zpoint/vibe-seller/amazon-image-studio

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.