skills/saas-ai-imagery/SKILL.md
Generate AI image prompts for SaaS marketing websites with consistent branding. Covers prompt architecture, style consistency, placement strategy, and extensive examples for hero sections, features, pricing, and more. Use when creating AI-generated images, illustrations, or visual assets for a SaaS website, landing page, or marketing campaign.
npx skillsauth add miketromba/skills saas-ai-imageryInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Generate cohesive, branded AI image assets for SaaS marketing websites using structured prompt engineering and style consistency techniques.
Every production-quality AI image prompt follows this formula:
SUBJECT + ENVIRONMENT + COMPOSITION + LIGHTING + STYLE + CAMERA + QUALITY + NEGATIVES
[Image Type] + [Subject] + [Background Setting] + [Style]
Example: A product illustration of a dashboard interface floating in an abstract gradient space, clean minimal glassmorphism style with soft shadows
"a red car in a forest" produces different results than "a forest with a red car""pores visible on skin" > "highly detailed")Define reusable blocks that get prepended/appended to every prompt. This is the single most important technique for cohesive visual identity across all generated assets.
STYLE BASE: "[Rendering style], [camera/quality descriptor]."
Choose ONE and use everywhere:
"Professional DSLR photography, sharp detail, natural textures, realistic lighting""High-end magazine photography, styled compositions, intentional color grading""Clean 3D render, soft materials, studio-lit product visualization, clay-morphic""Digital illustration, clean lines, flat color areas, vector-like quality""Smooth glass-like surfaces, layered translucency, subtle refraction, digital sculpture"COLOR: "Color palette: [primary with hex], [secondary with hex], [neutrals].
Avoid [unwanted colors]."
Use descriptive language alongside hex codes since AI models respond to descriptions.
LIGHTING: "[Type] from [direction], [color temp]. [Shadow quality].
No [unwanted lighting]."
| Lighting Style | Prompt Language | Brand Feel |
|---|---|---|
| Soft natural | "Soft diffused natural light, warm color temperature" | Approachable, warm |
| Studio professional | "Professional studio lighting, three-point setup, clean shadows" | Corporate, polished |
| Golden hour | "Golden hour sunlight, long warm shadows, backlit glow" | Aspirational, premium |
| Flat even | "Even flat lighting, minimal shadows, bright and clean" | Modern, tech, minimal |
COMPOSITION: "[Shot type], [subject placement], [depth of field],
[perspective]. [Negative space for text overlay]."
EXCLUSIONS: "No: [unwanted elements, styles, artifacts]."
Always include at minimum: "No: cartoonish elements, text, watermarks, logos, cluttered backgrounds"
[Subject Description] + [STYLE BASE] + [COLOR] + [LIGHTING] + [COMPOSITION] + [EXCLUSIONS]
The subject changes per image. Everything else stays constant. That is how you get consistency.
Create a reusable template with a {SUBJECT} variable:
"{SUBJECT}. [Your style base]. Color palette dominated by [your colors].
[Your lighting]. [Your composition]. No: [your exclusions]."
Swap only the subject for each new image. All other blocks remain identical.
--sref [URL] to apply the visual style of an existing image to new generations--sref [code] with 10-digit style codes from Midjourney's style library--sw [0-1000] to control style influence strength (default 100)--sref random to discover new styles, then reuse the generated code--sv 7 (default) for latest style reference algorithmMidjourney personalization (--p) applies learned aesthetic preferences. Create dedicated profiles for your brand by selecting images that match your desired look.
Use --seed [number] in Midjourney to get reproducible starting points. Same seed + similar prompt = more consistent outputs.
See placement-guide.md for detailed placement strategies.
Quick reference:
| Section | Image Type | Purpose | |---|---|---| | Hero | Abstract 3D / surreal / metaphorical | Communicate value prop emotionally | | Features | Spot illustrations (one per feature) | Clarify each feature's benefit | | How It Works | Schematic/blueprint style | Show process flow visually | | Social Proof | Lifestyle/editorial photos | Build trust and relatability | | Pricing | Premium 3D / polished icons | Signal value, justify pricing | | CTA sections | Character-driven / aspirational | Drive action with emotion | | Blog headers | Thematic illustrations | Set context for content |
| Style | Best Signal | Ideal Audience | Top Placement | |---|---|---|---| | Tactile Tech (vector + organic texture) | "Human and capable" | Fintech, Security, DevOps | Hero, About | | Blueprint (monolinear, schematic) | "Precise and reliable" | Engineering, PM tools | How It Works, Features | | Spot Illustrations (small, consistent) | "Organized and clear" | All SaaS products | Feature cards, Pricing | | Abstract Surreal | "Innovative and seamless" | AI, Automation, Analytics | Hero background, Headers | | High-Contrast 3D (clay-morphic, glossy) | "Premium and polished" | Enterprise, Design tools | Hero, Pricing | | Character-Driven | "Approachable and memorable" | HR, Education, Community | Everywhere (system) |
Midjourney: Thrives on descriptive natural language + photographic terminology. Use --ar, --stylize, --sref, --style raw for control. Words at prompt start get most weight.
DALL-E / GPT Image Gen: Favors conversational, narrative descriptions. Best for exact text rendering and spatial composition. Fewer technical camera keywords needed.
Flux: Strong at photorealism and prompt adherence. Benefits from explicit camera/lens specifications and structured prompts.
Stable Diffusion (SDXL/SD3): Requires strict syntax, strong negative prompts, and keyword weighting (keyword:1.5). Pair with ControlNet for pose/depth control.
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