Agent skill

Linkfox Keepa Product Search

by linkfox-ai in linkfox-ai/linkfox-skills

基于Keepa数据的亚马逊高级商品搜索与筛选,支持品类、价格、月销量、关键词、BSR排名、评论数、评分、包装尺寸、重量、配送方式等多维度条件。当用户提到Keepa选品、亚马逊商品查找、高级选品、BSR筛选、按销售排名选品、月销量过滤、关键词选品、品类选品、竞品筛选、小众商品发掘、历史排名筛选、Keepa product selection, advanced product…

MITAuto-check passed

Install Linkfox Keepa Product Search

skills CLI
$ npx skills add linkfox-ai/linkfox-skills --skill linkfox-keepa-product-search -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install linkfox-ai/linkfox-skills linkfox-keepa-product-search --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/linkfox-ai/linkfox-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/linkfox-keepa-product-search .claude/skills/linkfox-keepa-product-search && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
linkfox-keepa-product-search
GitHub stars
107
Used in
1 other repo
Token cost
~3.6k tokens
SKILL.md length
1,468 words
Files
5 (incl. scripts, references)
Skills in repo
177
Repo updated
First seen
Licence
MIT

At a glance

基于Keepa数据的亚马逊高级商品搜索与筛选,支持品类、价格、月销量、关键词、BSR排名、评论数、评分、包装尺寸、重量、配送方式等多维度条件。当用户提到Keepa选品、亚马逊商品查找、高级选品、BSR筛选、按销售排名选品、月销量过滤、关键词选品、品类选品、竞品筛选、小众商品发掘、历史排名筛选、Keepa product selection, advanced product…

  • Works in 6 steps: Determine the marketplace: Map the… → Set keyword filters: Use keyword for… → Set category scope: Use… → …
  • SKILL.md covers Core Concepts, Parameters, 调用方式 and 解决认证和算力问题, plus 5 more sections
  • Runs Python scripts from its folder; calls python; needs LINKFOX_AGENT_API_KEY and LINKFOXAGENT_API_KEY

What it does

Linkfox Keepa Product Search is an agent skill from linkfox-ai/linkfox-skills. 基于Keepa数据的亚马逊高级商品搜索与筛选,支持品类、价格、月销量、关键词、BSR排名、评论数、评分、包装尺寸、重量、配送方式等多维度条件。当用户提到Keepa选品、亚马逊商品查找、高级选品、BSR筛选、按销售排名选品、月销量过滤、关键词选品、品类选品、竞品筛选、小众商品发掘、历史排名筛选、Keepa product selection, advanced product selection, BSR filtering, sales filtering, category search, competitor screening, historical data filtering, Amazon product selection时触发此技能。即使用户未明确提及"Keepa",只要其需求涉及多条件亚马逊商品搜索、按销售指标筛选商品或超越简单关键词搜索的高级选品,也应触发此技能。

Its SKILL.md is about 3.6k tokens, which your agent loads only when the skill is triggered. The skill folder holds 6 other files, including scripts and reference files (for example `references/api.md`, `references/onboarding.md` and `scripts/keepa_product_search.py`).

The licence is MIT.

Example prompts

  • “/linkfox-keepa-product-search”

Requirements

  • Python 3
  • A credential in LINKFOX_AGENT_API_KEY
  • A credential in LINKFOXAGENT_API_KEY

Workflow steps

6 steps, taken from the first numbered list in SKILL.md.

  1. Determine the marketplace: Map the user's target country to the correct domain ID value
  2. Set keyword filters: Use keyword for title-based filtering with positive and negative terms
  3. Set category scope: Use categoriesIncludeNames or rootCategoryNames to scope by category; convert user input into proper category path…
  4. Apply numeric filters: Map sales volume, price, BSR, review, and rating requirements to the appropriate Gte/Lte parameters
  5. Set sort order: If the user wants results sorted by sales, price, or rating, configure the sort array
  6. Enable historical data: Set history to 1 if the user needs monthly sales trends or price history

What it can do on your machine

Read from SKILL.md and the folder at commit 38fef04. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 2 files in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • skill.linkfox.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • LINKFOX_AGENT_API_KEY
    • LINKFOXAGENT_API_KEY

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Linkfox Keepa Product Search loads about 3.6k tokens when it runs, and up to ~6.7k if it reads all its reference files. Until then it costs about 107 tokens; SKILL.md has 1,468 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~107
When it runs · the whole SKILL.md, loaded when a task matches
~3.6k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~6.7k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from linkfox-ai/linkfox-skills at commit 38fef04, republished under its MIT licence (© linkfox-ai). 1,468 words, ~3,605 tokens.

Download SKILL.mdSave it as .claude/skills/linkfox-keepa-product-search/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.
name
linkfox-keepa-product-search
description
基于Keepa数据的亚马逊高级商品搜索与筛选,支持品类、价格、月销量、关键词、BSR排名、评论数、评分、包装尺寸、重量、配送方式等多维度条件。当用户提到Keepa选品、亚马逊商品查找、高级选品、BSR筛选、按销售排名选品、月销量过滤、关键词选品、品类选品、竞品筛选、小众商品发掘、历史排名筛选、Keepa product selection, advanced product selection, BSR filtering, sales filtering, category search, competitor screening, historical data filtering, Amazon product selection时触发此技能。即使用户未明确提及"Keepa",只要其需求涉及多条件亚马逊商品搜索、按销售指标筛选商品或超越简单关键词搜索的高级选品,也应触发此技能。

This skill guides you on how to search and filter Amazon products using Keepa's extensive product database, helping Amazon sellers find products that match specific criteria across multiple dimensions.

Core Concepts

This tool provides advanced Amazon product search powered by Keepa data. Unlike a simple Amazon storefront search, it supports multi-criteria filtering: category, price range, monthly sales volume, BSR (Best Sellers Rank), keyword matching (positive and negative), review counts, ratings, package dimensions, weight, fulfillment type, historical sales rank, and more. It returns detailed product data including pricing, titles, images, listing dates, materials, weights, monthly sales for the past 12 months, and more.

BSR (Best Sellers Rank): A lower salesRank value means better sales performance. Rank 1 is the best-selling product in its category. When a user says "top-selling products", they want low BSR values.

Price unit: Prices are expressed in the smallest currency unit (e.g., cents for USD). So $25.99 = 2599. Always convert when building queries and when displaying results.

Category names: The categoriesIncludeNames parameter supports multi-level category paths separated by a colon : or the > character. Automatically convert user input into the correct format.

Parameters

Marketplace (Required)
ParameterTypeRequiredDescriptionDefault
domainstringYesAmazon marketplace ID-

Domain ID mapping:

IDMarketplace
1Amazon.com (United States)
2Amazon.co.uk (United Kingdom)
3Amazon.de (Germany)
4Amazon.fr (France)
5Amazon.co.jp (Japan)
6Amazon.ca (Canada)
8Amazon.it (Italy)
9Amazon.es (Spain)
10Amazon.in (India)
11Amazon.com.mx (Mexico)

Default marketplace is 1 (US). Use domain 1 when the user doesn't specify a marketplace.

Keyword Filtering
ParameterTypeDescription
keywordstringTitle keyword filter (case-insensitive; space = AND; wrap phrases in double quotes; prefix with - to exclude; & is replaced by space; max 50 keywords, max 1000 chars)
Category Filtering
ParameterTypeDescription
rootCategoryarray[int]Root category IDs (max 50)
rootCategoryNamesarray[string]Root category names (max 50); used when rootCategory is empty; system auto-resolves IDs
categoriesIncludearray[int]Sub-category IDs to include (max 50)
categoriesIncludeNamesarray[string]Sub-category names to include (max 50); supports full category paths with : or > separators
categoriesExcludearray[int]Sub-category IDs to exclude (max 50)
categoriesExcludeNamesarray[string]Sub-category names to exclude (max 50); supports full category paths
Sales & Ranking Filters
ParameterTypeDescription
currentSalesGteintegerCurrent BSR -- minimum (higher number = worse rank)
currentSalesLteintegerCurrent BSR -- maximum (lower number = better rank)
avg90SalesGteinteger90-day average BSR -- minimum
avg90SalesLteinteger90-day average BSR -- maximum
deltaPercent90SalesGteinteger90-day BSR change percentage -- minimum
deltaPercent90SalesLteinteger90-day BSR change percentage -- maximum
monthlySoldGteintegerMonthly sales units -- minimum
monthlySoldLteintegerMonthly sales units -- maximum
srAvgGteintegerHistorical average BSR -- minimum (for a specific month)
srAvgLteintegerHistorical average BSR -- maximum (for a specific month)
srAvgMonthstringHistorical BSR month selection (format: YYYYMM, within last 36 months)
Price Filters
ParameterTypeDescription
currentNewGteintegerCurrent new price -- minimum (smallest currency unit)
currentNewLteintegerCurrent new price -- maximum (smallest currency unit)
currentBuyBoxShippingGteintegerCurrent Buy Box price including shipping -- minimum (smallest currency unit)
currentBuyBoxShippingLteintegerCurrent Buy Box price including shipping -- maximum (smallest currency unit)
Review & Rating Filters
ParameterTypeDescription
currentCountReviewsGteintegerReview count -- minimum
currentCountReviewsLteintegerReview count -- maximum
currentRatingGtenumberRating -- minimum (0.0-5.0)
currentRatingLtenumberRating -- maximum (0.0-5.0)
Package & Dimensions Filters
ParameterTypeDescription
packageLengthGte / packageLengthLteintegerPackage length range (mm)
packageWidthGte / packageWidthLteintegerPackage width range (mm)
packageHeightGte / packageHeightLteintegerPackage height range (mm)
packageWeightGte / packageWeightLteintegerPackage weight range (grams)
Other Filters
ParameterTypeDescription
brandarray[string]Brand names (OR match)
colorarray[string]Colors (OR match)
sizearray[string]Sizes (OR match)
availableDateGte / availableDateLtestringListing date range (yyyy-MM-dd)
buyBoxIsAmazonbooleanBuy Box seller is Amazon
buyBoxIsFBAbooleanBuy Box is FBA fulfilled
isHazMatbooleanHazardous material flag
variationCountGte / variationCountLteintegerVariation count range
currentCountNewGte / currentCountNewLteintegerNumber of new offers range
outOfStockPercentage90Gte / outOfStockPercentage90Lteinteger90-day out-of-stock percentage range
singleVariationbooleanReturn only one variation per parent ASIN
productTypearray[int]Product types: 0=standard, 1=downloadable, 2=ebook, 5=variation parent
Data Options
ParameterTypeDescriptionDefault
historyintegerInclude historical data (price history, sales rank, monthly sales per month)0 (no)
ratingintegerInclude rating info1 (yes)
Pagination & Sorting
ParameterTypeDescriptionDefault
pageintegerPage number (starting from 1)1
perPageintegerResults per page (min 50, max 100)50
sortarray[object]Sort rules (max 3); each object: `{"fieldName": "...", "sortDirection": "ascdesc"}`

Sortable fields: availableDate, currentSales, monthlySold, currentRating, currentCountReviews, currentBuyBoxShipping, currentNew

调用方式

  • API 端点:POST /keepa/productSearch(完整参数/响应/错误码见 references/api.md)
  • Python 脚本:python scripts/keepa_product_search.py '<JSON 参数>' [--inline]
  • 成本约束:本工具会消耗算力;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-keepa-product-search-<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。

解决认证和算力问题

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
  • 响应提示算力或余额不足:消息含"算力余额不足/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。

How to Build Queries

Construct the request parameters based on the user's intent:

  1. Determine the marketplace: Map the user's target country to the correct domain ID value
  2. Set keyword filters: Use keyword for title-based filtering with positive and negative terms
  3. Set category scope: Use categoriesIncludeNames or rootCategoryNames to scope by category; convert user input into proper category path format
  4. Apply numeric filters: Map sales volume, price, BSR, review, and rating requirements to the appropriate Gte/Lte parameters
  5. Set sort order: If the user wants results sorted by sales, price, or rating, configure the sort array
  6. Enable historical data: Set history to 1 if the user needs monthly sales trends or price history
Show full SKILL.md (574 more words)Show less
Usage Examples

1. Search for electronics with monthly sales over 1000 on US marketplace

json
{"domain": "1", "rootCategoryNames": ["Electronics"], "monthlySoldGte": 1000}

2. Find products in a price range with good ratings

json
{"domain": "1", "currentBuyBoxShippingGte": 1500, "currentBuyBoxShippingLte": 5000, "currentRatingGte": 4.0, "keyword": "wireless charger"}

3. New products listed in the last 6 months with low review counts

json
{"domain": "1", "availableDateGte": "2025-10-01", "currentCountReviewsLte": 50, "monthlySoldGte": 500}

4. BSR rank filtering for competitive analysis

json
{"domain": "1", "categoriesIncludeNames": ["Home & Kitchen"], "currentSalesLte": 5000, "sort": [{"fieldName": "monthlySold", "sortDirection": "desc"}]}

5. Find non-Amazon FBA products with good sales

json
{"domain": "1", "buyBoxIsAmazon": false, "buyBoxIsFBA": true, "monthlySoldGte": 300, "currentRatingGte": 4.0}

6. Lightweight small products for easy shipping

json
{"domain": "1", "packageWeightLte": 500, "packageLengthLte": 200, "packageWidthLte": 150, "packageHeightLte": 100, "monthlySoldGte": 200}

7. Search on Japan marketplace with historical data

json
{"domain": "5", "keyword": "USB charger", "history": 1, "monthlySoldGte": 100}

8. Brand-specific search excluding hazardous materials

json
{"domain": "1", "brand": ["Anker", "UGREEN"], "isHazMat": false, "sort": [{"fieldName": "monthlySold", "sortDirection": "desc"}]}

Display Rules

  1. Present data clearly: Show search results in well-structured tables with key fields: ASIN, title, price, BSR, monthly sales, rating, review count, brand
  2. Price conversion: Convert prices from smallest currency unit to standard format (e.g., 2599 -> $25.99)
  3. BSR clarification: When showing BSR data, remind users that lower values mean better sales ranking
  4. Monthly sales history: When historical data is included, present the 12-month sales trend clearly
  5. Pagination notice: Inform users of the total result count and suggest fetching additional pages if needed
  6. Image links: If image URLs are available, mention them but do not attempt to render them inline unless the user requests it
  7. Error handling: When a query fails, explain the reason and suggest adjusting filter criteria

Important Limitations

  • Result cap: Maximum 100 results per page, minimum 50
  • Sort limit: Maximum 3 sort rules per query
  • Category limit: Maximum 50 category IDs or names per filter
  • Keyword limit: Maximum 50 keywords in keyword parameter
  • Historical data cost: Setting history=1 increases response size and token cost significantly
  • Price unit: All price values are in the smallest currency unit (cents, pence, etc.)

User Expression & Scenario Quick Reference

Applicable -- Multi-criteria Amazon product search and filtering:

User SaysScenario
"Find products with monthly sales over X"Sales volume filtering
"Search for products in XX category"Category-based product discovery
"Products with BSR under X"Sales rank filtering
"New products listed in the last N months"New product discovery
"Products priced between $X and $Y"Price range filtering
"FBA products with good ratings"Fulfillment + rating filter
"Lightweight products under X grams"Package dimension filtering
"Products from brand XX"Brand-specific search
"Show me historical sales data for XX"Historical sales analysis
"Advanced product selection", "product screening"Multi-criteria product research
"Niche product hunting", "find low-competition products"Competitive gap analysis
"BSR trends", "sales rank history"Historical rank filtering

Not applicable -- Needs beyond product search:

  • Real-time Amazon search result page simulation (use Amazon Search)
  • Historical search term volume or ranking trends (use ABA data)
  • Product review content or sentiment analysis
  • Advertising campaign management or bid optimization
  • Listing optimization or copywriting suggestions
  • Inventory or supply chain data

Boundary judgment: When users say "product research" or "find products", if it involves filtering by sales metrics, BSR, price, category, and other structured criteria, this skill applies. If they want to see what appears on the actual Amazon search page for a keyword, use Amazon Search instead. If they want search term analytics, use ABA data.

算力消耗规则

按动态规则计费:消耗算力 = 0.045 × (找商品阶段消耗的 Keepa token + 拉取商品详情阶段消耗的 Keepa token)。先找商品,再拉商品详情;若第一段未找到商品,则只计找商品阶段消耗。

重要:本技能的服务按倍数动态计算,可能一次性消耗大量算力,必须提醒用户,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.


For more high-quality, professional cross-border e-commerce skills, set LinkFox Skills.

© linkfox-ai, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 4 other files (scripts, references) in skills/linkfox-keepa-product-search of linkfox-ai/linkfox-skills.

  • SKILL.md
  • references/api.md
  • references/onboarding.md
  • scripts/keepa_product_search.py
  • scripts/onboarding.py

Open the folder on GitHubat commit 38fef04

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in linkfox-ai/linkfox-skills, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Linkfox Keepa Product Search next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Linkfox Keepa Product Search compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Linkfox Keepa Product Search this skilllinkfox-ai/linkfox-skills1071 repos~3.6kAutomated safety check: PassMIT
Linkfox Onboardinginfometa/workbuddyskills348—~1.8kAutomated safety check: PassNone
Linkfox Aigc Textgeninfometa/workbuddyskills348—~1.5kAutomated safety check: PassNone
Linkfox Keepa Product Requestlinkfox-ai/linkfox-skills1071 repos~2.4kAutomated safety check: PassMIT
Linkfox Keepa Product Serieslinkfox-ai/linkfox-skills1071 repos~2.5kAutomated safety check: PassMIT
Linkfox Sellersprite Product Searchlinkfox-ai/linkfox-skills1071 repos~3.6kAutomated safety check: PassMIT

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    Mercado Libre(美客多)选品数据查询与分析,通过 LinkFox 网关统一调用 24 个商品、官链、关键词、类目、趋势、店铺、评论、汇率与套餐用量工具,覆盖墨西哥、巴西、阿根廷、智利、哥伦比亚站点。当用户提到 Mercado Libre、美客多、美客多选品、商品搜索、类目趋势、关键词热搜、流量词反查、店铺查询、评论查询、汇率、套餐用量时触发此技能。

    107 GitHub stars~2k tokensUpdated 27 days ago
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More from linkfox-ai/linkfox-skills

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    linkfox-ai/linkfox-skills

    1688平台以图搜图,通过商品图片精准检索外观相似或同款的1688货源,返回标题、价格、起批量、月销量、复购率、交易评分等核心数据。当用户提到1688以图搜图、1688找货源、以图找同款、跨境找工厂、1688识图、图片找货源、找相似货源、image search 1688、find supplier by…

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  • Linkfox Aba Intelligent Query

    linkfox-ai/linkfox-skills

    亚马逊ABA(品牌分析)搜索词数据的查询与分析,涵盖15个站点近3年的周维度数据。当用户提到ABA数据、亚马逊搜索词分析、关键词挖掘、搜索排名趋势、市场机会分析、季节性关键词、高点击低转化分析、蓝海词发现、竞品关键词分析、ABA data, search term report, keyword mining, search ranking trends, blue ocean…

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  • Linkfox Amazon Alexa Search

    linkfox-ai/linkfox-skills

    通过亚马逊前台的 Alexa 购物助手发起自然语言问答,获取与问题相关的导购回答、推荐商品分组、ASIN 列表,以及可继续追问的问题。每次调用仅支持 1 条 prompt,如需追问须由 agent 总结上下文后拼接新问题发起新请求。可用 url 补充亚马逊页面上下文。当用户提到亚马逊 Alexa、Alexa 购物助手、亚马逊智能助手、AI…

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  • 亚马逊反向选品:基于历史商业洞察报告沉淀的指标数据池,按 30+ 项商业维度(市场规模与增长、价格区间与档位份额、竞争密度与头部集中度、人群画像如年龄/性别/收入、评论卖点与痛点等)反向筛选亚马逊赛道与关键词。当用户提到反向选品、指标筛选、细分市场反查、蓝海赛道挖掘、低竞争赛道、新人友好赛道、品牌分散市场、痛点切入、卖点反查、定价档位机会、人群画像选品、Amazon niche reverse…

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  • Linkfox Amazon Product Detail

    linkfox-ai/linkfox-skills

    通过ASIN获取亚马逊商品详细信息,包括标题、图片、五点描述、规格参数、A+页面、价格、评分评论、变体等;可在取得原始HTML时尝试提取Item Highlights(商品亮点)。当用户提到亚马逊商品详情、ASIN查询、商品页面数据、Listing分析、五点描述提取、Item…

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  • Linkfox Amazon Reviews List

    linkfox-ai/linkfox-skills

    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…

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Questions about Linkfox Keepa Product Search

What does Linkfox Keepa Product Search do?

基于Keepa数据的亚马逊高级商品搜索与筛选,支持品类、价格、月销量、关键词、BSR排名、评论数、评分、包装尺寸、重量、配送方式等多维度条件。当用户提到Keepa选品、亚马逊商品查找、高级选品、BSR筛选、按销售排名选品、月销量过滤、关键词选品、品类选品、竞品筛选、小众商品发掘、历史排名筛选、Keepa product selection, advanced product…. Linkfox Keepa Product Search is an agent skill from linkfox-ai/linkfox-skills.

How do I install Linkfox Keepa Product Search in Claude Code?

Run `npx skills add linkfox-ai/linkfox-skills --skill linkfox-keepa-product-search -a claude-code`. Or copy the skill folder (skills/linkfox-keepa-product-search in linkfox-ai/linkfox-skills) into .claude/skills/linkfox-keepa-product-search in your project. Claude Code loads it when a task matches its description.

How do I install Linkfox Keepa Product Search in Codex?

Run `npx skills add linkfox-ai/linkfox-skills --skill linkfox-keepa-product-search -a codex`. Or copy the skill folder (skills/linkfox-keepa-product-search in linkfox-ai/linkfox-skills) into .agents/skills/linkfox-keepa-product-search in your project. Codex loads it when a task matches its description.

Can I use Linkfox Keepa Product Search in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add linkfox-ai/linkfox-skills --skill linkfox-keepa-product-search -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/linkfox-keepa-product-search, .gemini/skills/linkfox-keepa-product-search, .github/skills/linkfox-keepa-product-search and .opencode/skills/linkfox-keepa-product-search in your project.

What does Linkfox Keepa Product Search need to run?

Going by SKILL.md and its folder, Linkfox Keepa Product Search needs Python for the scripts in its folder, the command-line tools its instructions call (python) and credentials named LINKFOX_AGENT_API_KEY and LINKFOXAGENT_API_KEY. Our summary lists: Python 3; A credential in LINKFOX_AGENT_API_KEY; A credential in LINKFOXAGENT_API_KEY.

Does Linkfox Keepa Product Search access the network?

SKILL.md names 1 domain. As links in the text: skill.linkfox.com. This is read from the text; nothing was executed.

Is Linkfox Keepa Product Search safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Linkfox Keepa Product Search use?

Linkfox Keepa Product Search is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Linkfox Keepa Product Search use?

About 3.6k tokens (SKILL.md is roughly 14k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 3.1k tokens, read only when the agent opens those files.

What are the alternatives to Linkfox Keepa Product Search?

Skills that share tags, products or a category with Linkfox Keepa Product Search: Linkfox Onboarding (infometa/workbuddyskills, 348 stars), Linkfox Aigc Textgen (infometa/workbuddyskills, 348 stars), Linkfox Keepa Product Request (linkfox-ai/linkfox-skills, 107 stars) and Linkfox Keepa Product Series (linkfox-ai/linkfox-skills, 107 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Linkfox Keepa Product Search?

linkfox-ai (a GitHub user) maintains it in linkfox-ai/linkfox-skills, which has 107 GitHub stars. The repository holds 177 skills in this directory. The repository was last updated on September 14, 2026.

Source: linkfox-ai/linkfox-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.