# AI Multimodal Integration for Frontend Design Entry point for using the `ck:ai-multimodal` skill to generate and analyze visual assets that align with frontend design thinking and aesthetic guidelines. ## When to Use Use `ck:ai-multimodal` in frontend design when you need to: **Asset Generation**: - Generate hero images, background assets, decorative elements - Create placeholder images with specific aesthetic qualities - Produce marketing visuals that match UI design language - Generate icon sets, illustrations, or graphic elements - Create texture overlays, gradient meshes, or background patterns - Prototype visual concepts before implementing in code **Visual Analysis**: - Analyze generated assets to verify they meet design standards - Compare multiple variations objectively with ratings - Extract exact color palettes with hex codes for implementation - Test assets with UI overlays for readability and contrast **Design Extraction**: - Extract design guidelines from existing images or videos - Analyze competitor designs to understand their approach - Reverse-engineer design systems from inspiration screenshots - Create documented guidelines based on visual analysis - Establish consistent aesthetic direction from references ## Core Principles ### 1. Design-Driven Generation **NEVER** generate generic AI imagery. Every asset must align with: - The chosen aesthetic direction (brutalism, maximalism, retro-futurism, etc.) - Typography system and visual hierarchy - Color palette and theme consistency - Overall design story and purpose ### 2. Contextual Asset Creation Assets aren't standalone—they're part of a cohesive interface. Consider: - **Purpose**: Hero image vs. background texture vs. decorative element - **Integration**: How it interacts with overlaid text, buttons, forms - **Technical constraints**: File size, aspect ratio, responsive behavior - **Accessibility**: Color contrast, text readability, decorative vs. informative ### 3. Analysis is Mandatory Never integrate assets without comprehensive analysis: - Score quality objectively (1-10 scale, minimum 7/10) - Extract specific values: hex codes, not "blue"; px sizes, not "large" - Compare multiple variations before deciding - Test with UI overlays, not in isolation ### 4. Learn from Excellence Extract design systems systematically from high-quality references: - Analyze 3-5 screens to identify patterns - Document actionably with CSS variables and exact values - Validate predictions (fonts, colors) manually - Adapt principles contextually, don't copy blindly ## Workflow Quick Reference ### For Asset Generation **See**: `asset-generation.md` 1. Define design context (aesthetic, colors, typography, tone) 2. Craft design-driven prompts (not generic) 3. Generate with appropriate Imagen 4 model 4. Analyze and verify quality (score ≥ 7/10) 5. Iterate or integrate based on results **Models**: imagen-4.0-generate-001 (standard), imagen-4.0-ultra-generate-001 (production), imagen-4.0-fast-generate-001 (iteration) ### For Visual Analysis **See**: `visual-analysis.md` 1. Define evaluation criteria (context-specific) 2. Run comprehensive analysis with structured prompts 3. Compare multiple variations objectively 4. Extract color palettes with hex codes 5. Test integration with UI elements **Model**: gemini-2.5-flash (vision understanding) ### For Design Extraction **See**: `design-extraction.md` 1. Capture high-quality reference screenshots 2. Extract comprehensive design elements systematically 3. Analyze multiple screens for consistent patterns 4. Extract motion guidelines from videos (if applicable) 5. Document actionably with CSS-ready specifications **Model**: gemini-2.5-flash (vision understanding) ## Integration with Other Skills ### With `aesthetic` Skill Use `aesthetic` for overall design system guidance and quality evaluation framework. Then use `ck:frontend-design` with `ck:ai-multimodal` for asset generation and analysis that follows those guidelines. ### With `ck:chrome-devtools` Skill Use `ck:chrome-devtools` to capture full-screen screenshots from inspiration websites for design extraction. Capture at actual viewport size, not full-page scrolls. ### With `ui-styling` Skill Generate and analyze assets first, then implement using shadcn/ui + Tailwind with colors/styles that complement the generated imagery. ### With `web-frameworks` Skill Optimize generated assets for Next.js App Router: image optimization, responsive images, lazy loading. ### With `ck:media-processing` Skill Post-process generated assets: resize, compress, add filters, create compositions using FFmpeg/ImageMagick. ## Navigation **Detailed Workflows**: - `asset-generation.md` - Complete generation workflow with prompt strategies - `visual-analysis.md` - Analysis and verification workflow - `design-extraction.md` - Extract guidelines from existing designs **Additional Resources**: - `technical-guide.md` - File optimization, examples, checklists, common pitfalls - `animejs.md` - Animation implementation for frontend ## Quick Commands **Generate asset**: ```bash python scripts/gemini_batch_process.py \ --task generate \ --prompt "[design-driven prompt]" \ --output docs/assets/[name] \ --model imagen-4.0-generate-001 \ --aspect-ratio 16:9 ``` **Analyze asset**: ```bash python scripts/gemini_batch_process.py \ --files docs/assets/[image].png \ --task analyze \ --prompt "[evaluation criteria]" \ --output docs/assets/analysis.md \ --model gemini-2.5-flash ``` **Extract design guidelines**: ```bash python scripts/gemini_batch_process.py \ --files docs/inspiration/[reference].png \ --task analyze \ --prompt "[extraction criteria from design-extraction.md]" \ --output docs/design-guidelines/extracted.md \ --model gemini-2.5-flash ``` ## Remember 1. **Design First, Generate Second**: Start with design thinking, not generation capabilities 2. **Context is King**: Every asset serves the interface, not itself 3. **Iterate Ruthlessly**: First generation is rarely final—evaluate and refine 4. **Analysis is Mandatory**: Never integrate without comprehensive verification (≥7/10) 5. **Demand Specifics**: Hex codes not "blue", px not "large", ms not "fast" 6. **Learn from Excellence**: Extract design systems from high-quality references systematically 7. **Adapt, Don't Copy**: Understand principles, apply contextually to your unique design Generate assets that elevate frontend design, maintain aesthetic consistency, and serve user experience—never generic, always contextual.