Sellersprite Product Search

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...

Security Scan

The skill's code and docs expect an API key and call external LinkFox endpoints (consistent with its stated purpose), but the registry metadata does not declare the required environment credential and the origin is unknown — this mismatch is suspicious and worth addressing before installation.

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.

What to consider before installing

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.

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.

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