%-100%) indicates how frequently a particular topic appears across all reviews in the niche. A higher percentage means more customers are talking about that topic.

Supported Marketplaces

US (United States), JP (Japan), DE (Germany)

Default marketplace is US. Use US when the user does not specify a marketplace.

调用方式

  • API 端点POST /jiimore/getNicheReviewFromKeyword(完整参数/响应/错误码见 references/api.md
  • Python 脚本python scripts/jiimore_get_niche_review.py '' [--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 /linkfox///data/linkfox-jiimore-get-niche-review-from-keyword-.json 为脚本执行时的工作目录,在 Claude Code 里即当前项目目录; 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)
  • --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 jqConvertFrom-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

Required Parameter

ParameterTypeDescription
keywordstringThe search keyword (max 1000 chars). Must be in the language of the target marketplace (English for US, German for DE, Japanese for JP)

Marketplace & Pagination

ParameterTypeDefaultDescription
countryCodestringUSCountry code: US, JP, or DE
pageinteger1Page number (starting from 1)
pageSizeinteger50Results per page (10-100)

Sorting

ParameterTypeDefaultDescription
sortFieldstringunitsSoldT7Field to sort by (see Sortable Fields below)
sortTypestringdescSort direction: desc (descending) or asc (ascending)

Sortable Fields:

FieldDescription
unitsSoldT7Units sold (7-day)
searchVolumeT7Search volume (7-day)
searchVolumeGrowthT7Search volume growth (7-day)
clickConversionRateT7Click conversion rate (7-day)
searchConversionRateT7Search conversion rate (7-day)
clickCountT7Click count (7-day)
demandDemand score
avgPriceAverage price
maximumPriceMaximum price
minimumPriceMinimum price
productCountProduct count
brandCountBrand count
top5BrandsClickShareTop 5 brands click share
top5ProductsClickShareTop 5 products click share
clickCountT90Click count (90-day)
clickConversionRateT90Click conversion rate (90-day)
searchConversionRateT90Search conversion rate (90-day)
searchVolumeT90Search volume (90-day)
unitsSoldT90Units sold (90-day)
unitsSoldGrowthT90Units sold growth (90-day)
searchVolumeGrowthT90Search volume growth (90-day)
returnRateT360Return rate (360-day)
newProductsLaunchedT180New products launched (180-day)
successfulLaunchesT180Successful launches (180-day)
launchRateT180Launch success rate (180-day)
acosACOS
profitRate50Profit rate at 50% organic orders

Niche Filtering Parameters

All filter parameters follow a min/max range pattern. Values for percentage-based fields use a 0-1 scale (e.g., 0.05 = 5%).

Product & Brand Metrics:

ParameterTypeDescription
productCountMin / productCountMaxintegerProduct count range
brandCountMin / brandCountMaxintegerBrand count range
avgPriceMin / avgPriceMaxnumberAverage price range

Sales & Search Volume:

ParameterTypeDescription
unitsSoldT7Min / unitsSoldT7MaxintegerUnits sold (7-day) range
searchVolumeT7Min / searchVolumeT7MaxintegerSearch volume (7-day) range
clickCountT7Min / clickCountT7MaxintegerClick count (7-day) range

Conversion & Click Rates (0-1 scale):

ParameterTypeDescription
clickConversionRateT7Min / clickConversionRateT7MaxnumberClick conversion rate (7-day) range

Market Concentration (0-1 scale):

ParameterTypeDescription
top5BrandsClickShareMin / top5BrandsClickShareMaxnumberTop 5 brands click share range
top5ProductsClickShareMin / top5ProductsClickShareMaxnumberTop 5 products click share range
sponsoredProductsPercentageMin / sponsoredProductsPercentageMaxnumberSP ad percentage range

Brand & Seller Age:

ParameterTypeDescription
avgBrandAgeMin / avgBrandAgeMaxnumberAverage brand age (current)
avgBrandAgeQoqMin / avgBrandAgeQoqMaxnumberAverage brand age (90-day)
avgBrandAgeYoyMin / avgBrandAgeYoyMaxnumberAverage brand age (360-day)
avgSellingPartnerAgeMin / avgSellingPartnerAgeMaxnumberAverage seller age (current)
avgSellingPartnerAgeQoqMin / avgSellingPartnerAgeQoqMaxnumberAverage seller age (90-day)
avgSellingPartnerAgeYoyMin / avgSellingPartnerAgeYoyMaxnumberAverage seller age (360-day)

New Product & Return Metrics (0-1 scale):

ParameterTypeDescription
launchRateT180Min / launchRateT180MaxnumberLaunch success rate (180-day) range
newProductRateT180numberNew product percentage (180-day) min
returnRateT360Min / returnRateT360MaxnumberReturn rate (360-day) range

Advertising:

ParameterTypeDescription
cpcMediumMin / cpcMediumMaxnumberCPC (current) range

Usage Examples

1. Basic niche review lookup for a keyword

Analyze customer reviews in niche markets related to "yoga mat" on the US marketplace.

Parameters: {"keyword": "yoga mat", "countryCode": "US"}

2. Find niche reviews with high search volume

Show me niche market reviews for "wireless earbuds" where 7-day search volume is above 10000.

Parameters: {"keyword": "wireless earbuds", "countryCode": "US", "searchVolumeT7Min": 10000}

3. Low competition niches with review insights

Find review insights for "pet bed" niches where top 5 brands hold less than 30% click share.

Parameters: {"keyword": "pet bed", "countryCode": "US", "top5BrandsClickShareMax": 0.3}

4. Japanese market niche reviews

Analyze niche reviews for wireless earbuds on the Japan marketplace.

Parameters: {"keyword": "wireless earbuds", "countryCode": "JP"}

5. Sorted by demand score

Show niche reviews for "kitchen organizer" sorted by demand score in descending order.

Parameters: {"keyword": "kitchen organizer", "sortField": "demand", "sortType": "desc"}

6. Filter by new product success rate

Find niches for "phone case" where the 180-day new product launch success rate is above 20%.

Parameters: {"keyword": "phone case", "launchRateT180Min": 0.2}

7. Low return rate niches

Show review topics for "water bottle" niches with return rates below 5%.

Parameters: {"keyword": "water bottle", "returnRateT360Max": 0.05}

Display Rules

  1. Present data clearly: Show review topics in a well-organized table. Include the niche name, review type (positive/negative), topic, mention percentage, and a review example
  2. Percentage formatting: Convert 0-1 scale values to percentages for display (e.g., 0.15 -> 15%)
  3. Sentiment separation: When presenting results, group or clearly label positive vs. negative reviews so users can quickly identify opportunities and pain points
  4. Actionable insight framing: While showing data objectively, highlight high-mention-percentage negative reviews as potential product improvement opportunities, and high-mention-percentage positive reviews as features to emphasize in listings
  5. Volume notice: When results are large, show the most relevant data first and remind users about pagination options
  6. Error handling: When a query fails, explain the reason and suggest adjusting the keyword or filter criteria
  7. Language reminder: If a user provides a keyword in the wrong language for the target marketplace, remind them to use the marketplace's native language (English for US, German for DE, Japanese for JP)

User Expression & Scenario Quick Reference

Applicable -- Consumer review and sentiment analysis within Amazon niche markets:

User SaysScenario
"What do customers say about XX"Niche review topic lookup
"Customer pain points for XX"Negative review analysis
"What features do buyers love in XX"Positive review analysis
"Review sentiment for XX niche"Full sentiment breakdown
"Consumer demand insights for XX"Demand signal extraction from reviews
"Common complaints about XX products"Negative topic mining
"What makes XX products popular"Positive topic mining
"Niche market review analysis"General niche review exploration

Not applicable -- Needs beyond niche review analysis:

  • Individual ASIN review analysis (this tool works at the niche/market level)
  • Keyword search volume trends without review context (use ABA data tools instead)
  • Product listing optimization or copywriting
  • Advertising strategy and PPC management
  • Sales estimation or revenue forecasting

Boundary judgment: When users say "market research" or "product opportunity", if their intent focuses on understanding consumer sentiment, review topics, and pain points within a niche market, this skill applies. If they are asking about search volume trends, pricing strategy, or sales data without review context, it does not apply.

积分消耗规则

消耗 9 积分。

用户会因积分消耗而支付费用。请充分评估:当需要高频调用本技能,或用户对积分消耗量预期不足时,务必提醒用户,由用户决定是否继续。

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 references/api.md. Do not interrupt the user's flow.


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