image-insight

# Image Insight

## Overview

Analyze uploaded images and return structured JSON profiles containing
composition, color, lighting, subject, and background analysis with
actionable recreation parameters for AI image generation.

## Triggers

- `image-insight` - Primary trigger for image analysis
- "analyze this image" - Natural language trigger
- "extract visual style" - Style extraction request
- "generate image profile" - Profile generation request
- "what's in this image" - Detailed breakdown request

## Workflow

### Step 1: Receive Image

Accept the uploaded image file. Verify it's a valid image format.

### Step 2: Multi-Category Analysis

Analyze across all schema categories:

1. **metadata** - Confidence, image type, purpose
2. **composition** - Rule, layout, focal points, hierarchy
3. **color_profile** - Dominant colors with hex, palette, temperature
4. **lighting** - Type, direction, shadows, highlights
5. **technical_specs** - Medium, style, texture, depth of field
6. **artistic_elements** - Genre, influences, mood, atmosphere
7. **typography** - Fonts, placement (if text present)
8. **subject_analysis** - Expression, hair, hands, positioning
9. **background** - Setting, surfaces, objects catalog
10. **generation_parameters** - Recreation prompts, keywords

### Step 3: Apply Critical Area Rules

For portraits, apply detailed analysis per
[references/critical-areas.md](references/critical-areas.md):

- Hair: exact length, cut style, natural imperfections
- Hands: each hand separately, finger positions, tension
- Background: wall material distinction
  (drywall vs concrete vs brick)
- Lighting: directionality, shadow characteristics

### Step 4: Generate JSON Output

Return structured JSON following [references/json-schema.md](references/json-schema.md).

**Output requirements:**

- Valid JSON only - no markdown, no commentary
- All sections populated with specific values
- Hex codes for colors
- Actionable generation prompts

## Quick Reference

### Color P