Ecommerce Amazon Product Database

Jungle Scout -- Product Database Query

This skill queries the Jungle Scout Product Database via the NexScope tool gateway, enabling multi-condition filtering of Amazon products across 10 marketplaces. Sellers can discover products by category, price range, sales volume, revenue, reviews, rating, BSR rank, Listing Quality Score (LQS), seller type, and more.

Core Concepts

The Jungle Scout Product Database is a multi-dimensional filtering tool at the Amazon product level, helping sellers quickly identify target products from a vast catalog:

• Category-Based Discovery: Filter products by Amazon main categories
• Sales/Revenue Filtering: Narrow down products by monthly sales volume and revenue ranges
• Competition Assessment: Evaluate competition intensity through review counts, ratings, and seller counts
• Listing Quality Assessment: LQS (Listing Quality Score, 1-10) helps spot products with optimization potential
• Product Type Filtering: Distinguish FBA/FBM/AMZ seller types, standard/oversize product tiers
• New Product Discovery: Filter by listing date to find recently launched products

Internal paging: The API handles pagination automatically; you specify needCount to control how many results you want, and the backend fetches them across pages internally.

Data Fields

Key Output Fields

Supported Marketplaces

us (United States), uk (United Kingdom), de (Germany), in (India), ca (Canada), fr (France), it (Italy), es (Spain), mx (Mexico), jp (Japan)

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

API Invocation

• API Endpoint: POST /tool-jungle-scout/product-database/query (full parameters/responses/error codes see references/api.md)
• Python Script: python scripts/amazon_product_database.py '<JSON params>' [--inline]
• Cost Constraint: This tool consumes credits; the same parameter combination is called only once per session by default, with a 24h local cache in the script. Do not automatically retry with different keywords, pagination, or zip codes after failures/empty results; inform the user about additional cost before continuing.

Output Strategy (default script behavior):

• Always write the full response to <cwd>/nexscope/<YYYY-MM-DD>/<session>/data/nexscope-junglescout-product-database-<timestamp>.json (<cwd> is the working directory at script execution time, which in Claude Code is the current project directory; <session> is taken from the SESSION_ID environment variable, auto-grouped by user task; do NOT write to /tmp -- error out if the current directory is not writable)
• Response body <= 8 KB: after writing to disk, print the full JSON to stdout
• Response body > 8 KB: after writing to disk, stdout outputs only a summary (top-level fields, common counts like total/costToken, length of the largest list field + first 3 samples)
• Add --inline to force full output to stdout (while still writing to disk)

Data Reading Tips: First check the summary to see if it is sufficient; 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.

Authentication

Set the NEXSCOPE_API_KEY environment variable. If authentication fails (401/402) or you see insufficient balance errors, visit https://www.nexscope.ai/help/skills-external-access?co-from=skillNS to get an API Key or top up credits.

How to Build Queries

Only marketplace is required. All other parameters are optional filters -- combine them to narrow results.

Principles for Building API Calls

1. Marketplace mapping: "US site" -> us, "Japan site" -> jp, "Germany site" -> de; default to us when not specified
2. Keywords: includeKeywords supports comma-separated multiple terms (searches title or ASIN), e.g. yoga mat,fitness; excludeKeywords excludes products containing specific terms
3. Category matching: categories must use the corresponding marketplace is standard English category names, e.g. US site Sports & Outdoors, Home & Kitchen, etc.; multiple categories comma-separated
4. Numeric ranges: min/max used in pairs, either end can be omitted; e.g. only minSales=300 means monthly sales >= 300
5. Sorting: prefix sort field name with - for descending, e.g. -sales for sales high-to-low; defaults to name ascending
6. Result count: needCount controls total results returned; defaults to a standard amount if not set

Common Query Scenarios

1. Keyword search + sales volume filter

{
  "marketplace": "us",
  "includeKeywords": "yoga mat",
  "minSales": 300,
  "maxSales": 5000,
  "sort": "-sales",
  "needCount": 50
}

2. Category + price range filter

{
  "marketplace": "us",
  "categories": "Home & Kitchen",
  "minPrice": 15,
  "maxPrice": 50,
  "minSales": 100,
  "sort": "-revenue",
  "needCount": 50
}

3. High rating, low competition (few reviews, high rating)

{
  "marketplace": "us",
  "categories": "Beauty & Personal Care",
  "minRating": 4.0,
  "maxReviews": 200,
  "minSales": 100,
  "sort": "-sales",
  "needCount": 50
}

4. FBA-only product filter

{
  "marketplace": "us",
  "includeKeywords": "phone stand",
  "sellerTypes": "fba",
  "productTiers": "standard",
  "minSales": 200,
  "sort": "-sales",
  "needCount": 50
}

5. Exclude top brands + discover blue ocean opportunities

{
  "marketplace": "us",
  "categories": "Sports & Outdoors",
  "excludeTopBrands": true,
  "minSales": 300,
  "maxReviews": 500,
  "minRating": 4.0,
  "sort": "-sales",
  "needCount": 50
}

6. Discover new products by listing date

{
  "marketplace": "us",
  "categories": "Electronics",
  "minUpdatedAt": "2026-01-01",
  "minSales": 50,
  "sort": "-sales",
  "needCount": 50
}

Display Rules

1. Table format: Present results in a structured table with key columns: title, brand, price, monthly sales, monthly revenue, BSR rank, reviews, rating, LQS
2. Sorting note: Remind the user what sorting was applied and how many results were returned
3. Highlight insights: Mark products with notably low reviews but high sales (potential opportunity), or high LQS scores
4. Fee breakdown: When users ask about profitability, include feeBreakdown details (FBA fee, referral fee, total fees)
5. Image links: Include imageUrl when displaying individual product details
6. Error handling: When a query fails, explain the reason based on the error response and suggest adjusting parameters

Important Limitations

• marketplace is required: Every query must specify a marketplace
• Category names must match: categories values must exactly match the standard main category names for that marketplace
• Keyword limits: includeKeywords / excludeKeywords max 100 items each, max 50 characters per item
• Data freshness: Data is sourced from Jungle Scout periodic updates, not real-time data
• Rating range: minRating / maxRating values are 1.0-5.0
• Weight unit: minWeight / maxWeight are in pounds

User Expression & Scenario Quick Reference

Applicable - Amazon product multi-condition filtering and discovery:

Not applicable - Beyond product database filtering:

• Keyword search volume/trend analysis (use keyword history tools)
• ABA search term ranking (use ABA tools)
• Product detail page/listing content analysis
• Advertising/PPC strategy
• Non-Amazon platform product data

Boundary judgment: When users say "product selection", "find products", or "market research", if their need is to filter products by specific criteria (price, sales, category, reviews, etc.) from Amazon is product catalog, this skill applies. If they need keyword-level search volume data, advertising insights, or non-Amazon platform data, it does not apply.