Source Code

Image to Prompt

Analyze images and generate detailed, reproduction-quality prompts for AI image generation.

Workflow

Step 1: Category Detection First, classify the image into one of these categories:

portrait — People as main subject (photos, artwork, digital art)
landscape — Natural scenery, cityscapes, architecture, outdoor environments
product — Commercial product photos, merchandise
animal — Animals as main subject
illustration — Diagrams, infographics, UI mockups, technical drawings
other — Images that don't fit above categories

Step 2: Category-Specific Analysis Generate a detailed prompt based on the detected category.

Usage

Basic Analysis

# Analyze an image (auto-detect category)
openclaw message send --image /path/to/image.jpg "Analyze this image and generate a detailed prompt for reproduction"

Specify Output Format

Natural Language (default):

Analyze this image and write a detailed, flowing prompt description (600-1000 words for portraits, 400-600 for others).

Structured JSON:

Analyze this image and output a structured JSON description with all visual elements categorized.

With Dimensions Extraction

Request dimension highlights to get tagged phrases for each visual aspect:

Analyze this image with dimension extraction. Tag phrases for: backgrounds, objects, characters, styles, actions, colors, moods, lighting, compositions, themes.

Category-Specific Elements

Portrait Analysis Covers:

Model/Style: Photography type, quality level, visual style
Subject: Gender, age, ethnicity, skin tone, body type
Facial Features: Eyes, lips, face shape, expression
Hair: Color, length, style, part
Pose: Body position, orientation, leg/hand positions, gaze
Clothing: Type, color, pattern, fit, material, style
Accessories: Jewelry, bags, hats, etc.
Environment: Location, ground, background, atmosphere
Lighting: Type, time of day, shadows, contrast, color temperature
Camera: Angle, height, shot type, lens, depth of field, perspective
Technical: Realism, post-processing, resolution

Landscape Analysis Covers:

Terrain and water features
Sky and atmospheric elements
Foreground/background composition
Natural lighting and atmosphere
Color palette and photography style

Product Analysis Covers:

Product features and materials
Design elements and shape
Staging and background
Studio lighting setup
Commercial photography style

Animal Analysis Covers:

Species identification and markings
Pose and behavior
Expression and character
Habitat and setting
Wildlife/pet photography style

Illustration Analysis Covers:

Diagram type (flowchart, infographic, UI, etc.)
Visual elements (icons, shapes, connectors)
Layout and hierarchy
Design style (flat, isometric, etc.)
Color scheme and meaning

Output Examples

Natural Language Output (Portrait)

{
  "prompt": "A stunning photorealistic portrait of a young woman in her mid-20s with fair porcelain skin and warm pink undertones. She has striking emerald green almond-shaped eyes with long dark lashes, full rose-colored lips curved in a subtle confident smile, and an oval face with high cheekbones..."
}

Structured Output (Portrait)

{
  "structured": {
    "model": "photorealistic",
    "quality": "ultra high",
    "style": "cinematic natural light photography",
    "subject": {
      "identity": "young beautiful woman",
      "gender": "female",
      "age": "mid 20s",
      "ethnicity": "European",
      "skin_tone": "fair porcelain with pink undertones",
      "body_type": "slim athletic",
      "facial_features": {
        "eyes": "emerald green, almond-shaped, intense gaze",
        "lips": "full, rose pink, subtle smile",
        "face_shape": "oval with high cheekbones",
        "expression": "confident and serene"
      },
      "hair": {
        "color": "warm honey blonde",
        "length": "long",
        "style": "soft waves",
        "part": "center"
      }
    },
    "pose": {
      "position": "standing",
      "body_orientation": "three-quarter turn to camera",
      "legs": "weight on right leg, relaxed stance",
      "hands": {
        "right_hand": "resting on hip",
        "left_hand": "hanging naturally at side"
      },
      "gaze": "direct eye contact with camera"
    },
    "clothing": {
      "type": "flowing maxi dress",
      "color": "dusty rose",
      "pattern": "solid",
      "details": "V-neckline, cinched waist, silk material",
      "style": "romantic feminine"
    },
    "accessories": ["delicate gold necklace", "small hoop earrings"],
    "environment": {
      "location": "outdoor garden",
      "ground": "cobblestone path",
      "background": "blooming roses, soft bokeh",
      "atmosphere": "dreamy and romantic"
    },
    "lighting": {
      "type": "natural sunlight",
      "time": "golden hour",
      "shadow_quality": "soft diffused shadows",
      "contrast": "medium",
      "color_temperature": "warm"
    },
    "camera": {
      "angle": "slightly below eye level",
      "camera_height": "chest height",
      "shot_type": "medium shot",
      "lens": "85mm",
      "depth_of_field": "shallow",
      "perspective": "slight compression, flattering"
    },
    "mood": "romantic, confident, ethereal",
    "realism": "highly photorealistic",
    "post_processing": "soft color grading, subtle glow",
    "resolution": "8k"
  }
}

With Dimensions

{
  "prompt": "...",
  "dimensions": {
    "backgrounds": ["outdoor garden", "blooming roses", "soft bokeh"],
    "objects": ["delicate gold necklace", "small hoop earrings"],
    "characters": ["young beautiful woman", "mid 20s", "European"],
    "styles": ["photorealistic", "cinematic natural light photography"],
    "actions": ["standing", "three-quarter turn", "direct eye contact"],
    "colors": ["dusty rose", "honey blonde", "emerald green"],
    "moods": ["romantic", "confident", "ethereal", "dreamy"],
    "lighting": ["golden hour", "natural sunlight", "soft diffused shadows"],
    "compositions": ["medium shot", "85mm", "shallow depth of field"],
    "themes": ["romantic feminine", "portrait photography"]
  }
}

Tips for Best Results

High-resolution images produce more detailed prompts
Clear, well-lit images yield better category detection
Request structured output when you need programmatic access to individual elements
Use dimensions extraction when building prompt databases or training data
Specify word count expectations for natural language output if needed

Integration

This skill works with any vision-capable model. For best results, use:

GPT-4 Vision
Claude 3 (Opus/Sonnet)
Gemini Pro Vision

image2prompt