Use Nexscope data to search and filter Amazon products, supporting multi-dimensional criteria including price, monthly sales, BSR ranking, gross margin, ratings, fulfillment method, badges, seller origin, and more across multiple Amazon marketplaces. Trigger when the user mentions Amazon product selection research, product filtering, sales filtering, product discovery, BSR analysis, niche product discovery, competitor analysis, market opportunity assessment, product-level market size estimation, gross margin screening, Nexscope product selection, Amazon product selection, sales filtering, BSR analysis, profit screening, market analysis, product selection tool. Even if the user does not explicitly mention "Nexscope", if their need involves filtering and analyzing Amazon product-level data for product selection, this skill should also be triggered.
npx skills add https://github.com/nexscope-ai/nexscope-ecommerce-skills --skill ecommerce.amazon-broad-product-search
This skill guides you on how to search, filter, and analyze Amazon product data via the Nexscope product database, helping Amazon sellers make data-driven product selection decisions.
Nexscope 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. Supported marketplace codes are only: US, UK, DE, FR, JP, CA, IT, ES, MX, and IN (same as the gateway schema).
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:
| 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 (allowed set only): 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 |
| 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 |
| Parameter | Type | Description |
|-----------|------|-------------|
| minUnits / maxUnits | integer | Monthly sales volume range |
| minAmzUnit / maxAmzUnit | integer | Child-ASIN last-30-day sales range (only when querying last-30-day style data, e.g. dataSnapshotMonth: "nearly") |
| 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) |
| 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 |
| 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 |
| 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) |
| 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 |
| 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 |
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; use "" when you intentionally omit a business sort key (per gateway schema) |
| desc | string | "true" for descending, "false" for ascending |
Default sort: total_units descending.
If the hosting environment supplies them, you may pass chatId, uid, requestId, and teamId as strings (see references/api.md). They are not required for ad-hoc script calls.
POST /sellersprite/productSearch (complete params/response/error codes in references/api.md)python scripts/amazon_broad_product_search.py '<JSON params>' [--inline]Output strategy (script default behavior):
<cwd>/nexscope/<YYYY-MM-DD>/<session>/data/nexscope-sellersprite-product-search-<timestamp>.json (<cwd> is the working directory at script execution time, i.e. the current project directory in Claude Code; <session> is taken from the SESSION_ID env var, auto-grouped by user task; do not write to /tmp, error if current directory is not writable)total/costToken, length of largest list field + first 3 samples)--inline to force full output to stdout (still saves to disk)Data reading tip: Check the summary first to decide if it's enough; when specific fields are needed, prefer using jq or ConvertFrom-Json to extract from the saved json file on demand, avoiding loading the entire JSON into context.
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"}
}
message field and suggest adjusting query criteriaweightUnit must also be providedfilterSubNode is set to truelistedWithinLastMonths parameter only accepts specific values: 1, 3, 6, 12, or 24minAmzUnit / maxAmzUnit apply only to last-30-day style queries (typically dataSnapshotMonth: "nearly"); do not rely on them for historical yyyyMM snapshotsApplicable -- 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:
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.
Set the NEXSCOPE_API_KEY environment variable. If credentials are missing or expire, visit https://www.nexscope.ai/help/skills-external-access?co-from=skillNS to top up credits.
Take nexscope-ai/ecommerce.amazon-broad-product-search from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.