---
name: linkfox-amazon-search-by-image
description: 基于图片的亚马逊跨站点视觉商品搜索，支持8个站点的以图搜图和视觉相似商品发现。当用户提到以图搜图、图片搜索、视觉搜索、找同款、外观相似商品、图片找货、竞品图片搜索、相似商品发现、image search, Amazon visual search, find similar products, reverse image lookup, visual search, similar items, competitor image search, product image match时触发此技能。即使用户未明确提及"图片搜索"，只要用户提供了图片URL并希望在亚马逊上查找匹配或相似的商品，也应触发此技能。
---

# 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

| Marketplace | Domain | Default Zip Code |
|-------------|--------|-------------------|
| United States | amazon.com | 10001 |
| United Kingdom | amazon.co.uk | EC1A 1BB |
| Germany | amazon.de | 10115 |
| France | amazon.fr | 75001 |
| Italy | amazon.it | 00100 |
| Spain | amazon.es | 28001 |
| Japan | amazon.co.jp | 100-0001 |
| India | amazon.in | 110034 |

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

## Parameter Guide

| Parameter | Required | Description |
|-----------|----------|-------------|
| imageUrl | Yes | A valid, publicly accessible image URL to search with |
| amazonDomain | Yes | Amazon marketplace domain (e.g., `amazon.com`, `amazon.de`). Defaults to `amazon.com` |
| sort | No | Sort order for results. Supported values: `default`, `price-asc-rank`, `price-desc-rank`, `rating-asc-rank`, `rating-desc-rank`, `ratings-asc-rank`, `ratings-desc-rank` |
| deliveryZip | No | Delivery address zip code within the marketplace country. Uses the marketplace default if not specified |
| countryOrAreaCode | No | Country/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 |
| aggregateByKeepaData | No | Whether to enrich results with Keepa data (sales rank, monthly sales, FBA fees, dimensions, etc.) |

### Sort Options

| Value | Description |
|-------|-------------|
| `default` | Default relevance sorting |
| `price-asc-rank` | Price: low to high |
| `price-desc-rank` | Price: high to low |
| `rating-asc-rank` | Rating: low to high |
| `rating-desc-rank` | Rating: high to low |
| `ratings-asc-rank` | Review count: low to high |
| `ratings-desc-rank` | Review 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:
```bash
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 Says | Scenario |
|-----------|----------|
| "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 -->

---
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