linkfox-sellersprite-competitor

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

Parameter	Description	Example
marketplace	Amazon marketplace code	US, UK, DE, JP
keyword	Search keyword (translate to the marketplace language)	wireless earbuds
asinList	One or more ASINs, comma-separated (max 40)	B072MQ5BRX,B08N5WRWNW
sellerName	Seller name to filter by	Anker Direct
brand	Brand name to filter by	Anker
nodeLabel	Amazon category name (colon-separated levels)	Electronics:Headphones
nodeIdPath	Amazon category ID path	172282
matchType	Keyword match mode: 1 = phrase, 2 = fuzzy, 3 = exact (default 1)	1
showVariation	Show product variations: Y or N (default N)	N
dataSnapshotMonth	Data snapshot month (nearly for real-time, or yyyyMM)	nearly

Pagination & Sorting

Parameter	Description	Example
page	Page number, starting from 1	1
size	Results per page, 10-100 (default 50)	50
order.field	Sort field (see sort options below)	total_units
order.desc	Sort direction: true = descending, false = ascending	true

Sort Field Options

Field	Description
total_units	Monthly sales units
total_amount	Monthly sales revenue
bsr_rank	BSR ranking
price	Price
rating	Rating score
reviews	Number of reviews
profit	Gross margin
reviews_rate	Review rate
available_date	Listing date
questions	Q&A count
total_units_growth	Monthly sales unit growth rate
total_amount_growth	Monthly revenue growth rate
reviews_increasement	Monthly new reviews
bsr_rank_cv	7-day BSR growth count
bsr_rank_cr	7-day BSR growth rate
amz_unit	Variant sales units

Key Response Fields

Field	Description
asin	Product ASIN
title	Product title
price	Current price
monthlySalesUnits	Monthly sales volume
monthlySalesRevenue	Monthly sales revenue
bsr	BSR ranking
bsrGrowthRate	BSR growth rate
bsrGrowthCount	BSR growth count
rating	Rating score
ratings	Number of ratings
ratingsGrowth	Monthly new ratings
ratingsRate	Review rate
brand	Brand name
sellerName	BuyBox seller
sellerNation	BuyBox seller nationality
fulfillment	Fulfillment type (AMZ/FBA/FBM)
availableDateString	Listing date
profit	Gross margin
nodeLabelPath	Category path
imageUrl	Product image URL
monthlySalesUnitsGrowthRate	Monthly sales growth rate
listingQualityScore	Listing quality score
variationNum	Number of variations
parent	Parent ASIN
badgeBestSeller	Best Seller badge (Y/N)
badgeAmazonChoice	Amazon's Choice badge (Y/N)
badgeEbc	A+ Content (Y/N)
badgeVideo	Video present (Y/N)

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_competitor_lookup.py directly to run queries.

Usage Examples

1. Look up competitors by ASIN

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

Use case: Analyze specific competing products by their ASINs.

2. Search competitors by keyword

{
  "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

{
  "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

{
  "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

{
  "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

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

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

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 Says	Scenario
"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

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.

Handling Large Responses

To avoid overflowing the agent context, persist the response to disk and extract only the fields you need:

python scripts/response_io.py run --script scripts/sellersprite_competitor_lookup.py --out-dir <DIR> '<params>'
python scripts/response_io.py read <file> --fields "<paths>"   # or --path "<JMESPath>"

Pick --out-dir outside any git working tree (e.g. /tmp/... on Unix, %TEMP%/... on Windows). Persisted responses may contain PII, pricing, or auth-sensitive data — do not commit them. Files are not auto-deleted; clean up when the task is done.

run writes the full response to a file and emits only a schema preview + file path. read projects specific fields, with --limit/--offset for slicing and --format json|jsonl|csv|table for output.

When to prefer this pattern — apply your judgment based on the response characteristics, e.g.:

• High field count per record, or fields you don't need
• Batch/paginated results (multiple items per call)
• Long-text fields (descriptions, reviews, HTML, time series)
• Output reused across later steps rather than consumed immediately

For small, single-use responses, calling the main script directly is fine.

⚠️ The preview is a truncated schema + sample, not the full data. Any field-level decision must read from the persisted file via read.

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