version: "1.0.0" name: amazon-image-studio description: "Amazon listing-image knowledge for the general vibe_seller_generate_image tool: Amazon's image requirements (main/secondary), how to collect reference images from Amazon listings and supplier pages (e.g. 1688), and how to avoid poisoning generation with placeholder/blank images. Load this ONLY when the image work is FOR Amazon — creating or editing listing images (main image, gallery, infographic/A+), or when the user asks to match an Amazon listing's image style or meet Amazon requirements. Do NOT load it for generic image requests with no Amazon connection ('edit this picture', 'make me a fun image') — the vibe_seller_generate_image tool alone handles those." allowed-tools: Bash(browser-use:*) requires: [amazon-shared]

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);

1. 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.

3. Generate, audit, hand off

• One vibe_seller_generate_image call per image (kind: "main",

"infographic", …). Use nano-banana-pro for anything with on-image text.

• **Every image comes from the model — including "just remove the

background". "Keep the product, only drop the background", "put it on white", "crop it square" are all *generation* jobs: one `vibe_seller_generate_image` call whose `reference_images` is the photo and whose prompt says to keep the product identical and change only the background. Do not** reach for rembg, Pillow/OpenCV compositing, or ImageMagick — a PreToolUse guard blocks them, and generated_images/ is the tool's directory (each file's recorded prompt + model is what the user's inline card claims). A local cutout also loses what the model gives you for free: relit edges, a clean contact shadow, and no halo on hair/mesh/glass.

• After each image is saved, view the returned workspace path and

compare against the ORIGINAL supplier photo item by item (shape, colour, texture, proportions; infographic wording). Regenerate with a prompt naming the specific fix if anything differs.

• If you cannot actually SEE the image (the Read comes back as

something you can't look at — some models are text-only), say so and let the user judge: the image renders inline in the task. Do NOT substitute a pixel-measurement script for looking, and never act on what such a script measured — corner-RGB sampling and coverage-percent arithmetic answer a different question than "is this the right product image", and "fixing" those numbers locally is how the deliverable stops being the model's.

• Off-white background or an over-filled frame — the two things a

first pass gets wrong on a main image (e.g. RGB(254,254,253) instead of pure white, or the product bleeding to the edges). Fix by regenerating, never by post-processing: call the tool again with the PREVIOUS generated image as the reference_image and a prompt naming only the fix — "keep the product pixel-identical; background must be pure white RGB(255,255,255); leave a clear margin on all four sides so the product fills about 85% of the frame and touches no edge".

• Revising on user feedback — for ANY change the user asks after

seeing a generated image (lighter/darker, bigger/smaller, recolour, remove or add an element, change composition, …): call vibe_seller_generate_image again and ALWAYS pass the PREVIOUSLY GENERATED image (its generated_images/… path) as a reference_image, with a prompt describing ONLY the requested change. This EDITS the prior result — keeping what the user was happy with — instead of regenerating from the supplier photo and drifting. If the user also drops a NEW photo for the change (e.g. "this one's good, add my dog in the middle"), pass BOTH the previous generated image AND the new photo as reference_images and name each image's role by position in the prompt ("image 1 is the current design to keep; image 2 is the dog to add in the center").

• Putting the images ON a listing is the amazon-listing flow (Manage

Images / flat file) — this skill only produces the files.