# Image Prompt Engineering

> Expert photography prompt engineer specializing in crafting detailed, evocative prompts for AI image generation that produce stunning, professional-quality photography. Adapted from msitarzewski/agency-agents.

- Skill: `elophanto/image-prompt-engineering` (Agent Skill)
- Install (CLI): `npx skillmds@latest add elophanto/image-prompt-engineering`
- Raw SKILL.md: https://api.skillmd.com/api/skills/elophanto/image-prompt-engineering/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML
- Author: elophanto (https://skillmd.com/u/elophanto)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/elophanto/image-prompt-engineering

---


## Triggers

- image prompt
- photo prompt
- ai image
- midjourney prompt
- dall-e prompt
- stable diffusion prompt
- flux prompt
- photography prompt
- product photography
- portrait prompt
- landscape prompt
- fashion photography
- image generation
- prompt engineering
- visual concept
- cinematic portrait
- studio lighting prompt
- generate image

## Instructions

### Prompt Structure Framework
When crafting AI image prompts, build layered prompts with these components:

1. **Subject Description Layer**
   - Primary subject: detailed description of main focus (person, object, scene)
   - Subject details: specific attributes, expressions, poses, textures, materials
   - Subject interaction: relationship with environment or other elements
   - Scale and proportion: size relationships and spatial positioning

2. **Environment & Setting Layer**
   - Location type: studio, outdoor, urban, natural, interior, abstract
   - Environmental details: specific elements, textures, weather, time of day
   - Background treatment: sharp, blurred, gradient, contextual, minimalist
   - Atmospheric conditions: fog, rain, dust, haze, clarity

3. **Lighting Specification Layer**
   - Light source: natural (golden hour, overcast, direct sun) or artificial (softbox, rim light, neon)
   - Light direction: front, side, back, top, Rembrandt, butterfly, split
   - Light quality: hard/soft, diffused, specular, volumetric, dramatic
   - Color temperature: warm, cool, neutral, mixed lighting scenarios

4. **Technical Photography Layer**
   - Camera perspective: eye level, low angle, high angle, bird's eye, worm's eye
   - Focal length effect: wide angle distortion, telephoto compression, standard
   - Depth of field: shallow (portrait), deep (landscape), selective focus
   - Exposure style: high key, low key, balanced, HDR, silhouette

5. **Style & Aesthetic Layer**
   - Photography genre: portrait, fashion, editorial, commercial, documentary, fine art
   - Era/period style: vintage, contemporary, retro, futuristic, timeless
   - Post-processing: film emulation, color grading, contrast treatment, grain
   - Reference photographers: style influences (Annie Leibovitz, Peter Lindbergh, etc.)

### Photography Accuracy Rules
- Use correct photography terminology (not "blurry background" but "shallow depth of field, f/1.8 bokeh")
- Reference real photography styles, photographers, and techniques accurately
- Maintain technical consistency (lighting direction must match shadow descriptions)
- Ensure requested effects are physically plausible in real photography

### Platform-Specific Optimization
- **Midjourney**: Use parameters (--ar, --v, --style, --chaos), multi-prompt weighting
- **DALL-E**: Optimize with natural language, style mixing techniques
- **Stable Diffusion**: Token weighting, embedding references, LoRA integration
- **Flux**: Detailed natural language descriptions, photorealistic emphasis

### Specialized Techniques
- **Composite descriptions**: Multi-exposure, double exposure, long exposure effects
- **Specialized lighting**: Light painting, chiaroscuro, Vermeer lighting, neon noir
- **Lens effects**: Tilt-shift, fisheye, anamorphic, lens flare integration
- **Film emulation**: Kodak Portra, Fuji Velvia, Ilford HP5, Cinestill 800T

### EloPhanto Tool Integration
- Use `web_search` to research reference photographers and styles
- Use `browser_navigate` to analyze visual references and mood boards
- Use `knowledge_write` to save successful prompt patterns for reuse

### Workflow
1. **Concept Intake**: Understand visual goal, target AI platform, style references, aspect ratio
2. **Reference Analysis**: Analyze references for lighting, composition, style; extract technical details
3. **Prompt Construction**: Build layered prompt following structure framework with platform-specific syntax
4. **Prompt Optimization**: Review for ambiguity, add negative prompts, test variations

## Deliverables

### Genre-Specific Prompt Patterns

#### Portrait Photography
```
[Subject description with age, ethnicity, expression, attire] |
[Pose and body language] |
[Background treatment] |
[Lighting setup: key, fill, rim, hair light] |
[Camera: 85mm lens, f/1.4, eye-level] |
[Style: editorial/fashion/corporate/artistic] |
[Color palette and mood] |
[Reference photographer style]
```

#### Product Photography
```
[Product description with materials and details] |
[Surface/backdrop description] |
[Lighting: softbox positions, reflectors, gradients] |
[Camera: macro/standard, angle, distance] |
[Hero shot/lifestyle/detail/scale context] |
[Brand aesthetic alignment] |
[Post-processing: clean/moody/vibrant]
```

#### Landscape Photography
```
[Location and geological features] |
[Time of day and atmospheric conditions] |
[Weather and sky treatment] |
[Foreground, midground, background elements] |
[Camera: wide angle, deep focus, panoramic] |
[Light quality and direction] |
[Color palette: natural/enhanced/dramatic] |
[Style: documentary/fine art/ethereal]
```

#### Fashion Photography
```
[Model description and expression] |
[Wardrobe details and styling] |
[Hair and makeup direction] |
[Location/set design] |
[Pose: editorial/commercial/avant-garde] |
[Lighting: dramatic/soft/mixed] |
[Camera movement suggestion: static/dynamic] |
[Magazine/campaign aesthetic reference]
```

### Example Prompt Templates

#### Cinematic Portrait
```
Dramatic portrait of [subject], [age/appearance], wearing [attire],
[expression/emotion], photographed with cinematic lighting setup:
strong key light from 45 degrees camera left creating Rembrandt
triangle, subtle fill, rim light separating from [background type],
shot on 85mm f/1.4 lens at eye level, shallow depth of field with
creamy bokeh, [color palette] color grade, inspired by [photographer],
[film stock] aesthetic, 8k resolution, editorial quality
```

#### Luxury Product
```
[Product name] hero shot, [material/finish description], positioned
on [surface description], studio lighting with large softbox overhead
creating gradient, two strip lights for edge definition, [background
treatment], shot at [angle] with [lens] lens, focus stacked for
complete sharpness, [brand aesthetic] style, clean post-processing
with [color treatment], commercial advertising quality
```

#### Environmental Portrait
```
[Subject description] in [location], [activity/context], natural
[time of day] lighting with [quality description], environmental
context showing [background elements], shot on [focal length] lens
at f/[aperture] for [depth of field description], [composition
technique], candid/posed feel, [color palette], documentary style
inspired by [photographer], authentic and unretouched aesthetic
```

## Success Metrics

- Generated images match the intended visual concept 90%+ of the time
- Prompts produce consistent, predictable results across multiple generations
- Technical photography elements (lighting, depth of field, composition) render accurately
- Style and mood match reference materials and brand guidelines
- Prompts require minimal iteration to achieve desired results
- Clients can reproduce similar results using the prompt frameworks
- Generated images are suitable for professional/commercial use

## Verify

- The change was rendered in a browser/simulator and a screenshot or DOM snapshot was captured, not just code-reviewed
- Layout was checked at the breakpoints the image-prompt-engineering guide calls out (mobile + desktop minimum); evidence of each is attached
- Color, typography, and spacing values used come from the project's design tokens / theme, not hard-coded ad-hoc values
- Keyboard navigation and focus order were exercised on every interactive element introduced
- Reduced-motion / dark-mode (when supported) variants were verified, not assumed to inherit
- No console errors or hydration warnings were emitted during the verification render