An automated tool to audit, pad, and re-upload Amazon product images to ensure they meet the 1:1 aspect ratio requirement.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install skill-listing-image-optimizer
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install skill-listing-image-optimizer using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Amazon Listing Image Optimizer?
The Amazon Listing Image Optimizer is a specialized utility designed to prevent search suppression by ensuring all product photography adheres to Amazon's strict 1:1 aspect ratio requirements. By utilizing Openclaw Skills, this tool automates the tedious process of identifying non-conforming images, applying professional white-background padding, and pushing updates directly to live listings via the Selling Partner API (SP-API).
This skill is essential for sellers managing large catalogs where manual image editing is impractical. It bridges the gap between raw product photography and marketplace compliance, leveraging high-quality resampling and automated workflows to maintain listing health and visibility. Integrating Openclaw Skills into your e-commerce stack allows for programmatic maintenance of visual assets without ever opening Seller Central.
Amazon Listing Image Optimizer Use Cases
- Automatically identifying and fixing landscape or portrait images that cause Amazon search suppression.
- Bulk auditing FBA inventory to ensure all secondary images (PT01-PT08) meet resolution standards.
- Standardizing product images to 2000x2000px for optimal zoom functionality on mobile and desktop.
- Streamlining the listing update process for multi-marketplace seller accounts through Openclaw Skills automation.
How Amazon Listing Image Optimizer Works
- The audit script queries the Amazon SP-API to retrieve current image metadata for specified SKUs or the entire catalog.
- Non-square images are flagged and downloaded to a local temporary directory.
- A Python-based image processing script uses the Pillow library and LANCZOS resampling to pad the images to a 2000x2000 white square.
- A temporary local HTTP server is launched to provide a public-facing URL for Amazon's crawlers to access the fixed files.
- The skill submits the new image locations to the SP-API and monitors for an accepted response before shutting down the local server.
Amazon Listing Image Optimizer Setup
1. Install Dependencies
pip3 install Pillow
npm install amazon-sp-api
2. Configure Credentials
Create a file named amazon-sp-api.json in your root directory:
{
"lwaClientId": "amzn1.application-oa2-client.YOUR_CLIENT_ID",
"lwaClientSecret": "YOUR_CLIENT_SECRET",
"refreshToken": "Atzr|YOUR_REFRESH_TOKEN",
"region": "us",
"marketplace": "ATVPDKIKX0DER",
"sellerId": "YOUR_SELLER_ID"
}
3. Environment Setup
Ensure your AMAZON_SPAPI_PATH environment variable points to your credentials file to allow Openclaw Skills to authenticate successfully.
Amazon Listing Image Optimizer Data Schema & Taxonomy
The skill organizes image data and reports using the following structure:
| Data Type | Format | Description |
|---|---|---|
| Audit Report | JSON | List of non-conforming SKUs and image slot IDs |
| Source Images | .jpg | Original files downloaded from Amazon tagged as _orig.jpg |
| Optimized Images | .jpg | Processed 2000x2000 white-padded files tagged as _fixed.jpg |
| API Metadata | JSON | Mapping of image slots (MAIN, PT01-PT08) to SP-API attributes |
All local file processing occurs within the ./image_fix/ directory by default.
Amazon Listing Image Optimizer Advanced Features
- Multi-slot processing: Simultaneously updates MAIN and all secondary image slots (PT01 through PT08).
- High-fidelity resizing: Uses LANCZOS resampling to maintain image sharpness at 95% JPEG quality.
- Automated infrastructure: Spins up and auto-terminates a local HTTP server to host images for Amazon's ingestion engine.
- Full pipeline integration: Execute audit, fix, and upload sequences through a single chain of Openclaw Skills commands.
- Bulk mode: Support for
--allflag to process thousands of FBA SKUs in a single session.
SKILL.md
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