Image Prompt Engineer

v1.0.1

Expert photography prompt engineering skill for AI image generation. Use when: generating prompts for Midjourney/DALL-E/Stable Diffusion/Flux, creating produ...

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byTyroneMok@tyronecoh

Install

OpenClaw Prompt Flow

Install with OpenClaw

Best for remote or guided setup. Copy the exact prompt, then paste it into OpenClaw for tyronecoh/image-prompt-engineer-tm.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "Image Prompt Engineer" (tyronecoh/image-prompt-engineer-tm) from ClawHub.
Skill page: https://clawhub.ai/tyronecoh/image-prompt-engineer-tm
Keep the work scoped to this skill only.
After install, inspect the skill metadata and help me finish setup.
Use only the metadata you can verify from ClawHub; do not invent missing requirements.
Ask before making any broader environment changes.

Command Line

CLI Commands

Use the direct CLI path if you want to install manually and keep every step visible.

OpenClaw CLI

Bare skill slug

openclaw skills install image-prompt-engineer-tm

ClawHub CLI

Package manager switcher

npx clawhub@latest install image-prompt-engineer-tm
Security Scan
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high confidence
Purpose & Capability
Name/description match the contents: detailed prompt templates, platform syntax, photography references. No unexpected credentials, binaries, or system access are requested.
Instruction Scope
SKILL.md stays on-topic, describing prompt construction, platform syntax, lighting and film references. One minor vagueness: 'Documentation — Save successful patterns' suggests persisting examples but gives no location or mechanism; this is not inherently malicious but ambiguous about where/how saved data would be stored.
Install Mechanism
No install spec and no code files — instruction-only content. This minimizes on-disk or remote install risk.
Credentials
No environment variables, credentials, or config paths are required. The sensitivity requested is proportional (none) to the skill's purpose.
Persistence & Privilege
Skill is not always-enabled and does not request persistent system privileges or modify other skills. Autonomous invocation remains enabled by platform default (normal).
Assessment
This skill appears internally consistent and low-risk: it only provides prompt templates and photography references and asks for no credentials or installs. Before installing, consider: (1) the 'save successful patterns' note is vague — confirm where/if the agent would persist examples; (2) some model providers restrict 'in the style of [living artist]' prompts — check the image-generation service's content and copyright rules you plan to use; (3) because the skill can be invoked autonomously by default, ensure you are comfortable with the agent using these prompts automatically. If you want extra assurance, run it in a non-production agent or restrict autonomous invocation while you test.

Like a lobster shell, security has layers — review code before you run it.

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215downloads
0stars
1versions
Updated 2w ago
v1.0.1
MIT-0

Image Prompt Engineer 📷

Expert at crafting detailed, structured prompts for AI image generation tools (Midjourney, DALL-E, Stable Diffusion, Flux).

Core Workflow

  1. Concept Intake — Understand visual goal, platform, style, brand requirements
  2. Reference Analysis — Lighting, composition, style elements from references
  3. Prompt Construction — Layer: Subject → Environment → Lighting → Technical → Style
  4. Optimization — Negative prompts, platform-specific syntax, quality enhancers
  5. Documentation — Save successful patterns

Prompt Structure Framework

Layer 1: Subject

- Primary subject (person, object, scene)
- Details: age, ethnicity, expression, attire, textures, materials
- Interaction with environment
- Scale and proportion

Layer 2: Environment

- Location type (studio, outdoor, urban, natural, interior)
- Environmental details (weather, time of day, textures)
- Background treatment (sharp, blurred, gradient, minimalist)
- Atmospheric conditions (fog, rain, haze, clarity)

Layer 3: Lighting

- Light source (golden hour, overcast, softbox, neon, rim light)
- Light direction (front, side, back, Rembrandt, butterfly, split)
- Light quality (hard/soft, diffused, specular, volumetric)
- Color temperature (warm, cool, neutral, mixed)

Layer 4: Technical (Photography Specs)

- Camera perspective (eye-level, low angle, bird's eye, worm's eye)
- Focal length effect (wide angle, telephoto compression, standard)
- Depth of field (shallow for portrait, deep for landscape)
- Exposure style (high key, low key, balanced, HDR, silhouette)

Layer 5: Style

- Photography genre (portrait, fashion, editorial, commercial, documentary, fine art)
- Era/period (vintage, contemporary, retro, futuristic, timeless)
- Post-processing (film emulation, color grading, contrast, grain)
- Reference photographers (Annie Leibovitz, Peter Lindbergh, etc.)

Genre Templates

Portrait

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

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

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

Fashion

[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: static/dynamic] |
[Magazine/campaign aesthetic reference]

Platform Syntax

Midjourney

/imagine prompt: [subject] --ar 16:9 --v 6 --style raw --chaos 5 --seed [n]
--ar     → aspect ratio
--v      → version (5, 6, etc.)
--style  → style mode
--chaos  → variation (0-100)
--seed   → reproducibility
--no     → negative prompt
::       → weighted emphasis

DALL-E

Natural language, conversational
Style mixing: "in the style of [X] mixed with [Y]"
Be specific about what you want

Stable Diffusion

[subject], [details], [lighting], [style]
Negative: [unwanted elements]
(lora:model:weight) → LoRA weighting
[token:weight] → explicit weighting

Flux

Detailed natural language descriptions
Photorealistic emphasis
Less need for photography jargon

Negative Prompts (Midjourney/SD)

--no blurry, low quality, distorted, watermark, text, logo, noisy
(negative weighting where supported)

Photography Terminology (Use Correctly)

❌ Vague✅ Technical
Blurry backgroundShallow depth of field, f/1.8 bokeh
Big pictureWide-angle, 24mm, environmental portrait
Dark shadowsDeep shadows, high contrast, Rembrandt lighting
Nice lightingSoft golden hour, butterfly lighting, rim light
Old lookingFilm grain, Kodak Portra 400, faded contrast

Success Metrics

  • Generated images match concept ≥ 90% first attempt
  • Consistent results across generations
  • Technical elements (lighting, DOF, composition) render accurately
  • Minimal iteration needed
  • Suitable for professional/commercial use

Reference Files

  • references/platform-syntax.md — Platform-specific syntax cheat sheet
  • references/photography-terms.md — Correct photography terminology
  • references/lighting-patterns.md — Lighting setups and effects
  • references/film-emulation.md — Film stock references and looks

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