amazon-image-studio

amazon-image-studio is a skill for Claude Code from zpoint/vibe-seller. It costs 139 tokens per session (1,626 once invoked), scanned A, original, Apache-2.0.

A guide for creating Amazon product-listing images with an image-generation tool. It explains Amazon’s rules for the main product image and how to gather suitable reference images.

In plain words
What is it for?
Use it when generating Amazon main images, secondary lifestyle images, feature graphics, size charts, or comparison images for a product listing.
Why use it?
It helps avoid images being rejected because of backgrounds, missing products, unwanted text, incorrect sizing, or unusable placeholder references.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: names the AskUserQuestion tool.

Good fit Use it when generating Amazon main images, secondary lifestyle images, feature graphics, size charts, or comparison images for a product listing.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/zpoint/vibe-seller/amazon-image-studio
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add zpoint/vibe-seller --skill amazon-image-studio
Clone the repo
git clone --depth 1 https://github.com/zpoint/vibe-seller

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for amazon-image-studio

README.md
[![agentmods](https://agentmods.dev/badge/skills/zpoint/vibe-seller/amazon-image-studio/github.svg)](https://agentmods.dev/skills/zpoint/vibe-seller/amazon-image-studio)
Your own site
<a href="https://agentmods.dev/skills/zpoint/vibe-seller/amazon-image-studio"><img src="https://agentmods.dev/badge/skills/zpoint/vibe-seller/amazon-image-studio/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for amazon-image-studio

Your own site · 80×15
<a href="https://agentmods.dev/skills/zpoint/vibe-seller/amazon-image-studio"><img src="https://agentmods.dev/badge/skills/zpoint/vibe-seller/amazon-image-studio.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 139 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,626 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00139 $0.01626
Opus 5 $0.00069 $0.00813
Sonnet 5 $0.00028 $0.00325
Haiku 4.5 $0.00014 $0.00163

Measured 10d ago against content hash 14cf8e73d710, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

amazon-image-studio scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

app/skills_v2/amazon-image-studio/SKILL.md · 113 lines

How it starts

The opening of the file, as written. The whole thing — 113 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Amazon Image Studio

Amazon-specific knowledge for generating listing images with the general vibe_seller_generate_image tool. The tool itself documents the generic contract (user-language prompt, references carry a real subject's appearance, roles by position, the user-confirm pause) — this skill adds only what is Amazon:

1. Amazon image requirements

MAIN image (the one search results show — strictest):

  • Pure white background, exactly RGB (255,255,255) — off-white fails Amazon's automated scan.
  • Product fills ~85% of the frame, fully visible, not cropped.
  • NO text, logos, badges, watermarks, borders, props, or accessories not included in the purchase. Product only, as the buyer receives it.
  • ≥1000px on the longest side; ≥1600px recommended (enables zoom). Square (1:1) displays best. JPEG/PNG.
  • Category variations exist (e.g. adult apparel is usually shown on a model; shoes as a single shoe at an angle). When in doubt, mirror what the store's own live listings of the same category do.

Secondary images (gallery slots 2-7+): lifestyle shots, infographics with feature callouts, dimension/scale charts and comparison tables are all allowed and convert well. On-image text is fine HERE (never on the main image) — spell every word exactly in the prompt and proofread the result character by character.

2. Collecting reference images

  • Supplier page (e.g. 1688): extract the original gallery image URLs from the page (full-size, not thumbnails) and pass them as reference_images directly — the generator fetches URLs itself.
  • Amazon listing (style reference): open the listing's dp page and take the hi-res image URLs (m.media-amazon.com/images/I/…, request the large _SL1600_ variant). These carry the store's composition, palette and infographic layout.
  • Never pass a blank/placeholder image. Two traps produce them:
    • listings whose images were never uploaded show a "No image available" placeholder;
    • lazy-loading pages serve tiny stand-in GIFs (e.g. 60×40px) until the image scrolls into view. Judge what you actually fetched — is it a full-resolution product photo? A placeholder passed "just in case" poisons the generation.
  • Style-reference search order (autonomous, never stall):
    1. a live-imaged listing of the same product type on this store;
    2. otherwise ANY live-imaged listing on this store (brand style — hero look, palette, chip band — carries across categories; you reference its composition, never its product);
    3. if the whole store has no live images, ask the user once (AskUserQuestion): provide a style image (they can drag one into the confirmation popup's reference area) or proceed with supplier photos only — optional; proceed immediately if declined.

Read the full file on GitHub · 113 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 10d ago First seen · 113 lines · 139 tokens per session scan A 14cf8e73d710

Subscribe to this mod's changes

amazon-image-studio is a skill published in the GitHub repository zpoint/vibe-seller (64 stars, last pushed yesterday), licensed Apache-2.0. It adds 139 tokens to every session and 1,626 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

Other skills, from other repositories

beat-sync-reel

Generates Instagram Reels where product image cuts are synced to audio beats. Accepts audio as a local file, URL, or search query. Uses librosa for beat detection, FFmpeg Ken Burns for scene animation, and Pillow for text overlays. No AI video generation — fully free, fast, and scalable.

gooseworks-ai/goose-skills · 68 tokens

byted-livesaas-master

A control tool for managing business livestreams, including rooms, comments, viewers, product cards, coupons, and live-session settings.

bytedance/agentkit-samples · 160 tokens

byted-ind-ecom-product-video-prompt

A structured prompt-writing guide for creating e-commerce product videos with Seedance 2.0. It turns one or more product images into a product showcase script using scene settings, timed shots, and output constraints.

bytedance/agentkit-samples · 79 tokens

tiktok-shop-branding

Brand building and positioning on TikTok Shop. Brand identity development, content pillars, community engagement, brand storytelling, and authenticity strategies. Use when the user asks about TikTok branding, brand building, brand identity, or brand positioning on TikTok.

nexscope-ai/eCommerce-Skills · 55 tokens

tiktok-shop-content-strategy

TikTok Shop content creation strategy and planning. Trending formats, viral hooks, product showcasing, hashtag strategy, and content calendar development. Use when the user asks about TikTok content strategy, viral content creation, TikTok marketing, or content planning.

nexscope-ai/eCommerce-Skills · 56 tokens

amazon-listing-images

Amazon product listing image strategy and optimization. Comprehensive shot planning, infographic design, lifestyle photography, mobile optimization, and conversion-focused visual content. Use when the user asks about Amazon images, product photography, visual optimization, or listing conversion.

nexscope-ai/Amazon-Skills · 51 tokens