skill-listing-image-optimizer — Автоматический оптимизатор изображений для Amazon

--- name: skill-listing-image-optimizer description: "Audit Amazon product listing images for non-square dimensions, auto-pad them to 2000×2000 white background, and push corrected images to live listings via SP-API. Works with any marketplace and seller account." metadata: openclaw: requires: { bins: ["node", "python3"] } --- # Amazon Listing Image Optimizer Automatically fix non-square product images on Amazon listings — download, pad to 2000×2000 white background, and push back to live listings via SP-API. No manual Seller Central work required. --- ## Why This Exists Amazon penalizes listings with non-square images (aspect ratio != 1:1). Common offenders: - Landscape 16:9 or 4:3 product shots - Portrait hero images - Tiny low-resolution images This skill detects, fixes, and re-uploads — all automatically. --- ## Setup ### 1. Install dependencies ```bash pip3 install Pillow npm install amazon-sp-api ``` ### 2. Create SP-API credentials file ```json { "lwaClientId": "amzn1.application-oa2-client.YOUR_CLIENT_ID", "lwaClientSecret": "YOUR_CLIENT_SECRET", "refreshToken": "Atzr|YOUR_REFRESH_TOKEN", "region": "eu", "marketplace": "YOUR_MARKETPLACE_ID", "sellerId": "YOUR_SELLER_ID" } ``` Set `AMAZON_SPAPI_PATH` env var to point to it (default: `./amazon-sp-api.json`). --- ## Scripts ### `audit.js` — Detect non-square images ```bash node scripts/audit.js --sku "MY-SKU" # audit single SKU node scripts/audit.js --all # audit all FBA SKUs node scripts/audit.js --all --out report.json # save report ``` Outputs: list of non-conforming image slots with dimensions. ### `pad_to_square.py` — Fix images locally ```bash # After audit.js downloads originals to ./image_fix/ python3 scripts/pad_to_square.py ./image_fix/ ``` Pads all `*_orig.jpg` files to 2000×2000 white background, outputs `*_fixed.jpg`. ### `push_images.js` — Upload fixed images to Amazon ```bash node scripts/push_images.js --dir ./image_fix/ --sku "MY-SKU" --slots PT03,PT05 ``` Spins up a local HTTP server on a public port, submits image URLs to SP-API, then auto-kills the server after 15 minutes (time for Amazon to crawl). ### `fix_title.js` — Patch listing title ```bash node scripts/fix_title.js --sku "MY-SKU" --title "New optimized title here" ``` --- ## Full Pipeline (one command) ```bash node scripts/audit.js --all --out report.json python3 scripts/pad_to_square.py ./image_fix/ node scripts/push_images.js --dir ./image_fix/ --from-report report.json ``` --- ## Image Slot Reference | Slot | Attribute | Description | |------|-----------|-------------| | MAIN | `main_product_image_locator` | Hero image (must be white bg) | | PT01–PT08 | `other_product_image_locator_1` … `_8` | Secondary images | --- ## Notes - Amazon processes image updates within 15–30 mins of ACCEPTED response - VPS must have a publicly accessible IP/port for the temp HTTP server (or use S3/Cloudflare) - PIL uses LANCZOS resampling for best quality when resizing - Keep images under 10MB; target 2000×2000px @ 95% JPEG quality ## Related - [skill-amazon-spapi](https://github.com/Zero2Ai-hub/skill-amazon-spapi) — Core SP-API auth & orders