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Get Started Free →Generate images using Nano Banana Pro (Gemini 3 Pro Preview). Use when creating app icons, logos, UI graphics, marketing banners, social media images, illustrations, diagrams, or any visual assets. Supports reference images for style transfer and character consistency. Triggers include phrases like 'generate an image', 'create a graphic', 'make an icon', 'design a logo', 'create a banner', 'same style as', 'keep the style', or any request needing visual content.
.claude/skills/itamarzand88-nano-image-generator/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-09 | ✗→✓ | ▲ Improved | 7% | 0% |
| case-01 | ✗→✓ | ▲ Improved | -60% | 0% |
| case-02 | ✗→✓ | ▲ Improved | 106% | 0% |
| case-03 | ✗→✓ | ▲ Improved | -70% | 0% |
| case-04 | ✗→✓ | ▲ Improved | 144% | 0% |
<!-- source: nano-image-generator — https://raw.githubusercontent.com/lxfater/nano-image-generator-skill/main/SKILL.md -->
Generate images using Nano Banana Pro (Gemini 3 Pro Preview) for any visual asset needs. Supports reference images for style transfer and character consistency.
bash# Basic generation python scripts/generate_image.py "A friendly robot mascot waving" --output ./mascot.png # With style reference (keep same visual style) python scripts/generate_image.py "Same style, new content" --ref ./reference.jpg --output ./new.png
bashpython scripts/generate_image.py <prompt> --output <path> [options]
Required:
prompt - Image description--output, -o - Output file pathOptions:
--aspect, -a - Aspect ratio (default: 1:1)1:12:3, 3:4, 4:5, 9:163:2, 4:3, 5:4, 16:9, 21:9--size, -s - Resolution: 1K, 2K (default), 4K--ref, -r - Reference image (can use multiple times, max 14)Gemini supports up to 14 reference images for:
Keep the visual style (colors, textures, mood) from a reference:
bashpython scripts/generate_image.py "New scene with mountains, same visual style as reference" \ --ref ./style-reference.jpg --output ./styled-mountains.png
Maintain character appearance across multiple images:
bashpython scripts/generate_image.py "Same character now in a forest setting" \ --ref ./character.png --output ./character-forest.png
Combine elements from multiple references:
bashpython scripts/generate_image.py "Combine the style of first image with subject of second" \ --ref ./style.png --ref ./subject.png --output ./combined.png
For generating a series with consistent style:
--ref for subsequent imagesbash# Generate cover python scripts/generate_image.py "Tech knowledge card cover" -o ./01-cover.png # Generate subsequent cards with style reference python scripts/generate_image.py "Card 2 content, same style" --ref ./01-cover.png -o ./02-card.png python scripts/generate_image.py "Card 3 content, same style" --ref ./01-cover.png -o ./03-card.png
./assets/icons/./marketing/./src/assets/./generated/--aspect 1:1--aspect 16:9 or 21:9--aspect 9:16--aspect 3:4--aspect 3:2 or 4:3App icon:
bashpython scripts/generate_image.py "Minimalist flat design app icon of a lightning bolt, purple gradient background, modern iOS style" \ --output ./assets/app-icon.png --aspect 1:1
Marketing banner:
bashpython scripts/generate_image.py "Professional website hero banner for a productivity app, abstract geometric shapes, blue and white color scheme" \ --output ./public/images/hero-banner.png --aspect 16:9
Xiaohongshu knowledge card:
bashpython scripts/generate_image.py "Tech knowledge card, dark blue purple gradient, neon cyan accents, code block style, Chinese text '标题'" \ --output ./xiaohongshu/card.png --aspect 3:4
Style transfer:
bashpython scripts/generate_image.py "Transform this photo into watercolor painting style" \ --ref ./photo.jpg --output ./watercolor.png
Character in new scene:
bashpython scripts/generate_image.py "Same character from reference, now sitting in a cafe, warm lighting" \ --ref ./character.png --output ./character-cafe.png --aspect 3:2
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-09 | fail→pass | 11,056 | 5,793 | -48% | 1 | 1 | 0% | 2,544 | 2,724 | +7% | 0 | 0 | — |
case-01 | fail→pass | 53,815 | 4,424 | -92% | 1 | 1 | 0% | 4,322 | 1,715 | -60% | 0 | 0 | — |
case-02 | fail→pass | 10,793 | 1,793 | -83% | 1 | 1 | 0% | 889 | 1,833 | +106% | 0 | 0 | — |
case-03 | fail→pass | 29,431 | 4,998 | -83% | 1 | 1 | 0% | 6,203 | 1,876 | -70% | 0 | 0 | — |
case-04 | fail→pass | 4,238 | 3,104 | -27% | 1 | 1 | 0% | 814 | 1,988 | +144% | 0 | 0 | — |
case-05 | fail→pass | 27,805 | 1,562 | -94% | 1 | 1 | 0% | 6,174 | 1,673 | -73% | 0 | 0 | — |
case-06 | pass→pass | 3,776 | 2,350 | -38% | 1 | 1 | 0% | 817 | 1,834 | +124% | 0 | 0 | — |
case-07 | fail→pass | 8,309 | 2,379 | -71% | 1 | 1 | 0% | 369 | 1,922 | +421% | 0 | 0 | — |
case-08 | fail→fail | 7,922 | 5,282 | -33% | 1 | 1 | 0% | 917 | 1,832 | +100% | 0 | 0 | — |
case-10 | fail→pass | 3,917 | 2,294 | -41% | 1 | 1 | 0% | 433 | 1,842 | +325% | 0 | 0 | — |
case-11 | pass→pass | 6,534 | 1,987 | -70% | 1 | 1 | 0% | 1,002 | 1,769 | +77% | 0 | 0 | — |
case-12 | fail→pass | 16,500 | 6,054 | -63% | 1 | 1 | 0% | 4,473 | 1,916 | -57% | 0 | 0 | — |
case-13 | pass→pass | 11,541 | 3,708 | -68% | 1 | 1 | 0% | 2,977 | 1,881 | -37% | 0 | 0 | — |
case-14 | fail→pass | 40,255 | 2,176 | -95% | 1 | 1 | 0% | 9,335 | 1,740 | -81% | 0 | 0 | — |
case-15 | pass→fail | 7,534 | 4,493 | -40% | 1 | 1 | 0% | 582 | 1,648 | +183% | 0 | 0 | — |
case-16 | fail→pass | 8,021 | 2,350 | -71% | 1 | 1 | 0% | 1,725 | 1,825 | +6% | 0 | 0 | — |
case-17 | fail→pass | 12,184 | 3,037 | -75% | 1 | 1 | 0% | 1,328 | 1,838 | +38% | 0 | 0 | — |
case-18 | pass→pass | 9,909 | 7,175 | -28% | 1 | 1 | 0% | 1,844 | 2,847 | +54% | 0 | 0 | — |
case-19 | fail→pass | 26,446 | 2,214 | -92% | 1 | 1 | 0% | 6,176 | 1,821 | -71% | 0 | 0 | — |
case-20 | fail→pass | 8,390 | 2,366 | -72% | 1 | 1 | 0% | 1,766 | 1,818 | +3% | 0 | 0 | — |
case-21 | pass→pass | 10,148 | 5,638 | -44% | 1 | 1 | 0% | 2,327 | 2,588 | +11% | 0 | 0 | — |
case-22 | fail→fail | 27,546 | 22,945 | -17% | 1 | 1 | 0% | 6,183 | 6,409 | +4% | 0 | 0 | — |
case-23 | pass→pass | 15,192 | 8,596 | -43% | 1 | 1 | 0% | 3,271 | 3,136 | -4% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 23 cases were attempted, and 18 counted toward the lift figure. The other 5 produced results that are not comparable between the two arms, so they are excluded from the headline rather than averaged into it. The headline lift of +57 percentage points is the difference between those two pass rates over the 18 comparable cases. 1 case got worse with the skill loaded, and it is included in that figure.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.