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slug: muapi-amazon-product-listing name: muapi-amazon-product-listing version: "1.0.0" description: Generate a complete Amazon product listing image set — hero image, lifestyle shot, infographic with features, and comparison/detail closeups optimized for Amazon standards. acceptLicenseTerms: true

Amazon Product Listing Pack

Generate a complete Amazon product listing image set — hero image, lifestyle shot, infographic with features, and comparison/detail closeups optimized for Amazon standards.

Inputs

| Name | Type | Required | Default | Description | |:---|:---|:---|:---|:---| | product_name | text | yes | — | The product name (e.g. "Stainless Steel Water Bottle 32oz"). | | product_category | text | yes | — | Amazon category (e.g. "Kitchen & Dining", "Sports & Outdoors", "Electronics"). | | key_features | text | yes | — | Comma-separated top features to highlight (e.g. "leak-proof lid, BPA-free, keeps cold 24h, fits cupholder"). | | target_buyer | text | no | general consumer | Who buys this (e.g. "athletes", "busy moms", "office workers aged 25-45"). | | product_image | image_url | no | — | Optional existing product photo to use as base reference. |

Steps

Submit a SINGLE the plan with all steps running in parallel.

All 4 Images (Parallel)

1. Hero image (white background) — muapi image generate (model=ai-product-photography) if {{product_image}} provided, else muapi image generate (model=gpt4o-text-to-image):

   • Prompt: Professional Amazon main listing hero image of {{product_name}}. Pure white background #FFFFFF. Product centered, perfectly lit with soft studio lighting, no shadows. High resolution, commercial product photography, sharp focus on all details, 2000x2000px equivalent quality.
   • Aspect ratio: 1:1

2. Lifestyle/context shot — muapi image generate (model=ai-product-shot) if {{product_image}} provided, else muapi image generate (model=nano-banana-pro):

   • Prompt: Amazon lifestyle image of {{product_name}} being used by {{target_buyer}} in a natural setting. {{product_category}} product in real-life use context. Warm natural lighting, aspirational but relatable, slight bokeh background. Commercial lifestyle photography, professional quality.
   • Aspect ratio: 1:1

3. Feature infographic — muapi image generate (model=gpt4o-text-to-image):

   • Prompt: Amazon product detail page infographic for {{product_name}}. Shows product with 4-5 callout arrows highlighting these key features: {{key_features}}. Clean white or light grey background, professional typography, bold feature labels with icons. Amazon A+ content style, feature benefit layout, commercial design.
   • Aspect ratio: 1:1

4. Closeup detail shot — muapi image generate (model=nano-banana-pro):

   • Prompt: Extreme closeup macro product detail shot of {{product_name}} — focus on premium materials, texture, quality craftsmanship. Studio lighting, white background, ultra sharp focus, demonstrates quality. Amazon product detail image showing materials/finish.
   • Aspect ratio: 1:1

After generation:

• Present all 4 images in order (main > lifestyle > infographic > detail)
• Suggest uploading to canvas to arrange as a listing mockup
• Offer to generate 3 additional A+ content module images

Notes

• Amazon requires main image on pure white background — enforce this strictly.
• Key features should be visually distinct and scannable in the infographic.
• For electronics, add "showing ports, buttons, and connections clearly" to the detail shot.

Trigger Keywords

amazon listing, amazon product, product listing, ecommerce listing, amazon images, product photography amazon, listing images

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Notes for the Executing Agent

• This recipe is LLM-orchestrated: read each phase, gather any missing inputs from the user, then call muapi CLI commands. Use muapi auth configure first if MUAPI_API_KEY is unset.
• For model IDs without a CLI alias yet, fall back to the raw endpoint via curl -X POST https://api.muapi.ai/api/v1/<endpoint> -H "x-api-key: $MUAPI_API_KEY" -H 'content-type: application/json' -d '{...}' and poll with muapi predict wait <request_id>.
• Substitute {{input_name}} placeholders with the user's actual inputs before issuing each call.