commercial

Commercial production with genmedia

Use this skill when the user wants advertising, product, brand, or e-commerce media. Load the reference files when you need prompt patterns or category examples:

• references/prompt-patterns.md
• references/workflows.md
• references/examples.md

Load model-routing alongside this skill for default endpoint choices.

Keep the output production-focused. Do not add inflated marketing language, unsupported claims, fake text in the image, or em dashes.

Inputs to collect

Only ask when the answer cannot be inferred from the task or the source files.

• Product: exact product name, category, material, color, scale, logo rules.
• Goal: hero shot, PDP image, ad creative, motion reveal, demo, UGC, lifestyle.
• Platform: square, vertical, landscape, banner, transparent background, print.
• Brand: premium, playful, clinical, athletic, minimal, natural, technical.
• Source media: product packshot, logo, reference scene, prior generated asset.
• Constraints: preserve packaging, avoid new labels, no fake readable copy.
• Model preference: use model-routing defaults unless the user names a model or the job is unusually expensive.

Genmedia workflow

1. Start from routed endpoint IDs.

   genmedia models --endpoint_id openai/gpt-image-2 --json
   genmedia models --endpoint_id fal-ai/nano-banana-pro/edit --json
   genmedia models --endpoint_id fal-ai/nano-banana-2 --json
   genmedia models --endpoint_id bytedance/seedance-2.0/image-to-video --json
   

   Use text search only as fallback discovery for a missing utility or unsupported role:

   genmedia models "background removal product image" --json
   genmedia docs "commercial product image generation" --json
   

2. Inspect the selected endpoint before running.

   genmedia schema <endpoint_id> --json
   genmedia pricing <endpoint_id> --json
   

3. Upload every local or remote reference file.

   genmedia upload ./product.png --json
   genmedia upload ./logo.png --json
   

4. Run still-image jobs synchronously when they are quick.

   genmedia run <endpoint_id> \
     --prompt "<commercial prompt>" \
     --image_url "<uploaded product url if supported>" \
     --download "./outputs/commercial/{request_id}_{index}.{ext}" \
     --json
   

5. Run video jobs async and download from status.

   genmedia run <endpoint_id> \
     --prompt "<motion prompt>" \
     --image_url "<uploaded hero frame if supported>" \
     --async \
     --json
   
   genmedia status <endpoint_id> <request_id> \
     --download "./outputs/commercial/{request_id}_{index}.{ext}" \
     --json
   

6. Use schema fields exactly. Do not pass guessed flags. If the model uses image_urls, reference_image_url, aspect_ratio, duration, seed, or another name, mirror that schema.

Prompt build order

Write prompts in this order so commercial intent stays clear:

1. Product invariant: exact object, material, color, packaging, scale.
2. Commercial role: hero image, PDP image, launch teaser, demo shot, social ad.
3. Setting: surface, background, props, environment, distance from product.
4. Lighting: softbox, strip light, rim light, backlight, caustics, practicals.
5. Camera: angle, focal length feel, macro, depth of field, motion if video.
6. Composition: centered, negative space, safe zone, text-free area, platform.
7. Brand tone: premium, clean, clinical, bold, energetic, warm, editorial.
8. Guardrails: preserve logo and packaging, no extra text, no distorted labels.

Do not promise claims like "best", "clinically proven", "50 percent faster", or celebrity endorsements unless the user provides that copy.

Model routing

• Text-heavy ads, labels, posters, UI mockups, packaging copy, and infographics: use openai/gpt-image-2 at quality=high. Prefer 2K or 4K when the final must carry small readable details. Treat this as expensive.
• Premium realistic stills: use openai/gpt-image-2.
• Premium stylized stills: use openai/gpt-image-2, then fal-ai/nano-banana-pro, then fal-ai/nano-banana-2.
• Fast draft stills: use fal-ai/flux-2/klein/9b.
• Image edits: use fal-ai/nano-banana-pro/edit, then openai/gpt-image-2/edit, then fal-ai/bytedance/seedream/v5/lite/edit.
• Product fidelity: use fal-ai/nano-banana-pro, fal-ai/nano-banana-2, or fal-ai/bytedance/seedream/v5/lite/text-to-image; use the matching edit endpoint when a product reference image exists.
• Product reveal video: create or upload a strong hero frame, then use bytedance/seedance-2.0/image-to-video for final quality.
• Fast or lower-cost video draft: use xai/grok-imagine-video/image-to-video or xai/grok-imagine-video/text-to-video.
• E-commerce batch: keep the same prompt skeleton and vary only background, crop, lighting, or platform format.
• Text overlays: generate with empty safe space. Add final text in a design or editing tool unless the selected model is explicitly good at typography.
• Background removal or cleanup: search for background removal, segmentation, inpainting, or product editing models and inspect their schemas.
• Final delivery: use --download with {request_id} and {index}.

Quality bar

Before returning, check:

• Product shape, logo, material, and color are not invented or distorted.
• The composition leaves enough room for platform crop and optional copy.
• Background props support the product and do not compete with it.
• Any generated text is absent or intentionally controlled.
• Lighting makes sense for the product material.
• Output paths are from downloaded_files[], not manually curled URLs.

If the result misses product fidelity, switch from text-only generation to a reference or edit workflow before retrying.