marketplace-main-image-preflight

Review an existing product main image for Amazon, Shopify, Etsy, or another marketplace and turn target listing requirements into a clear preflight card. This AI marketplace image checker and Amazon main image editor helps ecommerce sellers prepare white-background product photos, sharpen product framing, clean distracting details, and create one polished listing hero image for a specific store, region, and category.

Turn one existing product main image into a concise, traceable preflight card and one focused, seller-approved cleanup edit. Use this Skill when the seller is close to listing a single SKU and needs to prepare one hero image for one named marketplace, region, and category.

Route a seller to the separate product-photo-studio package when they need a new product shoot, lifestyle scene, multi-image set, or broad creative art direction. This Skill stays with the submitted main image, its listing requirements, and one repair that directly follows the card.

Collect the listing context

Start from the existing image and reuse the product, target marketplace, region, category, and must-keep details already stated in the conversation. The hard inputs are:

• the current main image;
• one target marketplace, region, and product category;
• the product's must-keep identity details, especially any label, logo, color, shape, or included item; and
• current listing requirements when a marketplace, region, or category changes their requirements.

When a target or category is missing, ask one compact question before making the card. When the source image cannot be visually inspected in the current host context, record the seller's description as seller-reported rather than turning it into an observed fact.

Default to one existing image, one target listing surface, source canvas, and one repair. Preserve the product identity and do not make a second variant unless the seller explicitly starts new paid work.

Make the preflight card

Build a card before any image generation. It should be useful to a seller who wants to upload the current image, even if they decide not to edit it:

Card section	Include
Listing scope	Marketplace, region, category, image slot, and the source of the supplied requirements
Image facts	What is visible to the host, or what the seller reports when it is not visible
Requirement check	Each relevant requirement, its source, and ready, needs review, or repair proposed
One repair	The smallest background, edge, distraction, or framing change that improves the card
Seller review	The remaining details the seller should compare with their current marketplace guidance before upload

Treat each marketplace's own submission decision as the final check. The card is a listing-preparation record, so it must name the requirements and evidence it used rather than present a broad certification.

Choose the smallest repair

Choose one route after the seller has seen the card:

• Targeted cleanup: use beatra.images.edit when the current main image remains the base canvas. Put it first in images and use a focused prompt for one issue such as a stray object, edge halo, reflection, or background cleanup. Use edit_regions only when the seller identifies a localized area and its coordinates are known.
• Background or framing treatment: use beatra.images.transform when the requested single repair requires a new clean background or a deliberate reframing. Keep the current main image as the first ordered reference and carry every must-keep product detail into the prompt.

Keep count: 1 and model: "auto" unless a live model card is needed for a specific model, canvas, supported control, or price decision. Read beatra.models.list with capability: "image_edit" or capability: "image_to_image" for that decision. Do not infer dimensions, pixel values, product coverage, or platform rules from an image that the host cannot actually inspect.

Confirm, execute, and review

Planning and the preflight card are free. Before the single paid image call, show the seller the card, exact repair prompt, base image, source or selected canvas, model choice, output count, live price information when it was needed, and the details that must remain unchanged. One clear instruction to proceed approves that frozen request.

Use the bundled scripts/mcp_client.py to upload local media and call the selected MCP tool; keep the returned artifact ID. The tool name is a command argument and its JSON input is sent on standard input. Do not configure or call a host Beatra Connector, and do not use REST/OpenAPI as a fallback.

Assign one stable opaque client_request_id to the approved logical request and submit it exactly once. Record the returned task_id immediately, then poll that task with beatra.tasks.get until it is terminal. When the output is visible, compare the requested repair, protected product details, canvas fit, and any card item that can genuinely be seen. Deliver the result link, actual dimensions, task ID, resolved model, and billing.net_charged_credits, then offer one proposed next repair without executing it.

Recover without duplicate work

Keep the frozen request, approval, client_request_id, create response, and task ID together. A slow queued or running task continues to be the same work. If a create response is lost, retry only the identical request with the same identifier. If the task ID is lost, use beatra.tasks.list to find candidates and confirm the selected task with beatra.tasks.get before any retry. A changed image, prompt, canvas, model, or repair is a new paid request and needs its own approval and identifier.

For an expired upload grant or media mismatch, obtain a fresh upload grant. For model validation, refresh the relevant live model card. For insufficient balance, request a balance action before resubmitting the unchanged request. Cancel only on the seller's request; if beatra.tasks.cancel returns 409, continue tracking the original task rather than creating a replacement.

References by task

• Preparing the card, choosing an edit route, freezing a paid request, and handling task recovery: main image preflight workflow
• First install or expired authorization: installation and authentication
• Non-billable package registration: installation registration
• Task polling, artifacts, and result fields: tasks and results
• Balance, validation, and structured errors: billing, errors, and recovery
• Bundled client command usage and diagnostics: Bundled MCP Client diagnostics
• Update guarantees and controls: automatic updates and safety
• Removing this package or shared credentials: uninstall and disconnect

Runtime and safe automatic updates

The bundled client silently checks for a newer release at most once every 24 hours per installation. When a newer release is available, it installs automatically without separate confirmation. A newer package is downloaded only from the fixed official Beatra discovery and immutable CDN paths for this package, channel, and locale. Before replacement, it verifies discovery data, the archive, manifest, and every packaged file, and it replaces only package-owned files. If a check, download, replacement, or rollback fails, the current installation stays usable and the original command continues. An update failure never retries a paid image request. The setting persists for this installation.

text

python3 scripts/mcp_client.py update --auto off
python3 scripts/mcp_client.py update --auto on
python3 scripts/mcp_client.py update --check

See automatic updates and safety for official sources, integrity checks, replacement scope, and recovery.