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Linkfox Amazon Search By Image

  • 245 installs
  • 64 repo stars
  • Updated August 3, 2026
  • linkfox-ai/linkfox-skills

Send product photos to Linkfox Amazon image-search endpoints to discover matching ASINs, compare offers, and enrich reseller, arbitrage, or catalog intelligence agents.

About

Linkfox skill enabling Claude to reverse-search Amazon listings from product images, parse matching ASINs and pricing signals, and power reseller sourcing, catalog enrichment, and competitive intelligence agent workflows.

  • image-to-ASIN search
  • Amazon catalog match
  • Linkfox API
  • offer comparison
  • sourcing automation

Linkfox Amazon Search By Image by the numbers

  • 245 all-time installs (skills.sh)
  • +38 installs in the week ending Aug 2, 2026 (Skillselion tracking)
  • Ranked #2,599 of 16,546 AI & Agent Building skills by installs in the Skillselion catalog
  • Data as of Aug 4, 2026 (Skillselion catalog sync)
npx skills add https://github.com/linkfox-ai/linkfox-skills --skill linkfox-amazon-search-by-image

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Listed on Skillselion
Installs245
repo stars64
Last updatedAugust 3, 2026
Repositorylinkfox-ai/linkfox-skills

What it does

Send product photos to Linkfox Amazon image-search endpoints to discover matching ASINs, compare offers, and enrich reseller, arbitrage, or catalog intelligence agents.

Files

SKILL.mdMarkdownGitHub ↗

Amazon Image-Based Search

This skill guides you on how to perform visual product searches on Amazon using an image URL, helping Amazon sellers and researchers find visually similar products across multiple marketplaces.

Core Concepts

Amazon Image-Based Search (visual search) allows you to submit a product image URL and retrieve Amazon listings that are visually similar. This is invaluable for competitive analysis, sourcing alternatives, identifying counterfeits, and discovering market opportunities based on product appearance.

The tool searches across 8 Amazon marketplaces and returns rich product data including ASIN, title, image, price, rating, review count, brand, and optionally Keepa-enriched data (sales rank, monthly sales, FBA fees, dimensions, etc.).

Supported Marketplaces

MarketplaceDomainDefault Zip Code
United Statesamazon.com10001
United Kingdomamazon.co.ukEC1A 1BB
Germanyamazon.de10115
Franceamazon.fr75001
Italyamazon.it00100
Spainamazon.es28001
Japanamazon.co.jp100-0001
Indiaamazon.in110034

Default marketplace is amazon.com (US). Use amazon.com when the user does not specify a marketplace.

Parameter Guide

ParameterRequiredDescription
imageUrlYesA valid, publicly accessible image URL to search with
amazonDomainYesAmazon marketplace domain (e.g., amazon.com, amazon.de). Defaults to amazon.com
sortNoSort order for results. Supported values: default, price-asc-rank, price-desc-rank, rating-asc-rank, rating-desc-rank, ratings-asc-rank, ratings-desc-rank
deliveryZipNoDelivery address zip code within the marketplace country. Uses the marketplace default if not specified
countryOrAreaCodeNoCountry/region code for cross-border delivery (e.g., CN, JP, KR). Cannot be used together with deliveryZip. Note: India marketplace does not support cross-border delivery
aggregateByKeepaDataNoWhether to enrich results with Keepa data (sales rank, monthly sales, FBA fees, dimensions, etc.)

Sort Options

ValueDescription
defaultDefault relevance sorting
price-asc-rankPrice: low to high
price-desc-rankPrice: high to low
rating-asc-rankRating: low to high
rating-desc-rankRating: high to low
ratings-asc-rankReview count: low to high
ratings-desc-rankReview count: high to low

Important: If the requested sort order is not in the supported list above, do NOT attempt to use any other tool or workaround to compensate. Inform the user of the supported sort options.

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/amazon_search_by_image.py directly to run queries.

Local Image Upload

This tool requires a publicly accessible image URL. If the user provides a local image file path (e.g., C:\Users\...\photo.png, /home/.../image.jpg), you must upload it first to obtain a public URL.

Run the upload script:

python scripts/upload_image.py /path/to/local/image.png

The script will return a public URL (valid for 24 hours) that can be used as the image URL parameter.

Usage Examples

1. Basic image search on the US marketplace

Search Amazon US for products that look similar to this image:
https://m.media-amazon.com/images/I/61pAlIX8SZL._AC_SY575_.jpg

2. Find similar products on a specific marketplace

Search Amazon Germany (amazon.de) for products visually similar to this image:
https://example.com/product-photo.jpg

3. Image search sorted by price (low to high)

Find similar products on Amazon US for this image, sorted by price from low to high:
https://example.com/my-product.jpg

4. Image search with Keepa data enrichment

Search Amazon US for products matching this image and include Keepa sales data:
https://example.com/competitor-product.jpg

5. Cross-border delivery search

Search Amazon Japan for similar products to this image, with delivery to China:
https://example.com/item.jpg

6. Competitor lookalike discovery

I found this product image on a competitor's listing. Find me all similar-looking products on Amazon UK:
https://example.com/competitor.jpg

Display Rules

1. Present data clearly: Show search results in a well-structured table. Key columns to prioritize: product image, title, ASIN, price, rating, review count, and brand 2. Image display: When the response includes imageUrl for products, display them inline so users can visually compare results 3. Price and currency: Always show price alongside the currency code (e.g., $29.99 USD, 24.99 EUR) 4. Keepa data: When aggregateByKeepaData is enabled and Keepa fields are present, show supplementary data (monthly sales, sales rank, FBA fees) in an expanded section or additional columns 5. Result count: Always inform the user of the total number of results found (total / totalCount) 6. Error handling: When a query fails, explain the issue and suggest checking that the image URL is valid and publicly accessible 7. Sort limitation: If the user requests a sort order not in the supported list, clearly explain which sort options are available rather than attempting unsupported workarounds 8. No secondary processing: Results from this tool are not stored in a database, so secondary SQL processing is not available

User Expression & Scenario Quick Reference

Applicable -- Visual product search scenarios on Amazon:

User SaysScenario
"Find similar products to this image"Basic image search
"Search by image", "reverse image search on Amazon"Visual search
"Find competitor lookalikes", "find same-style products"Competitor analysis by appearance
"What products on Amazon look like this"Product discovery
"Find cheaper alternatives that look the same"Price-based visual comparison
"Search Amazon JP/DE/UK for this product image"Cross-marketplace visual search
"Show me Keepa data for similar products"Enriched visual search
"Find products similar to this photo, sorted by rating"Sorted visual search

Not applicable -- Needs beyond image-based product search:

  • Text-based keyword search on Amazon (use keyword search tools instead)
  • ABA search term data analysis
  • Product review analysis or listing optimization
  • Sales estimation without a source image
  • Image editing or image generation
  • Searching with a local image file (the tool requires a publicly accessible URL)

Boundary judgment: When users say "find similar products" or "competitor analysis", if they provide an image URL and the intent is to find visually similar Amazon listings, this skill applies. If they are asking for keyword-based search, sales data analysis, or product research without an image, it does not apply.

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.

<!-- LF_LARGE_RESPONSE_BLOCK -->

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/amazon_search_by_image.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.
This skill exposes multiple entry scripts: amazon_search_by_image.py, upload_image.py. Pass --script scripts/<name>.py to choose the one you need.

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. <!-- /LF_LARGE_RESPONSE_BLOCK -->

--- For more high-quality, professional cross-border e-commerce skills, set [LinkFox Skills](https://skill.linkfox.com/).

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