How do I install the Skill Listing Image Optimizer skill?

Run npx skillmds@latest add dvcrn/skill-listing-image-optimizer in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Skill Listing Image Optimizer safe to use?

This skill has not completed SkillMD's automated safety review yet. Independent scanners report: SkillSpector: PASS, Skill Scanner: PASS. Capability flags: executes scripts, makes network calls. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Skill Listing Image Optimizer?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Skill Listing Image Optimizer free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Skill Listing Image Optimizer?

dvcrn (@dvcrn) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Skill Listing Image Optimizer by dvcrn

Name: Skill Listing Image Optimizer
Rating: 4.2 (5 reviews)
Author: dvcrn

Skill Listing Image Optimizer

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.

dvcrn Updated Sep 8, 2026 32 repo stars

File contents

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

pip3 install Pillow
npm install amazon-sp-api

2. Create SP-API credentials file

{
  "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

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

# 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

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

node scripts/fix_title.js --sku "MY-SKU" --title "New optimized title here"

Full Pipeline (one command)

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

skill-amazon-spapi — Core SP-API auth & orders

---name: skill-listing-image-optimizerdescription: 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.---# Amazon Listing Image OptimizerAutomatically 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 ExistsAmazon 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 imagesThis skill detects, fixes, and re-uploads — all automatically.---## Setup### 1. Install dependencies```bashpip3 install Pillownpm 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```bashnode scripts/audit.js --sku "MY-SKU" # audit single SKUnode scripts/audit.js --all # audit all FBA SKUsnode 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```bashnode 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```bashnode scripts/fix_title.js --sku "MY-SKU" --title "New optimized title here"```---## Full Pipeline (one command)```bashnode scripts/audit.js --all --out report.jsonpython3 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

Frequently asked questions