HomeFrameworks3D Hair & Beauty Commerce
EnterpriseFeaturedNewv1.0L5 Semantic FrameworkUpdated July 2026

3D Hair & Beauty Commerce

Real-time 3D hair color preview, texture configurator, and AR try-on for beauty ecommerce

4.9(214 reviews)3.4K installs52 prompts6 stages3D / Web3D
GPT-4Claude

The 3D Hair & Beauty Commerce framework is the definitive AI prompt system for beauty brands, hair care retailers, and salon platforms building the next generation of online shopping experiences. Hair color is the single highest-return-rate product category in beauty ecommerce — because customers cannot visualize the result before buying. This framework solves that with a complete technical stack: a real-time HSL-shift hair color shader that previews any shade instantly on a 3D head model, morph-target blending between hair texture styles, WebXR AR try-on that anchors the preview to the customer's own face, and a shade-matching system that reads the customer's current hair color from their camera and recommends the closest product. Every prompt is engineered for beauty ecommerce conversion — not just visual novelty.

Full Access Unlocked

All 52 prompts · All 6 modules

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Secure checkout via Stripe
Lifetime updates (currently v1.0)
Instant delivery after purchase

"The HSL hair color shader prompt produced a result that our in-house team had been trying to build f..."

Head of Digital · Top-5 global hair care brand

Need expert implementation?

Hire an Orchestrator

Connect with a certified Prompt.Doctor Orchestrator to deploy this framework for you.

How to use this framework

No coding required. You will use ChatGPT or Claude as your AI tool. Follow these steps in order — do not skip ahead.

1

Purchase & download the framework

Click the buy button on this page. After checkout, go to the and hit Download .zip. Unzip it — you'll get a .md file (the full framework) and a .pdf (easy to read reference). Keep both open.

2

Open your project — new or existing

This dashboard is designed to integrate into any existing project or be built as a standalone app. If you already have a site in Airo (or Cursor, Bolt, etc.), open that project. If you're starting fresh, create a new project. The Orchestrator Prompt handles both cases — it scans what's already there and adds only what's missing.

3

Paste the Orchestrator Prompt into your builder's chat

Open the on this page. Copy the Orchestrator Prompt and paste it into your AI builder's chat. It will scaffold the full admin system — secure login, email marketing module, booking engine, and CMS — on top of your existing codebase. This takes 2–5 minutes.

4

Add your API keys as secrets

Critical — Novice Users

In your builder, go to Settings → Secrets and add the keys your app needs. For this framework: STRIPE_SECRET_KEY (for booking payments — get it from your Stripe dashboard), ANTHROPIC_API_KEY (for AI-assisted content — get it from console.anthropic.com), and DATABASE_URL (your MySQL connection string). No key is needed for the admin login, CMS, or email modules — those run on your existing infrastructure.

Don't have a MySQL server?

You can purchase a shared hosting plan with cPanel and MySQL at host.esgwon.dev. Once your account is set up, follow the step-by-step guide to create your database and connect it to your AI website builder.

How to set up cPanel MySQL & connect to your AI website →

Need help with Stripe?

Get your STRIPE_SECRET_KEY and STRIPE_PUBLISHABLE_KEY from your Stripe dashboard. The guide covers test keys, webhook setup, and going live.

Stripe API keys — setup & testing guide →

Need help with Anthropic?

Get your ANTHROPIC_API_KEY from console.anthropic.com. The guide covers model selection, cost management, and troubleshooting.

Anthropic API key — setup & model guide →

Prompting Airo after setup — always name the file

When asking Airo to add tables, columns, or features to the admin dashboard, always include src/server/lib/admin-db.ts in your prompt. Without it, Airo may target the wrong database. Example: "Add a bookings table in the admin database (src/server/lib/admin-db.ts) — do not touch any other database connection in this project."

See safe prompting examples →
5

Run the framework prompts inside your live app

Your app is now running in the builder's preview panel. Open the on this page, copy each prompt one at a time, and paste it into your builder's chat. Replace every [BRACKET] with your real data before sending. Work through the stages in order — each stage output feeds the next.

6

Test end-to-end, then publish or hand off to your client

Walk through the admin as a real user: log in, create a booking, send a test email campaign, update a CMS image, and run the Safe-to-Publish gate. Once everything passes, click Publish in your builder. Because this is a white-label dashboard, your client accesses it at /admin on their own domain — no Prompt.Doctor branding, no third-party login required.

Who is this for?

Hair care brands building 3D product pages to reduce color purchase returns
Beauty ecommerce platforms adding virtual try-on to differentiate from competitors
Salon booking platforms letting clients preview color results before appointments
DTC beauty startups building immersive product discovery as a brand differentiator

Everything you get

52 production-ready prompts across 6 beauty commerce areas
Real-time hair color HSL-shift shader previewing 200+ shades on a 3D head model
Morph-target hair texture blending: straight, wavy, curly, coily transitions
WebXR AR try-on with face mesh anchoring for mobile camera preview
Shade matching system: camera → dominant color detection → product recommendation
Product packaging 3D viewer with label texture swap and 360° orbit
Complete ecommerce integration: shade + style → SKU → cart

What's Inside

6 modules · 52 prompts · 6 workflow stages

Modules(6 total)

Head Model & Hair Mesh

GLTF head model loading with separate hair mesh, UV mapping for color shader, LOD for mobile, and hair mesh morph targets for style variants

9 prompts

Real-Time Color Shader

Custom GLSL HSL-shift ShaderMaterial for hair color preview, 200+ shade swatch system, highlight and lowlight layer blending, and root-to-tip gradient mapping

10 prompts

Texture & Style Configurator

Morph target blending between straight/wavy/curly/coily hair geometries, length slider via vertex shader Y-scale, and volume/density parameter

9 prompts

AR Try-On System

WebXR Face Tracking session setup, face mesh landmark anchoring, MediaPipe FaceMesh fallback for non-WebXR browsers, and head model alignment to face pose

10 prompts

Shade Matching AI

getUserMedia camera stream, canvas pixel sampling for dominant hair color, LAB color space distance to product shade library, and top-3 recommendation display

8 prompts

Product Viewer & Commerce

3D product packaging viewer with label texture swap, 360° auto-rotate, shade-to-SKU mapping table, dynamic pricing, and add-to-cart with configuration payload

6 prompts
Sample Prompts(52 total)
Real-Time Hair Color HSL Shader·GPT-4

Write a React Three Fiber component that applies a real-time hair color preview shader to a 3D hair mesh using a custom GLSL ShaderMaterial. Requirements: (1) The hair mesh is a GLTF model with a UV-mapped texture (the base hair texture provides strand detail and specularity). (2) ShaderMaterial uniforms: u_baseTexture (sampler2D — the original hair texture), u_targetHue (float, 0.0–1.0), u_targetSaturation (float, 0.0–1.0), u_targetLightness (float, 0.0–1.0), u_colorIntensity (float, 0.0–1.0 — blend between original and target color), u_highlightHue (float), u_highlightMask (sampler2D — grayscale texture defining highlight placement), u_rootDarkness (float, 0.0–1.0 — how dark the roots are relative to lengths). (3) Fragment shader: (a) Provide complete RGB↔HSL conversion functions in GLSL. (b) Sample u_baseTexture — extract its luminance to preserve strand detail. (c) Convert u_targetHue/Saturation/Lightness to RGB. (d) Apply u_rootDarkness: darken the color based on UV.y (roots at top, tips at bottom — adjust lightness by mix(targetL * (1.0 - u_rootDarkness), targetL, uv.y)). (e) Blend highlight color at u_highlightMask regions. (f) Multiply final color by original luminance to preserve strand shading. (g) mix() between original texture color and computed color by u_colorIntensity. (4) React component: HairColorPreview with props shadeHex: string (convert to HSL for uniforms), highlightHex: string, rootDarkness: number, colorIntensity: number. Update uniforms reactively on prop change. (5) Outside Canvas: a shade swatch grid component showing 24 color options, clicking one updates shadeHex. Full TypeScript.

Shade Matching from Camera·Claude

Write a TypeScript module that analyzes a user's hair color from their webcam and recommends the closest products from a shade library. Requirements: (1) captureHairSample(): request getUserMedia({ video: { facingMode: "user" } }), draw a single frame to a hidden canvas, sample a 40x40 pixel region in the upper-center of the frame (where hair typically appears), compute the average RGB of all pixels. (2) rgbToLab(r, g, b): implement the full sRGB → XYZ → CIELAB conversion in TypeScript (provide the complete math — D65 illuminant, gamma correction, XYZ matrix). (3) deltaE(lab1, lab2): implement CIE76 color difference formula: sqrt((L1-L2)^2 + (a1-a2)^2 + (b1-b2)^2). (4) Shade library: define a ShadeLibrary type: Array<{ id: string, name: string, hex: string, skuId: string, level: 1|2|3|4|5|6|7|8|9|10 }>. Convert each shade hex to LAB on initialization. (5) findClosestShades(sampledRgb, library, topN = 3): convert sampled RGB to LAB, compute deltaE against all library shades, return top N sorted by ascending deltaE with their deltaE scores. (6) React component: ShadeMatcher — shows a "Scan My Hair Color" button, activates camera, captures sample, displays top 3 recommended shades with product names, swatch colors, and "Add to Cart" buttons. Handle camera permission denial gracefully. Full TypeScript.

Workflow Architecture(6 stages)

system

19 prompts

Stage 1

templates

10 prompts

Stage 2

workflow

15 prompts

Stage 3

prompts

8 prompts

Stage 4

Everything included

GLTF head model with hair mesh: UV-mapped hair geometry with strand-level detail
Real-time hair color system: HSL shift shader for instant color preview across 200+ shades
Hair texture configurator: straight, wavy, curly, coily — morph target blending between styles
Product packaging 3D viewer: GLTF bottle/jar models with label texture swap
WebXR AR try-on: face mesh anchoring via WebXR Face Tracking or MediaPipe FaceMesh
Shade matching AI: camera input → dominant hair color detection → closest product recommendation
Ecommerce cart integration: selected shade + style → SKU lookup + add-to-cart
Full Access Unlocked

What builders say

"The HSL hair color shader prompt produced a result that our in-house team had been trying to build for 6 months. The root-to-tip gradient, the highlight mask layer, the luminance preservation for strand detail — it's the complete system, not a toy demo."

Ho

Head of Digital

Top-5 global hair care brand

"The CIELAB shade matching system is the feature that reduced our hair color return rate by 34%. The deltaE color distance math — converting camera pixels to LAB space and finding the closest product shade — is exactly the right algorithm for this problem."

C

CTO

Beauty ecommerce platform, $28M ARR

You have full access

All 52 prompts across 6 modules are unlocked for your account.

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