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Sellersprite Product Search

作者 linkfox-ai · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
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在 OpenClaw 中安装
/install linkfox-sellersprite-product-search
功能描述
使用卖家精灵数据搜索和筛选亚马逊商品,支持价格、月销量、BSR排名、毛利率、评分、配送方式、标签、卖家来源等多维度条件,覆盖多个亚马逊站点。当用户提到亚马逊选品调研、产品筛选、销量过滤、产品发掘、BSR分析、小众商品发现、竞品分析、市场机会评估、按商品维度的市场规模估算、毛利率筛选、SellerSprite pr...
使用说明 (SKILL.md)

SellerSprite Product Search

This skill guides you on how to search, filter, and analyze Amazon product data via the SellerSprite product database, helping Amazon sellers make data-driven product selection decisions.

Core Concepts

SellerSprite Product Search provides access to a comprehensive Amazon product database with rich filtering dimensions. It supports real-time data (last 30 days) as well as monthly historical snapshots for year-over-year and month-over-month comparisons. Data spans multiple Amazon marketplaces including US, UK, DE, FR, JP, CA, IT, ES, MX, and IN.

BSR (Best Sellers Rank): A lower BSR value means better sales performance in its category. A BSR of 1 means the top-selling product in that category. When a user says "BSR improved", it means the numeric value decreased; "BSR dropped" means the value increased.

Data snapshot: The dataSnapshotMonth parameter controls which time period to query. Use nearly (the default) for real-time last-30-day data, or a yyyyMM string (e.g., 202412) to query a historical monthly snapshot. This is useful for seasonal analysis and year-over-year comparison.

Match types for keywords: When searching by keyword, three matching strategies are available:

  • Phrase match (default): Product titles must contain the keyword phrase
  • Fuzzy match: Broader matching with related terms
  • Exact match: Strict exact-string matching

Parameter Guide

Search & Filtering

Parameter Type Description Default
keyword string Search keyword; translate to the target marketplace language (e.g., English for US, German for DE) -
matchType integer 1 = Phrase match, 2 = Fuzzy match, 3 = Exact match 1
excludeKeywords string Keywords to exclude from results -
marketplace string Marketplace code: US, UK, DE, FR, JP, CA, IT, ES, MX, IN US
nodeLabel string Amazon category name -
nodeIdPath string Amazon category node ID -
filterSubNode boolean Whether to filter by subcategory node (only effective when nodeLabel or nodeIdPath is set) -
dataSnapshotMonth string Data snapshot month in yyyyMM format, or nearly for real-time last 30 days nearly

Price & Financials

Parameter Type Description
minPrice / maxPrice number Price range filter
minProfit / maxProfit number Gross margin range (1-100, unit: %)
minRevenue / maxRevenue number Monthly revenue range
minFba / maxFba number FBA fee range

Sales & Ranking

Parameter Type Description
minUnits / maxUnits integer Monthly sales volume range
minUnitsGrowthRate / maxUnitsGrowthRate number Monthly sales growth rate (%)
minBsr / maxBsr integer Main-category BSR rank range
minBsrGrowthRate / maxBsrGrowthRate number BSR growth rate (%)
minBsrGrowthCount / maxBsrGrowthCount integer BSR growth count
minSubNodeBsrRank / maxSubNodeBsrRank integer Subcategory BSR rank (requires filterSubNode = true)

Reviews & Ratings

Parameter Type Description
minRating / maxRating number Rating score range (0-5); 3.8-4.3 indicates product improvement opportunity
minRatings / maxRatings integer Number of ratings range (0-10000)
minRatingsGrowthCount / maxRatingsGrowthCount integer Monthly new ratings count
minListingQualityScore / maxListingQualityScore number Listing quality score range

Product Attributes

Parameter Type Description
minVariations / maxVariations integer Variation count range
minWeights / maxWeights number Weight range
weightUnit string Weight unit: g, kg, oz, lb (required if weight filters are used)
dimensionType string Package dimension type (marketplace-specific codes)
minSellers / maxSellers integer Number of sellers range

Badges & Fulfillment

Parameter Type Description
badgeBestSeller string Best Seller badge: Y / N / empty (all)
badgeAmazonsChoice string Amazon's Choice badge: Y / N / empty (all)
badgeNewRelease string New Release badge: Y / N / empty (all)
fulfillment string Fulfillment type: AMZ, FBA, FBM (comma-separated for multiple)
showVariation string Show variations: Y / N (default N)

Seller & Brand

Parameter Type Description
sellerNation string Seller country code (e.g., US, CN, HK); comma-separated for multiple
includeSellers / excludeSellers string Include / exclude specific sellers
includeBrands / excludeBrands string Include / exclude specific brands

Listing & Pagination

Parameter Type Description Default
hideUnlistedProduct boolean Hide delisted products true
listedWithinLastMonths integer Listed within last N months (1, 3, 6, 12, or 24) -
page integer Page number, starting from 1 1
size integer Results per page (10-100) 20

Sorting

Use the order object with two fields:

Field Type Description
field string Sort field: total_units, total_amount, bsr_rank, price, rating, reviews, profit, reviews_rate, available_date, questions, total_units_growth, total_amount_growth, reviews_increasement, bsr_rank_cv, bsr_rank_cr, amz_unit
desc string "true" for descending, "false" for ascending

Default sort: total_units descending.

API Usage

This tool calls the LinkFox tool gateway API. See references/api.md for calling conventions, request parameters, and response structure. You can also execute scripts/sellersprite_product_search.py directly to run queries.

Usage Examples

1. Find high-sales products in a niche Search for products with keyword "yoga mat" in the US marketplace with monthly sales above 500 units, sorted by monthly sales descending.

{
  "keyword": "yoga mat",
  "marketplace": "US",
  "minUnits": 500,
  "order": {"field": "total_units", "desc": "true"}
}

2. Discover new product opportunities with low competition Find recently listed products (within 6 months) in the US with fewer than 50 ratings and monthly revenue above $5,000.

{
  "keyword": "desk organizer",
  "marketplace": "US",
  "listedWithinLastMonths": 6,
  "maxRatings": 50,
  "minRevenue": 5000,
  "order": {"field": "total_units", "desc": "true"}
}

3. Product improvement opportunity mining Find products with ratings between 3.8 and 4.3 (improvement sweet spot), monthly sales above 300, in a specific category.

{
  "keyword": "phone case",
  "marketplace": "US",
  "minRating": 3.8,
  "maxRating": 4.3,
  "minUnits": 300,
  "order": {"field": "total_units", "desc": "true"}
}

4. High-margin product screening Find products with gross margin above 40%, price between $15 and $50, at least 100 monthly sales.

{
  "marketplace": "US",
  "minProfit": 40,
  "minPrice": 15,
  "maxPrice": 50,
  "minUnits": 100,
  "order": {"field": "profit", "desc": "true"}
}

5. Seasonal year-over-year comparison Query last year's December snapshot data to compare with current data for seasonal product planning.

{
  "keyword": "christmas lights",
  "marketplace": "US",
  "dataSnapshotMonth": "202412",
  "minUnits": 200,
  "order": {"field": "total_units", "desc": "true"}
}

6. Chinese seller competitive landscape Find FBA-fulfilled products from Chinese sellers in a category with high monthly sales.

{
  "keyword": "bluetooth speaker",
  "marketplace": "US",
  "sellerNation": "CN",
  "fulfillment": "FBA",
  "minUnits": 200,
  "order": {"field": "total_units", "desc": "true"}
}

7. Best Seller & Amazon's Choice badge holders Find products carrying the Best Seller badge with strong sales performance.

{
  "keyword": "water bottle",
  "marketplace": "US",
  "badgeBestSeller": "Y",
  "order": {"field": "total_units", "desc": "true"}
}

8. Fast-growing products by sales growth rate Find products with monthly sales growth rate above 50%.

{
  "keyword": "standing desk",
  "marketplace": "US",
  "minUnitsGrowthRate": 50,
  "order": {"field": "total_units_growth", "desc": "true"}
}

Display Rules

  1. Present data clearly: Show query results in well-structured tables. Key columns to prioritize: ASIN, title, price, monthly sales, monthly revenue, BSR rank, rating, ratings count, gross margin, fulfillment type
  2. BSR clarification: When showing BSR data, remind users that lower values mean better rankings
  3. Gross margin note: Gross margin values are percentages. Remind users this is an estimate based on price minus FBA fees and estimated costs
  4. Pagination awareness: When the total count exceeds the returned page size, inform the user of the total result count and suggest adjusting page or size parameters to see more results
  5. Snapshot labeling: When displaying historical snapshot data, clearly label the data period (e.g., "Data from December 2024 snapshot") to avoid confusion with real-time data
  6. Error handling: When a query fails, explain the reason based on the message field and suggest adjusting query criteria
  7. Weight unit reminder: When the user provides weight filters without specifying a unit, ask them to confirm the weight unit (g, kg, oz, or lb) before proceeding
  8. Keyword translation: When the user provides keywords in a language different from the target marketplace, translate the keyword to the appropriate language and note the translation

Important Limitations

  • Result cap: Each page returns a maximum of 100 records (size parameter max is 100)
  • Historical snapshots: Only past monthly snapshots are available; future dates are not supported
  • Weight unit required: If any weight filter is used, the weightUnit must also be provided
  • Subcategory BSR: The subcategory BSR rank filters only work when filterSubNode is set to true
  • Listed time enum only: The listedWithinLastMonths parameter only accepts specific values: 1, 3, 6, 12, or 24

User Expression & Scenario Quick Reference

Applicable -- Product-level data queries on Amazon:

User Says Scenario
"Find products with high sales in XX category" Niche product search
"Show me low-competition products", "new product opportunities" Blue ocean product discovery
"Which products have high margins" Profitability screening
"Products with rising sales", "trending products" Growth trend detection
"What are Chinese sellers selling well" Competitive landscape analysis
"Recently launched products doing well" New product tracking
"Products with bad reviews but good sales" Product improvement opportunities
"Compare this category with last year" Seasonal / YoY analysis
"FBA products under $30 with 1000+ sales" Multi-criteria product filtering
"Best sellers in XX category" Badge-based product discovery

Not applicable -- Needs beyond product-level search data:

  • ABA search term / keyword analysis (use ABA Data Explorer instead)
  • Advertising / PPC campaign data
  • Product review text analysis
  • Listing copywriting or optimization
  • Supplier sourcing or manufacturing costs
  • Logistics and inventory planning

Boundary judgment: When users say "product research" or "market analysis", if it boils down to filtering Amazon products by sales, price, BSR, ratings, and other product attributes, then this skill applies. If they are asking about keyword search volume, search term rankings, or click/conversion share data, the ABA Data Explorer skill is more appropriate.

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.

安全使用建议
Before installing, confirm the missing declaration of the required API key: the included script and docs expect LINKFOXAGENT_API_KEY but the registry metadata lists no required env vars. Verify you trust the endpoints (tool-gateway.linkfox.com and skill-api.linkfox.com) and the skill owner (no homepage provided). Ask the publisher to: (1) update the registry metadata to declare LINKFOXAGENT_API_KEY as a required credential, (2) provide a homepage or publisher identity, and (3) clarify whether any feedback or telemetry is sent automatically. If you proceed, only supply an API key with scoped permissions you trust and monitor network usage; do not reuse high‑privilege secrets.
功能分析
Type: OpenClaw Skill Name: linkfox-sellersprite-product-search Version: 1.0.0 The skill bundle provides a legitimate tool for searching and filtering Amazon product data via the SellerSprite API. The Python script (sellersprite_product_search.py) uses standard libraries to make authenticated POST requests to a documented gateway, and the instructions in SKILL.md are consistent with the tool's stated purpose of e-commerce market research.
能力评估
Purpose & Capability
The SKILL.md and the included Python script both call the SellerSprite productSearch API at https://tool-gateway.linkfox.com and require an API key (LINKFOXAGENT_API_KEY). That capability aligns with the skill's stated purpose (Amazon product search). However, the registry metadata lists no required environment variables or primary credential, which contradicts the code and API docs. The skill source/homepage is also missing, reducing traceability.
Instruction Scope
Runtime instructions and the script are narrowly scoped to building a JSON request and POSTing it to the documented SellerSprite API, then formatting results. The SKILL.md also indicates the skill should auto-trigger for broad product-research intents (may be over-broad but not in itself malicious). The instructions do not attempt to read other system files or unrelated env vars.
Install Mechanism
This is an instruction-only skill with a small helper script; there is no install spec, no downloaded artifacts, and no obfuscated code. The included Python script uses standard library modules and performs a single network request.
Credentials
The script and API docs require a single API key via the environment variable LINKFOXAGENT_API_KEY — that is plausible and proportionate for calling a third‑party web API. However, the registry metadata does not declare this required env var (or any primary credential), which is an incoherence that could hide unexpected credential usage. The skill also documents an additional feedback endpoint (skill-api.linkfox.com) which is separate but not unusual; confirm whether feedback calls will be made automatically.
Persistence & Privilege
The skill does not request persistent 'always' inclusion and there is no indication it modifies other skills or global agent configuration. It only performs outbound HTTP requests when invoked.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install linkfox-sellersprite-product-search
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /linkfox-sellersprite-product-search 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.0
Initial release
元数据
Slug linkfox-sellersprite-product-search
版本 1.0.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
常见问题

Sellersprite Product Search 是什么?

使用卖家精灵数据搜索和筛选亚马逊商品,支持价格、月销量、BSR排名、毛利率、评分、配送方式、标签、卖家来源等多维度条件,覆盖多个亚马逊站点。当用户提到亚马逊选品调研、产品筛选、销量过滤、产品发掘、BSR分析、小众商品发现、竞品分析、市场机会评估、按商品维度的市场规模估算、毛利率筛选、SellerSprite pr... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 97 次。

如何安装 Sellersprite Product Search?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install linkfox-sellersprite-product-search」即可一键安装,无需额外配置。

Sellersprite Product Search 是免费的吗?

是的,Sellersprite Product Search 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Sellersprite Product Search 支持哪些平台?

Sellersprite Product Search 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Sellersprite Product Search?

由 linkfox-ai(@linkfox-ai)开发并维护,当前版本 v1.0.0。

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