# Content Image > Image prompt engineering for AI image generation models. Use when user wants to generate images, create image prompts, or optimize prompts for DALL-E, Midjourney, Stable Diffusion, or other image generation tools. - Skill: `vstorm-co/content-image` (Agent Skill, multi-file: 6 files) - Install (CLI): `npx skillmds@latest add vstorm-co/content-image` - Raw SKILL.md: https://api.skillmd.com/api/skills/vstorm-co/content-image/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: AI & ML - Author: vstorm-co (https://skillmd.com/u/vstorm-co) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/vstorm-co/content-image --- # Content Image Skill ## Important: This Skill Generates Prompts, Not Images Claude cannot generate images. This skill produces **ready-to-paste prompts** optimized for AI image generation models. The output is text that the user copies into DALL-E, Midjourney, Stable Diffusion, or another image generation tool. Every output includes: 1. The prompt text (optimized for the target model) 2. Recommended model and settings 3. Negative prompt (where the model supports it) 4. Variations to try --- ## When This Skill Activates - User asks for an image, illustration, or visual asset - User wants to create image prompts or optimize existing prompts - User mentions DALL-E, Midjourney, Stable Diffusion, Flux, or other image generation tools - User says "generate an image of..." or "I need a visual for..." - User wants a hero image, social media graphic, blog illustration, or product shot --- ## Prompt Structure Every effective image prompt has four components: ### 1. Subject What is in the image. Be specific and concrete. - Bad: "a person working" - Good: "a software developer sitting at a standing desk with dual monitors, writing code, coffee mug nearby" The subject should be described in enough detail that two different artists would produce recognizably similar images. ### 2. Style The visual treatment. Reference a specific style from the style library or describe it explicitly. - Bad: "nice looking" - Good: "editorial photography, shallow depth of field, natural window light, 35mm lens" See `style-library/` for pre-built style descriptions: - `style-library/editorial.md` -- Clean, professional photography - `style-library/flat-illustration.md` -- Bold, geometric, vector-like - `style-library/3d-render.md` -- Soft lighting, smooth surfaces, product-shot feel - `style-library/film-still.md` -- Cinematic, dramatic, atmospheric ### 3. Mood / Atmosphere The emotional tone of the image. - Calm, focused, productive - Energetic, vibrant, optimistic - Dramatic, tense, high-stakes - Warm, inviting, approachable - Minimal, quiet, contemplative ### 4. Technical Specs Resolution, aspect ratio, and model-specific parameters. - Aspect ratio: 16:9 (hero banners), 1:1 (social), 4:5 (Instagram portrait), 3:2 (blog photos) - Quality: high detail, photorealistic vs. stylized - Lighting: natural, studio, dramatic, flat, backlighting - Camera: wide angle, close-up, overhead, eye-level --- ## Generation Flow ### Step 1: Read Brand Context If `brand/VISUAL.md` exists, read it for: - Color palette (suggest prompts that align with brand colors) - Visual style preference (photography vs. illustration, minimal vs. bold) - Mood and tone (professional, playful, technical) If the brand aesthetic is "clean, minimal, professional," do not suggest prompts for grungy textures or maximalist compositions. ### Step 2: Understand the Need Ask: - **What is the image for?** Blog header, social post, presentation slide, product page, email banner. - **What should it show?** The subject matter. - **What feeling should it evoke?** The mood. - **Any existing visual references?** Links to images they like. - **Target model?** DALL-E, Midjourney, Stable Diffusion, or no preference. If the user provides a vague request ("I need an image for my blog post about AI"), ask for specifics before generating prompts. ### Step 3: Select Style Based on the brand and use case, recommend a style: | Use Case | Recommended Style | Why | |---|---|---| | Blog hero image (professional) | Editorial photography | Clean, credible, publication-quality | | Social media graphic | Flat illustration | Eye-catching, scalable, shares well | | Product landing page | 3D render | Modern, polished, product-focused | | Thought leadership piece | Film still | Dramatic, memorable, shareable | | Technical documentation | Flat illustration | Clear, diagrammatic, on-brand | | Event promotion | Editorial or film still | Atmospheric, engaging | ### Step 4: Build Prompt Assemble the prompt using the four components (subject + style + mood + technical specs). Structure varies by model -- see `model-specifics.md`. ### Step 5: Add Negative Prompt For models that support negative prompts (Stable Diffusion, some Midjourney modes), specify what to avoid: Common negative prompt elements: - "blurry, low quality, distorted, deformed" - "text, watermark, signature, logo" (unless text is desired) - "stock photo, generic, clip art" (for editorial/premium look) - "oversaturated, neon, garish" (for professional/muted aesthetics) ### Step 6: Provide Variations Always offer 2-3 prompt variations: 1. **Close-up variant**: Tighter framing, more detail on the subject. 2. **Wide variant**: Environmental context, more setting. 3. **Alternative style**: A different visual treatment for comparison. --- ## Brand Alignment When generating prompts, align with the brand aesthetic from `brand/VISUAL.md`: ### Color Alignment If the brand uses warm earth tones, suggest prompts with: - "warm lighting, golden hour, earth tones, amber and terracotta palette" If the brand uses cool blues and grays, suggest: - "cool lighting, blue-gray tones, steel and slate palette, overcast sky" Do not force brand colors into every image, but guide the aesthetic direction. ### Style Alignment | Brand Aesthetic | Prompt Direction | |---|---| | Minimal, clean | "clean composition, negative space, simple background, uncluttered" | | Bold, vibrant | "saturated colors, dynamic composition, high contrast, energetic" | | Corporate, professional | "studio lighting, neutral background, polished, sharp focus" | | Playful, creative | "whimsical elements, bright colors, unexpected angles, hand-drawn feel" | | Technical, precise | "technical illustration, blueprint aesthetic, grid lines, precise geometry" | ### Consistency Across Assets When generating multiple prompts for the same project (e.g., a series of blog post images), maintain consistency: - Same style and mood across all prompts - Same aspect ratio and quality settings - Same color temperature and lighting direction - Reference the same style library entry for all prompts in the series --- ## Model-Specific Optimization See `model-specifics.md` for detailed guidance. Summary: ### DALL-E 3 - Uses natural language descriptions - Longer, more descriptive prompts work well - Specify style, mood, and technical details in full sentences - No negative prompt support (describe what you want, not what you do not want) ### Midjourney - Responds well to stylistic keywords and aesthetic references - Use `--ar` for aspect ratio, `--s` for stylization, `--q` for quality - Shorter, more keyword-driven prompts can be effective - Version-specific parameters (v6, v6.1) ### Stable Diffusion - Supports weighted tokens: `(important detail:1.3)` for emphasis - Negative prompts are critical for quality - Sampler and step count affect output - LoRA and checkpoint selection matter --- ## Output Format For each prompt request, deliver: ``` ## Prompt [The full prompt text, ready to paste] ## Model & Settings - **Recommended model**: [DALL-E 3 / Midjourney v6.1 / SDXL] - **Aspect ratio**: [16:9 / 1:1 / 4:5 / etc.] - **Quality/Steps**: [model-specific settings] ## Negative Prompt (if applicable) [Negative prompt text for SD/MJ] ## Variations ### Variation 1: [Description] [Alternative prompt] ### Variation 2: [Description] [Alternative prompt] ## Notes [Any tips for getting the best result: regenerate if X, adjust Y for Z] ``` --- ## Common Prompt Patterns ### The "Person Doing Thing" Pattern `[demographic detail] [person description] [action] in [setting], [style], [lighting], [mood]` Example: "A mid-30s Southeast Asian woman reviewing data on a tablet in a modern open office, editorial photography, natural window light from the left, focused and productive atmosphere" ### The "Product Shot" Pattern `[product] on [surface/background], [camera angle], [lighting setup], [style]` Example: "A matte black wireless keyboard on a minimal white desk, 45-degree angle, soft studio lighting with subtle shadow, 3D product render, clean and modern" ### The "Abstract Concept" Pattern `[visual metaphor for concept], [style], [color palette], [mood]` Example: "Interconnected glowing nodes forming a neural network pattern, dark background, blue and purple gradient, isometric 3D render, futuristic and clean" ### The "Environment" Pattern `[place description], [time of day], [weather/atmosphere], [style], [camera position]` Example: "A coworking space with floor-to-ceiling windows at golden hour, plants on desks, warm natural light, editorial photography, wide angle from the entrance" --- ## What This Skill Does Not Do - Generate actual images (Claude is a text model) - Create SVG graphics (use content-infographic for that) - Design logos or brand marks (use a designer or specialized tool) - Edit existing photos (use Photoshop, Lightroom, or similar) If the user needs an SVG or infographic, redirect to the content-infographic skill. If they need a presentation visual, redirect to content-presentation.