Agent skill

Linkfox Sellersprite Competitor Lookup

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

使用卖家精灵数据在亚马逊上查找和分析竞品,覆盖12个站点,包含销量、BSR、定价、评分和增长趋势等商品指标。当用户提到竞品查询、竞品分析、ASIN反查、竞争商品研究、查找相似商品、市场竞品发现、商品对标、竞品销量估算、分析竞争Listing、competitor analysis, ASIN reverse lookup, competitor sales, competitor…

MITAuto-check passedMarketing & SEO

Install Linkfox Sellersprite Competitor Lookup

skills CLI
$ npx skills add linkfox-ai/linkfox-skills --skill linkfox-sellersprite-competitor-lookup -a claude-code

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

GitHub CLI
$ gh skill install linkfox-ai/linkfox-skills linkfox-sellersprite-competitor-lookup --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-sellersprite-competitor-lookup .claude/skills/linkfox-sellersprite-competitor-lookup && 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-sellersprite-competitor-lookup
GitHub stars
107
Used in
1 other repo
Token cost
~2.7k tokens
SKILL.md length
1,145 words
Files
5 (incl. scripts, references)
Skills in repo
177
Repo updated
First seen
Licence
MIT

At a glance

使用卖家精灵数据在亚马逊上查找和分析竞品,覆盖12个站点,包含销量、BSR、定价、评分和增长趋势等商品指标。当用户提到竞品查询、竞品分析、ASIN反查、竞争商品研究、查找相似商品、市场竞品发现、商品对标、竞品销量估算、分析竞争Listing、competitor analysis, ASIN reverse lookup, competitor sales, competitor…

  • Works in 8 steps: Present data clearly: Show query results… → Keyword language: When searching by… → BSR clarification: When displaying BSR… → …
  • Tasks that involve Competitor analysis
  • SKILL.md covers Core Concepts, Supported Marketplaces, Parameter Guide and 调用方式, plus 6 more sections
  • Runs Python scripts from its folder; calls python; needs LINKFOX_AGENT_API_KEY and LINKFOXAGENT_API_KEY

What it does

Linkfox Sellersprite Competitor Lookup is an agent skill from linkfox-ai/linkfox-skills. 使用卖家精灵数据在亚马逊上查找和分析竞品,覆盖12个站点,包含销量、BSR、定价、评分和增长趋势等商品指标。当用户提到竞品查询、竞品分析、ASIN反查、竞争商品研究、查找相似商品、市场竞品发现、商品对标、竞品销量估算、分析竞争Listing、competitor analysis, ASIN reverse lookup, competitor sales, competitor research, SellerSprite, market competitor discovery, competitor trends时触发此技能。即使用户未明确提及"卖家精灵"或"竞品查询",只要其需求涉及通过ASIN、关键词、卖家名称、品牌或品类发现和分析亚马逊竞品,也应触发此技能。

Its SKILL.md is about 2.7k 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/onboarding.py`).

It sits in Marketing & SEO, covering Competitor analysis. The licence is MIT.

When your agent uses it

  • Tasks that involve Competitor analysis

Example prompts

  • “/linkfox-sellersprite-competitor-lookup”

Requirements

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

Workflow steps

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

  1. Present data clearly: Show query results in well-formatted tables. Include key metrics such as ASIN, title, price, monthly sales, BSR…
  2. Keyword language: When searching by keyword, always translate the keyword to the target marketplace language (e.g., English for US/UK…
  3. BSR clarification: When displaying BSR data, remind users that a lower BSR value indicates stronger sales performance.
  4. Growth metrics: When showing growth rates, clarify whether positive values mean improvement or decline (positive BSR growth count means…
  5. Pagination notice: When the total result count exceeds the returned page size, inform the user of the total count and offer to fetch…
  6. Badge highlights: When products carry badges (Best Seller, Amazon's Choice, A+ Content, Video), highlight these in the results as they are…
  7. Error handling: When a query fails, explain the reason based on the message field and suggest adjusting query parameters.
  8. Snapshot guidance: When users want to do seasonal or trend analysis, proactively suggest using historical snapshots (e.g., last year's…

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 Sellersprite Competitor Lookup loads about 2.7k tokens when it runs, and up to ~5.5k if it reads all its reference files. Until then it costs about 95 tokens; SKILL.md has 1,145 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~95
When it runs · the whole SKILL.md, loaded when a task matches
~2.7k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~5.5k

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). 1,145 words, ~2,740 tokens.

Download SKILL.mdSave it as .claude/skills/linkfox-sellersprite-competitor-lookup/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.
name
linkfox-sellersprite-competitor-lookup
description
使用卖家精灵数据在亚马逊上查找和分析竞品,覆盖12个站点,包含销量、BSR、定价、评分和增长趋势等商品指标。当用户提到竞品查询、竞品分析、ASIN反查、竞争商品研究、查找相似商品、市场竞品发现、商品对标、竞品销量估算、分析竞争Listing、competitor analysis, ASIN reverse lookup, competitor sales, competitor research, SellerSprite, market competitor discovery, competitor trends时触发此技能。即使用户未明确提及"卖家精灵"或"竞品查询",只要其需求涉及通过ASIN、关键词、卖家名称、品牌或品类发现和分析亚马逊竞品,也应触发此技能。

SellerSprite Competitor Lookup

This skill guides you on how to query and analyze Amazon competitor product data, helping Amazon sellers discover competing products, benchmark performance, and extract actionable competitive intelligence.

Core Concepts

The SellerSprite Competitor Lookup tool provides comprehensive Amazon product data across 12 marketplaces. It allows querying products by ASIN, keyword, seller name, brand, or category, and returns detailed metrics including monthly sales volume, revenue, BSR ranking, pricing, ratings, and growth trends.

Data snapshots: The tool supports both real-time data (last 30 days) and historical monthly snapshots. Use nearly (default) for current data or a yyyyMM format (e.g., 202501) for historical snapshots. Historical snapshots capture all active listings for that month, enabling year-over-year and seasonal comparisons.

Category hierarchy: Amazon category names support multi-level paths separated by colons (:). For example, Electronics:Computers & Accessories:Monitors. Convert user-provided category descriptions into the proper colon-separated format.

Supported Marketplaces

US (United States), UK (United Kingdom), DE (Germany), FR (France), JP (Japan), CA (Canada), IT (Italy), ES (Spain), MX (Mexico), AU (Australia), TR (Turkey), IN (India)

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

Parameter Guide

Search Filters
ParameterDescriptionExample
marketplaceAmazon marketplace codeUS, UK, DE, JP
keywordSearch keyword (translate to the marketplace language)wireless earbuds
asinListOne or more ASINs, comma-separated (max 40)B072MQ5BRX,B08N5WRWNW
sellerNameSeller name to filter byAnker Direct
brandBrand name to filter byAnker
nodeLabelAmazon category name (colon-separated levels)Electronics:Headphones
nodeIdPathAmazon category ID path172282
matchTypeKeyword match mode: 1 = phrase, 2 = fuzzy, 3 = exact (default 1)1
showVariationShow product variations: Y or N (default N)N
dataSnapshotMonthData snapshot month (nearly for real-time, or yyyyMM)nearly
Pagination & Sorting
ParameterDescriptionExample
pagePage number, starting from 11
sizeResults per page, 10-100 (default 50)50
order.fieldSort field (see sort options below)total_units
order.descSort direction: true = descending, false = ascendingtrue
Sort Field Options
FieldDescription
total_unitsMonthly sales units
total_amountMonthly sales revenue
bsr_rankBSR ranking
pricePrice
ratingRating score
reviewsNumber of reviews
profitGross margin
reviews_rateReview rate
available_dateListing date
questionsQ&A count
total_units_growthMonthly sales unit growth rate
total_amount_growthMonthly revenue growth rate
reviews_increasementMonthly new reviews
bsr_rank_cv7-day BSR growth count
bsr_rank_cr7-day BSR growth rate
amz_unitVariant sales units
Key Response Fields
FieldDescription
asinProduct ASIN
titleProduct title
priceCurrent price
monthlySalesUnitsMonthly sales volume
monthlySalesRevenueMonthly sales revenue
bsrBSR ranking
bsrGrowthRateBSR growth rate
bsrGrowthCountBSR growth count
ratingRating score
ratingsNumber of ratings
ratingsGrowthMonthly new ratings
ratingsRateReview rate
brandBrand name
sellerNameBuyBox seller
sellerNationBuyBox seller nationality
fulfillmentFulfillment type (AMZ/FBA/FBM)
availableDateStringListing date
profitGross margin
nodeLabelPathCategory path
imageUrlProduct image URL
monthlySalesUnitsGrowthRateMonthly sales growth rate
listingQualityScoreListing quality score
variationNumNumber of variations
parentParent ASIN
badgeBestSellerBest Seller badge (Y/N)
badgeAmazonChoiceAmazon's Choice badge (Y/N)
badgeEbcA+ Content (Y/N)
badgeVideoVideo present (Y/N)

调用方式

  • API 端点:POST /sellersprite/competitor-lookup(完整参数/响应/错误码见 references/api.md)
  • Python 脚本:python scripts/sellersprite_competitor_lookup.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-sellersprite-competitor-lookup-<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。

Usage Examples

1. Look up competitors by ASIN

json
{
  "marketplace": "US",
  "asinList": "B072MQ5BRX,B08N5WRWNW"
}

Use case: Analyze specific competing products by their ASINs.

2. Search competitors by keyword

json
{
  "marketplace": "US",
  "keyword": "wireless earbuds",
  "matchType": 1,
  "order": {"field": "total_units", "desc": "true"},
  "size": 20
}

Use case: Discover top-selling products for a keyword, sorted by monthly sales.

3. Filter by brand and category

json
{
  "marketplace": "US",
  "brand": "Anker",
  "nodeLabel": "Electronics:Headphones",
  "order": {"field": "total_amount", "desc": "true"}
}

Use case: Analyze a specific brand's product lineup within a category.

4. Find products by seller name

json
{
  "marketplace": "DE",
  "sellerName": "Anker Direct",
  "order": {"field": "bsr_rank", "desc": "false"}
}

Use case: View all products from a particular seller sorted by BSR.

5. Historical snapshot comparison

json
{
  "marketplace": "US",
  "keyword": "space heater",
  "dataSnapshotMonth": "202412",
  "order": {"field": "total_units", "desc": "true"},
  "size": 20
}

Use case: Analyze seasonal product performance using historical data snapshots.

6. Show product variations

json
{
  "marketplace": "JP",
  "asinList": "B0XXXXXXXXX",
  "showVariation": "Y"
}

Use case: Examine all variation-level data for a product family.

Show full SKILL.md (497 more words)Show less

Display Rules

  1. Present data clearly: Show query results in well-formatted tables. Include key metrics such as ASIN, title, price, monthly sales, BSR, rating, and brand. Do not provide subjective business advice unless the user asks for it.
  2. Keyword language: When searching by keyword, always translate the keyword to the target marketplace language (e.g., English for US/UK, German for DE, Japanese for JP). Remind the user of this if they provide keywords in the wrong language.
  3. BSR clarification: When displaying BSR data, remind users that a lower BSR value indicates stronger sales performance.
  4. Growth metrics: When showing growth rates, clarify whether positive values mean improvement or decline (positive BSR growth count means BSR increased, which means worsened ranking).
  5. Pagination notice: When the total result count exceeds the returned page size, inform the user of the total count and offer to fetch additional pages.
  6. Badge highlights: When products carry badges (Best Seller, Amazon's Choice, A+ Content, Video), highlight these in the results as they are important competitive signals.
  7. Error handling: When a query fails, explain the reason based on the message field and suggest adjusting query parameters.
  8. Snapshot guidance: When users want to do seasonal or trend analysis, proactively suggest using historical snapshots (e.g., last year's same month) for comparison.

Important Limitations

  • Result cap: Each page returns 10-100 records (controlled by size). Use pagination for larger result sets.
  • ASIN limit: A maximum of 40 ASINs can be queried at once via asinList.
  • Historical snapshots: Only existing monthly snapshots can be queried; future dates are not supported.
  • Keyword language: Keywords should match the marketplace language for best results.

User Expression & Scenario Quick Reference

Applicable -- Amazon competitor product data queries:

User SaysScenario
"Find competitors for this ASIN"ASIN-based competitor lookup
"Top sellers for wireless earbuds"Keyword-based product discovery
"What is this seller selling"Seller product portfolio analysis
"Show me products in Electronics category"Category-based browsing
"Monthly sales for these ASINs"Sales estimation for specific products
"New products gaining traction"Growth trend detection
"Compare products across brands"Brand benchmarking
"How was this niche last December"Historical snapshot analysis
"Best sellers with high ratings"Multi-metric filtering
"FBA vs FBM in this category"Fulfillment type analysis

Not applicable -- Needs beyond competitor product data:

  • ABA search term data or keyword ranking (use ABA Data Explorer instead)
  • Advertising / PPC campaign management
  • Product reviews content or sentiment analysis
  • Listing copywriting or optimization suggestions
  • Supplier sourcing or manufacturing costs
  • Account health or policy compliance

算力消耗规则

消耗 15 算力。

用户会因算力消耗而支付费用。请充分评估:当需要高频调用本技能,或用户对算力消耗量预期不足时,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.


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-sellersprite-competitor-lookup of linkfox-ai/linkfox-skills.

  • SKILL.md
  • references/api.md
  • references/onboarding.md
  • scripts/onboarding.py
  • scripts/sellersprite_competitor_lookup.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 Sellersprite Competitor Lookup 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 Sellersprite Competitor Lookup compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Linkfox Sellersprite Competitor Lookup this skilllinkfox-ai/linkfox-skills1071 repos~2.7kAutomated safety check: PassMIT
SEO Content Brief GeneratorAgriciDaniel/claude-seo19k2 repos~2.6kAutomated safety check: PassMIT
SEO DataforseoAgriciDaniel/codex-seo7992 repos~4.6kAutomated safety check: PassMIT
Competitor ProfilingNexus-JPF/note-companion8704 repos~3.5kAutomated safety check: PassMIT
Startup Competitorsferdinandobons/startup-skill1.2k—~4.1kAutomated safety check: PassMIT
Amazon Listing Competitor Analysisbrowser-act/skills6.1k1 repos~3.2kAutomated safety check: PassMIT

Similar skills

  • SEO Content Brief Generator

    AgriciDaniel/claude-seo

    Builds research-backed SEO content briefs with competitor scoring, per-section word counts and page-type templates, for new pages or improving existing ones.

    19k GitHub starsUsed in 2 repos~2.6k tokens
    Marketing & SEOAuto-check passed
  • SEO Dataforseo

    AgriciDaniel/codex-seo

    Live SEO data via DataForSEO MCP server. An agent skill from AgriciDaniel/codex-seo.

    799 GitHub starsUsed in 2 repos~4.6k tokens
    Marketing & SEOAuto-check passed
  • Competitor Profiling

    Nexus-JPF/note-companion

    When the user wants to research, profile, or analyze competitors from their URLs.

    870 GitHub starsUsed in 4 repos~3.5k tokens
    Marketing & SEOAuto-check passed
  • Startup Competitors

    ferdinandobons/startup-skill

    Deep competitive intelligence for any market. An agent skill from ferdinandobons/startup-skill.

    1.2k GitHub stars~4.1k tokensUpdated 3 mo ago
    Marketing & SEOAuto-check passed
  • Analyzes a competitor's Amazon listing by ASIN with BrowserAct data extraction, then reports what it does well, where the market has gaps and opportunity points for your own listing.

    6.1k GitHub starsUsed in 1 repo~3.2k tokens
    Marketing & SEOAuto-check passed
  • SEO Competitor Comparison Pages

    AgriciDaniel/claude-seo

    Generates X vs Y comparison pages, alternatives-to-X pages, best-tools roundups and feature-matrix tables, with schema markup and verifiable data rules.

    19k GitHub starsUsed in 5 repos~1.9k tokens
    Marketing & SEOAuto-check passed

More from linkfox-ai/linkfox-skills

All 177 skills in this repo
  • Linkfox 1688 Search By Image

    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…

    107 GitHub starsUsed in 1 repo~2.4k tokens
    Auto-check passed
  • 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…

    107 GitHub starsUsed in 1 repo~2.2k tokens
    Auto-check passed
  • 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…

    107 GitHub starsUsed in 1 repo~3k tokens
    Auto-check passed
  • 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…

    107 GitHub starsUsed in 1 repo~3k tokens
    Auto-check passed
  • 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…

    107 GitHub starsUsed in 1 repo~2.5k tokens
    Auto-check passed
  • 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…

    107 GitHub starsUsed in 1 repo~2.5k tokens
    Auto-check passed

Categories

Questions about Linkfox Sellersprite Competitor Lookup

What does Linkfox Sellersprite Competitor Lookup do?

使用卖家精灵数据在亚马逊上查找和分析竞品,覆盖12个站点,包含销量、BSR、定价、评分和增长趋势等商品指标。当用户提到竞品查询、竞品分析、ASIN反查、竞争商品研究、查找相似商品、市场竞品发现、商品对标、竞品销量估算、分析竞争Listing、competitor analysis, ASIN reverse lookup, competitor sales, competitor…. Linkfox Sellersprite Competitor Lookup is an agent skill from linkfox-ai/linkfox-skills.

When should I use Linkfox Sellersprite Competitor Lookup?

Linkfox Sellersprite Competitor Lookup fits situations like: tasks that involve Competitor analysis.

How do I install Linkfox Sellersprite Competitor Lookup in Claude Code?

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

How do I install Linkfox Sellersprite Competitor Lookup in Codex?

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

Can I use Linkfox Sellersprite Competitor Lookup 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-sellersprite-competitor-lookup -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-sellersprite-competitor-lookup, .gemini/skills/linkfox-sellersprite-competitor-lookup, .github/skills/linkfox-sellersprite-competitor-lookup and .opencode/skills/linkfox-sellersprite-competitor-lookup in your project.

What does Linkfox Sellersprite Competitor Lookup need to run?

Going by SKILL.md and its folder, Linkfox Sellersprite Competitor Lookup 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 Sellersprite Competitor Lookup 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 Sellersprite Competitor Lookup 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 Sellersprite Competitor Lookup use?

Linkfox Sellersprite Competitor Lookup 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 Sellersprite Competitor Lookup use?

About 2.7k tokens (SKILL.md is roughly 11k 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 2.8k tokens, read only when the agent opens those files.

What are the alternatives to Linkfox Sellersprite Competitor Lookup?

Skills that share tags, products or a category with Linkfox Sellersprite Competitor Lookup: SEO Content Brief Generator (AgriciDaniel/claude-seo, 19k stars), SEO Dataforseo (AgriciDaniel/codex-seo, 799 stars), Competitor Profiling (Nexus-JPF/note-companion, 870 stars) and Startup Competitors (ferdinandobons/startup-skill, 1.2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Linkfox Sellersprite Competitor Lookup?

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.