ADHD-Closet

Clothing Item Attributes Reference

Complete guide to all attributes tracked for clothing items in the ADHD-Closet application.

Overview

The ADHD-Closet tracks rich metadata about each clothing item:

Smart AI recommendations for outfit matching
Precise filtering to find specific items
Visual balance for harmonious outfits
ADHD-friendly organization to reduce decision paralysis

Core Attributes (All Items)

These fields apply to every item in your wardrobe:

Basic Information

Field	Type	Description	Example
title	String	Optional name/description	“Black band t-shirt”
category	Enum	Main category	`tops`, `bottoms`, `dresses`, etc.
brand	String	Brand/manufacturer	“H&M”, “Target”, “Handmade”
sizeText	String	Size information	“M”, “32x30”, “One Size”
materials	String	Fabric composition	“100% cotton”, “Polyester blend”

Licensed Merchandise & Band Merch

Field	Type	Description	Example
isLicensedMerch	Boolean	Is this official licensed merchandise?	`true`, `false`, `null`
franchise	String	Band name, movie, game, show, etc.	“My Chemical Romance”, “Star Wars”, “The Legend of Zelda”
franchiseType	Enum	Type of franchise	`band`, `movie`, `tv_show`, `game`, `anime`, `comic`, `sports`, `brand`, `other`

Franchise Types:

band - Music groups/artists (My Chemical Romance, Metallica, BTS)
movie - Films (Star Wars, Marvel, Harry Potter)
tv_show - TV series (Stranger Things, The Mandalorian, Friends)
game - Video games (The Legend of Zelda, Minecraft, Pokemon)
anime - Anime series (Naruto, Attack on Titan, Sailor Moon)
comic - Comic books/graphic novels (Marvel, DC, manga)
sports - Sports teams (Manchester United, Lakers, Yankees)
brand - Fashion/lifestyle brands with prominent branding (Supreme, Nike, Adidas)
other - Other licensed content

Examples:

Band t-shirt with Slipknot logo: isLicensedMerch: true, franchise: "Slipknot", franchiseType: "band"
Hoodie with Baby Yoda: isLicensedMerch: true, franchise: "The Mandalorian", franchiseType: "tv_show"
Shirt with Mario graphics: isLicensedMerch: true, franchise: "Super Mario Bros", franchiseType: "game"
Plain black t-shirt: isLicensedMerch: false, franchise: null, franchiseType: null

Visual Characteristics

Field	Type	Description	Example
colors	Array	Named colors	`["black", "dark purple"]`
colorPalette	Array	Hex color codes	`["#000000", "#4B0082"]`
pattern	String	Pattern description	“solid”, “striped”, “floral”, “graphic print”
tags	Array	Style tags	`["emo", "goth", "casual", "edgy"]`

Metadata

Field	Type	Description	Example
fitNotes	String	How item fits	“Oversized fit creates volume contrast”
pairingTips	Array	Styling suggestions	`["Pairs well with high-waisted bottoms"]`
confidence	Object	AI confidence scores	`{ "category": 0.95, "colors": 0.88 }`

Wear & Care Tracking

Field	Type	Description
state	Enum	`available`, `laundry`, `unavailable`, `donate`
cleanStatus	Enum	`clean`, `dirty`, `needs_wash`
wearsBeforeWash	Int	Wears before washing needed
currentWears	Int	Current wear count since last wash
lastWornDate	DateTime	When item was last worn
lastWashedDate	DateTime	When item was last washed

Physical Storage

Field	Type	Description	Example
storageType	Enum	Storage method	`hanging`, `folded`, `drawer`, `shelf`
locationInCloset	String	Where stored	“Left side”, “Top drawer”
sortOrder	Int	Custom ordering	For organizing display

Category-Specific Attributes

These attributes are stored in the attributes JSON field and vary by category.

Tops

Attribute	Values	Description
neckline	crew, v-neck, scoop, boat, square, halter, off-shoulder, turtleneck	Neckline style
sleeveLength	sleeveless, short, 3/4, long	Length of sleeves
sleeveFit	fitted, loose, puff, bell	How sleeves fit
visualWeight	minimal, moderate, heavy, complex	Visual heaviness
silhouette	fitted, loose, oversized, boxy	Overall shape

Example:

{
  "neckline": "v-neck",
  "sleeveLength": "short",
  "sleeveFit": "fitted",
  "visualWeight": "minimal",
  "silhouette": "fitted"
}

Bottoms

Attribute	Values	Description
bottomsType	jeans, dress_pants, casual_pants, cargo_pants, shorts, skirt, leggings, joggers	Type of bottom (stored separately)
rise	low, mid, high	Waist height
inseam	Number	Length in inches
fit	skinny, slim, straight, wide, bootcut, flare	How bottom fits legs
hemline	raw, cuffed, distressed	Bottom edge style
visualWeight	minimal, moderate, heavy	Visual heaviness
pocketStyle	String	Description of pockets

Example:

{
  "rise": "high",
  "inseam": 30,
  "fit": "skinny",
  "hemline": "raw",
  "visualWeight": "moderate",
  "pocketStyle": "5-pocket jean style"
}

Note: High rise skinny jeans = bottomsType: "jeans" + rise: "high" + fit: "skinny"

Dresses

Attribute	Values	Description
neckline	crew, v-neck, scoop, boat, square, halter, off-shoulder, turtleneck	Neckline style
sleeveLength	sleeveless, short, 3/4, long	Length of sleeves
waistline	natural, empire, dropped, none	Where waist sits
hemline	mini, knee, midi, maxi, asymmetric	Dress length
silhouette	fitted, A-line, shift, bodycon, flowy	Overall shape

Example:

{
  "neckline": "scoop",
  "sleeveLength": "sleeveless",
  "waistline": "empire",
  "hemline": "midi",
  "silhouette": "A-line"
}

Outerwear

Attribute	Values	Description
silhouette	fitted, loose, oversized, boxy	Overall shape
length	cropped, hip, mid-thigh, knee, long	How long jacket is
visualWeight	minimal, moderate, heavy, complex	Visual heaviness

Example:

{
  "silhouette": "oversized",
  "length": "hip",
  "visualWeight": "heavy"
}

Shoes

Attribute	Values	Description
shoeType	sneakers, boots, sandals, heels, flats, loafers, oxfords, platforms	Type of shoe (stored separately)
heelHeight	Number	Height in inches
heelThickness	none, slim, chunky, wedge	Heel style
toeboxShape	rounded, almond, pointed, square	Toe shape
visualWeight	minimal, moderate, heavy	Visual heaviness

Example:

{
  "heelHeight": 3,
  "heelThickness": "chunky",
  "toeboxShape": "rounded",
  "visualWeight": "heavy"
}

Accessories

Attribute	Values	Description
accessoryType	purse, bag, backpack, belt, hat, scarf, gloves, sunglasses, watch	Type (stored separately)
size	small, medium, large	Overall size
material	String	What it’s made of
structure	structured, unstructured, semi-structured	How stiff/floppy
visualWeight	minimal, moderate, heavy	Visual heaviness
occasion	casual, formal, both	When to wear

Example:

{
  "size": "medium",
  "material": "leather",
  "structure": "structured",
  "visualWeight": "moderate",
  "occasion": "both"
}

Jewelry

Attribute	Values	Description
jewelryType	necklace, earrings, bracelet, ring, anklet, brooch	Type (stored separately)
metal	gold, silver, rose gold, bronze, mixed, none	Metal type
gemstones	yes, no	Has gemstones?
style	delicate, statement, chunky, minimalist	Overall style
occasion	everyday, formal, special	When to wear

Example:

{
  "metal": "silver",
  "gemstones": "no",
  "style": "statement",
  "occasion": "everyday"
}

Swimwear

Attribute	Values	Description
style	one-piece, two-piece, bikini, tankini, boardshorts, rash-guard	Swimwear style
coverage	minimal, moderate, full	How much covered
activity	swimming, surfing, beach, pool	Intended activity

Example:

{
  "style": "two-piece",
  "coverage": "moderate",
  "activity": "beach"
}

Activewear

Attribute	Values	Description
activityType	gym, running, yoga, cycling, sports	Intended activity
fit	compression, fitted, loose	How tight
moisture-wicking	yes, no	Wicks sweat?
visualWeight	minimal, moderate	Visual heaviness

Example:

{
  "activityType": "yoga",
  "fit": "fitted",
  "moisture-wicking": "yes",
  "visualWeight": "minimal"
}

Sleepwear

Attribute	Values	Description
style	pajamas, nightgown, robe, sleep-shirt, shorts-set	Sleepwear style
warmth	light, medium, heavy	How warm
season	summer, winter, all-season	Best season

Example:

{
  "style": "pajamas",
  "warmth": "medium",
  "season": "all-season"
}

Loungewear

Attribute	Values	Description
comfort-level	ultra-comfy, relaxed, presentable	Comfort rating
style	sweats, joggers, lounge-set, casual	Style type
occasion	home-only, casual-outing	Where to wear

Example:

{
  "comfort-level": "ultra-comfy",
  "style": "sweats",
  "occasion": "home-only"
}

Suits & Sets

Attribute	Values	Description
type	two-piece, three-piece, co-ord, matching-set	Set type
formality	casual, business-casual, formal	Formality level
completeness	complete-set, mix-and-match	Can pieces separate?

Example:

{
  "type": "two-piece",
  "formality": "business-casual",
  "completeness": "mix-and-match"
}

Visual Weight Explained

Visual weight describes how much visual “presence” an item has in an outfit.

Level	Description	Examples
Minimal	Light, airy, barely there	Simple tank top, thin jewelry, minimalist shoes
Moderate	Balanced presence	Basic t-shirt, regular jeans, simple accessories
Heavy	Strong visual impact	Chunky sweater, platform boots, large bag
Complex	Very busy/detailed	Heavily patterned top, intricate jewelry

Why it matters:

Balance heavy pieces with minimal pieces
Avoid all-heavy or all-minimal outfits
Create intentional focus points

Common Attribute Combinations

High-Waisted Skinny Jeans

{
  "category": "bottoms",
  "bottomsType": "jeans",
  "attributes": {
    "rise": "high",
    "fit": "skinny",
    "visualWeight": "moderate"
  }
}

Oversized Band T-Shirt

{
  "category": "tops",
  "attributes": {
    "neckline": "crew",
    "sleeveLength": "short",
    "sleeveFit": "loose",
    "silhouette": "oversized",
    "visualWeight": "moderate"
  }
}

Statement Chunky Platform Boots

{
  "category": "shoes",
  "shoeType": "platforms",
  "attributes": {
    "heelHeight": 3,
    "heelThickness": "chunky",
    "toeboxShape": "rounded",
    "visualWeight": "heavy"
  }
}

How Attributes Are Used

AI Outfit Generation

The AI uses attributes to create balanced, cohesive outfits:

User: "Generate an outfit"

AI analyzes:
- Visual weight balance (heavy + minimal = good)
- Color harmony (complementary colors)
- Formality matching (casual with casual)
- Season appropriateness (heavy coat in winter)
- Style consistency (tags overlap)

Result: Balanced, wearable outfit

Smart Filtering

Filter by specific attributes:

// Find all high-rise skinny jeans
items.filter(item => 
  item.category === 'bottoms' &&
  item.bottomsType === 'jeans' &&
  item.attributes.rise === 'high' &&
  item.attributes.fit === 'skinny'
)

// Find statement jewelry
items.filter(item =>
  item.category === 'jewelry' &&
  item.attributes.style === 'statement'
)

Pairing Recommendations

Attributes drive smart pairing suggestions:

High rise + Crop top = “Pairs well together”
Heavy boots + Flowy dress = “Creates nice contrast”
Statement necklace + Crew neck = “Shows off necklace”

Database Schema

Attributes are stored in two ways:

1. Separate Enum Fields (Sub-Types)

model Item {
  accessoryType AccessoryType? // purse, bag, etc.
  jewelryType   JewelryType?   // necklace, earrings, etc.
  shoeType      ShoeType?      // sneakers, boots, etc.
  bottomsType   BottomsType?   // jeans, dress_pants, etc.
}

2. JSON Attributes Field

model Item {
  attributes Json? // { "neckline": "v-neck", "rise": "high", ... }
}

Why two approaches?

Sub-types = Primary categorization (filterable, indexed)
Attributes = Detailed characteristics (flexible, extensible)

API Examples

Get Item with Attributes

const item = await prisma.item.findUnique({
  where: { id: itemId },
  select: {
    id: true,
    category: true,
    bottomsType: true,
    attributes: true,
    colors: true,
    tags: true
  }
});

// Access attributes
console.log(item.attributes.rise); // "high"
console.log(item.attributes.fit);  // "skinny"

Query by Attributes

// Find all high-rise bottoms
const highRiseItems = await prisma.item.findMany({
  where: {
    category: 'bottoms',
    attributes: {
      path: ['rise'],
      equals: 'high'
    }
  }
});

Update Attributes

await prisma.item.update({
  where: { id: itemId },
  data: {
    attributes: {
      rise: 'high',
      fit: 'skinny',
      visualWeight: 'moderate',
      hemline: 'raw'
    }
  }
});

AI Inference

Attributes are automatically detected from photos using AI:

// AI analyzes clothing photo
const result = await inferItemDetails(photoBase64);

// Returns:
{
  "category": "bottoms",
  "subType": "jeans",
  "colors": ["black"],
  "colorPalette": ["#1a1a1a"],
  "pattern": "solid",
  "attributes": {
    "rise": "high",
    "fit": "skinny",
    "visualWeight": "moderate",
    "hemline": "raw"
  },
  "fitNotes": "High-rise creates flattering silhouette",
  "pairingTips": [
    "Pairs well with crop tops",
    "Works with tucked-in shirts"
  ],
  "tags": ["casual", "versatile"],
  "confidence": {
    "category": 0.95,
    "attributes": 0.88
  }
}

The AI considers:

Visual appearance
Common fashion terminology
Style conventions
Practical wearability

ADHD-Friendly Design

Attributes support ADHD-friendly features:

Reduced Decision Paralysis

Pre-filtered suggestions based on attributes
“Top picks” use attribute matching
Progressive disclosure (show key attributes first)

Visual Clarity

Visual weight indicators
Color compatibility badges
Clear attribute labels

Quick Actions

Filter by common attributes (high-rise, oversized, etc.)
One-tap outfit generation using attribute intelligence
“Find similar” based on attributes

Learning System

Tracks which attribute combinations you choose
Learns your style preferences
Personalizes suggestions

Common Questions

Q: Can I edit attributes manually?

A: Yes! While AI infers attributes automatically, you can always edit them in the item detail view.

Q: What if an attribute doesn’t fit my item?

A: Use the closest match or leave blank. The system is flexible.

Q: Do I need to fill out all attributes?

A: No! Core attributes (category, colors) are most important. Others enhance recommendations but are optional.

Q: Can I add custom attributes?

A: The attributes JSON field is extensible. You can add custom key-value pairs.

Q: How accurate is AI attribute detection?

A: Typically 85-95% accurate. Review and adjust as needed.

Summary

Total Attributes Tracked

Category	Attributes
Core	10+ fields (title, brand, colors, pattern, etc.)
Tops	5 attributes
Bottoms	7 attributes
Dresses	5 attributes
Outerwear	3 attributes
Shoes	5 attributes
Accessories	6 attributes
Jewelry	5 attributes
Swimwear	3 attributes
Activewear	4 attributes
Sleepwear	3 attributes
Loungewear	3 attributes
Suits & Sets	3 attributes

Total: 60+ attributes across all categories

Key Benefits

Smarter outfit generation - AI matches items intelligently
Better organization - Find exactly what you need
Visual balance - Create harmonious looks
ADHD-friendly - Reduced decision-making burden
Learning system - Gets better over time

Last Updated: 2026-01-31
Version: 1.0 (Complete Attributes Reference)

Quick Reference Tables

Tops Attributes

Attribute	Options
Neckline	crew, v-neck, scoop, boat, square, halter, off-shoulder, turtleneck, cowl, mock, polo
Sleeve Length	sleeveless, short, 3/4, long
Sleeve Fit	fitted, loose, puff, bell, cap, dolman, raglan
Silhouette	fitted, loose, oversized, boxy, cropped, longline, tunic, peplum

Bottoms Attributes

Attribute	Options
Rise	high, mid, low, ultra-high, ultra-low
Inseam	short (< 27”), regular (27-32”), long (32”+), extra-long (34”+)
Leg Shape	skinny, straight, bootcut, flare, wide-leg, tapered, jogger
Waistband	elastic, drawstring, button/zip, pull-on, belted

Shoes Attributes

Attribute	Options
Heel Height	flat (0-1”), low (1-2”), mid (2-3”), high (3-4”), stiletto (4”+)
Toe Shape	round, pointed, square, almond, open
Closure	lace-up, slip-on, buckle, zipper, velcro

Universal Attributes

Attribute	Options
Visual Weight	minimal, moderate, heavy, complex
Pattern	solid, striped, plaid, floral, graphic, abstract, animal, polka-dot, paisley
Material	cotton, polyester, wool, silk, denim, leather, synthetic, blend, linen, cashmere
Fit	tight, fitted, regular, loose, oversized

Quick lookup complete! For detailed descriptions, see sections above.