118 AI Prompts for Frontend & UI

The best Frontend & UI prompts in the Coding library. Tested on ChatGPT, Claude, Gemini and every major model.

Browse the prompts

## Role

You are a UX architect and information designer specializing in e-commerce navigation systems that balance product discoverability, user intuition, and conversion optimization.

## Task

Design a comprehensive navigation menu structure for an e-commerce site. Deliver a strategic framework with visual hierarchy recommendations, labeling conventions, and interaction patterns.

## Context

{{business-context}}

The navigation must:
- Accommodate focused searchers, casual browsers, and comparison shoppers
- Scale with catalog growth while maintaining cognitive simplicity
- Reflect user mental models rather than internal business structure
- Balance SEO requirements with user comprehension
- Prioritize mobile-first constraints where appropriate
- Minimize clicks and decision fatigue to reduce abandonment

## Output

Provide:

### Primary Navigation Architecture
- Optimal navigation d

E-Commerce Navigation Menu Design Prompt

Designs comprehensive navigation menu structures for e-commerce sites that balance product discoverability, user intuition, and conversion optimization. Runs on ChatGPT, Claude, Gemini, and Grok.

37
## Role
You are a UI/UX architect specializing in checkout flow optimization, focusing on conversion psychology and reducing purchase friction.

## Task
Design a multi-step checkout UI flow tailored to the user's business requirements. Before each recommendation, analyze shipping and payment complexity, identify points where users abandon carts, determine where trust signals are needed, structure progressive disclosure, and provide fallback patterns for different user preferences.

## Context
Checkout flows must balance friction reduction with the information collection necessary to complete a transaction. The number of steps, fields per step, and trust elements depend on product type, payment complexity, shipping requirements, audience technical comfort, and conversion goals.

## Input Required
Provide the following about your checkout:

{{checkout-requirements}}

*Include: product type

Multi-Step Checkout UI Design Prompt

Generates a complete checkout flow specification with step-by-step breakdowns, trust signal placement, and progressive disclosure logic. Runs on ChatGPT, Claude, Gemini, and Grok to optimize conversion and reduce cart abandonment.

36

Microinteraction Design Strategy Prompt

Generates a multi-phase guide to designing and implementing UI microinteractions tailored to your product's emotional journey, user touchpoints, and technical constraints. Runs on ChatGPT, Claude, Gemini, and Grok to produce strategic recommendations, code snippets, and implementation roadmaps.

36

Personalization Widget Strategy Builder

Generates comprehensive UX personalization widget strategies for e-commerce platforms, balancing user value with privacy and business goals. Runs on ChatGPT, Claude, Gemini, and Grok.

36

Multi-Step Checkout Flow UI Design Prompt

Generates a phased checkout flow architecture that balances conversion goals with user trust, including progressive disclosure patterns, trust-building placements, and A/B testing strategies. Runs on ChatGPT, Claude, Gemini, and Grok.

34
## Role

You are a senior frontend architect specializing in optimistic UI patterns for high-traffic production applications. Your expertise covers state management, error recovery, synchronization challenges, network failure handling, race conditions, and perceived performance.

## Task

Design a comprehensive, production-ready optimistic UI system for the specified application. Provide detailed implementation strategies covering:

- Immediate UI updates on user actions
- Error handling and rollback mechanisms
- Temporary ID management and server confirmation
- Background synchronization and conflict resolution
- Data consistency between local and server state
- Recommended libraries and tools with implementation guidance
- Production-ready code patterns
- Testing approaches for optimistic behavior and edge cases

## Context

Optimistic UI patterns deliver instant perceived performance 

Optimistic UI Pattern Design Prompt

Generates a production-ready optimistic UI system with immediate updates, error handling, rollback mechanisms, and background sync strategies. Runs on ChatGPT, Claude, Gemini, and Grok for frontend architecture planning.

33
## Role
You are a mobile UX architect specializing in e-commerce navigation patterns. Your approach prioritizes real-world usage behaviors—designing for one-handed interaction during commutes, multitasking, and distracted browsing scenarios.

## Task
Create mobile navigation solutions that reduce cart abandonment and convert browsers into buyers. Analyze the provided context, then design three core navigation patterns optimized for thumb-reach zones, one-handed use, and minimal friction.

## Context
Mobile e-commerce faces 70% cart abandonment rates driven by navigation friction. Desktop-first patterns fail on mobile. Users shop while holding coffee, managing children, or commuting—one-handed usage is non-negotiable. Modern thumb-zone research accounts for evolved phone-holding behaviors across diverse device sizes (iPhone SE to Pro Max) and left/right-handed use.

{{mobile-commerce-cont

Mobile E-Commerce Navigation Design Prompt

Generates thumb-optimized navigation patterns for mobile shopping apps that reduce cart abandonment and improve one-handed usability. Runs on ChatGPT, Claude, Gemini, and Grok.

33

E-Commerce Wishlist Feature Design Prompt

Generates a complete wishlist system design including core functionality, engagement features, conversion pathways, and an implementation roadmap. Runs on ChatGPT, Claude, Gemini, and Grok.

32

Responsive Design Guidelines Generator

Generates structured responsive design guidelines covering breakpoints, grids, typography, accessibility, and performance optimization. Runs on ChatGPT, Claude, Gemini, and Grok to produce implementation-ready technical specifications.

32
## Role

You are a conversion optimization architect specializing in post-purchase experience design. You understand that order confirmation pages are high-intent retention moments where customer lifetime value is determined, and you know how to transform transactional confirmations into relationship-building experiences that drive repeat purchases and referrals.

## Task

Create comprehensive order confirmation page designs optimized for retention and upsell. Deliver multiple layout variations with detailed visual hierarchy, placement rationale, and copy recommendations.

## Context

The post-purchase moment is when customers are most receptive to future engagement. Standard confirmation pages waste this opportunity by being purely informational. Well-designed confirmation experiences balance immediate utility (order details, tracking) with strategic retention elements (loyalty invitati

Post-Purchase Order Confirmation Page UI Prompt

Generates retention-focused order confirmation page layouts that balance essential order details with loyalty invitations, referral prompts, and personalized recommendations. Runs on ChatGPT, Claude, Gemini, and Grok.

31
## Role

You are a UI Systems Architect specializing in component-driven design systems and Atomic Design methodology. You help teams transform scattered UI elements into scalable, maintainable design systems through systematic inventory and organization.

## Task

Guide the user through creating a comprehensive component inventory using Atomic Design principles (atoms → molecules → organisms → templates → pages). Adapt the depth and pace based on their app's complexity, current design maturity, and team needs.

## Context

The user has: {{app-context}}

*Describe your application: number of screens, current design state (inconsistent/partially documented/chaotic), biggest pain points (maintenance/scaling/inconsistency), and 2-3 key screen types or features.*

## Process

Work through these stages iteratively, adjusting scope and detail based on the app's complexity:

**Discovery & Asses

Create Component Inventories

Generates a systematic component inventory using Atomic Design methodology, transforming scattered UI elements into documented design systems. Runs on ChatGPT, Claude, Gemini, and Grok.

30

Zustand Store Builder for React State Management

Generates a production-ready Zustand store with TypeScript, localStorage persistence, modular slices, and authentication patterns. Runs on ChatGPT, Claude, and Cursor for React developers.

28

User Registration Flow Design Prompt

Generates a complete UX registration flow that balances business data needs with user trust and friction reduction. Runs on ChatGPT, Claude, Gemini, and Grok.

25
You are an expert motion graphics developer specializing in recipe explainer animations. Create a polished, production-ready HTML + JavaScript animation that visually demonstrates a recipe from start to finish in exactly 30 seconds.

## Recipe to Animate
{{recipe-details}}

## Technical Requirements
- Use vanilla JavaScript with CSS animations or a lightweight library (GSAP, Anime.js) for smooth motion
- Build a self-contained single HTML file (inline CSS and JS)
- Timeline: 30 seconds total, auto-play on load
- Responsive canvas (scales to viewport)
- No external dependencies beyond a single CDN-hosted animation library if needed

## Animation Structure
1. **Opening (0-3s)**: Empty glass/container fades in with recipe title overlay
2. **Ingredient sequence (3-25s)**: Each ingredient animates in with:
   - Ingredient name label
   - Measurement (oz, ml, count, dashes)
   - Visual pour/ad

Recipe Motion Graphic Explainer Video

Generate a HTML and JavaScript-based 30-second recipe motion graphic explainer video.

12
You are a generative motion designer building Dribbble-level UI morphing animations with pure functional rendering.

# Project Brief

{{ui-states}}

{{accent-color}}

{{song-reference}}

# Design System

**Canvas**: 1440×1440, light warm gray (#F5F3F0)  
**Palette**: Black (#0A0A0A) / White (#FEFEFE) / the accent for semantic highlights only  
**Typography**: Geist Sans, crisp weight hierarchy  
**Motion**: Spring physics (closed-form step response, ζ=0.82, ωₙ=8 rad/s), 4–8% overshoot maximum  
**Easing**: Banned — bouncy curves, elastic, gratuitous ease-out-back  
**Effects**: Banned — particle bursts, glows, gradients on UI chrome, drop shadows, mismatched icon stroke weights  
**Camera**: Zoom so each state fills 70–85% of frame height; transitions on springs  

# Morphing Rules

- **One element, never cut**: every state is the same shape morphing size, border-radius, and color  
- **

Morphing Shape UI States Music Video

Generate a dynamic music-driven UI animation sequence using morphing shape transformations and user-choreographed interactions, complete with code implementation.

8

Immersive Wow-Factor Interactive Experience

Create an immersive, wow-factor interactive experience through code that pushes the boundaries of creativity and technology.

4

Soft Body Gummy Dice WebGPU Simulation

Generate a self-contained WebGPU application simulating soft-body gummy dice with customizable colors and interaction features.

4
You are an expert front-end developer specializing in smooth, production-ready CSS and JavaScript animations. Write clean, performant animation code for the following card entrance effect.

## Card Component to Animate
{{card-structure}}

## Animation Sequence Requirements

**Phase 1: Card Entrance (0–800ms)**
- Card scales from 30% to 100% with an easing curve (ease-out or custom cubic-bezier)
- Opacity transitions from 0 to 1 simultaneously
- Use transform: scale() and opacity for GPU acceleration

**Phase 2: Content Staggered Reveal (starts at 600ms, stagger 80–120ms per element)**
- Card details (heading, subheading, metadata, labels, etc.) slide in sequentially
- Each detail element should translate from an offset position (e.g., translateY(20px) or translateX(-15px)) to its final position
- Apply to elements in visual reading order: top to bottom, left to right

**Phase 3: Graph Li

Card Reveal Staged Animation Spec

Generate smooth, production-ready CSS and JavaScript animation code for a card reveal effect. Produces a complete, framework-agnostic animation spec with CSS, JS, and HTML structure.

4
You are an expert motion designer specializing in premium dark-mode UI animations for developer tools and SaaS products. Create a production-ready After Effects / Lottie animation specification that meets Dribbble's top 1% quality standards.

## Canvas & Foundation
- Background: Pure black (#000000) with a 16px subtle grid overlay (8% white, 0.5px stroke)
- Safe area: 1920×1080, design for 16:9 with 5% edge padding
- Color palette: Monochrome whites/grays (#FFFFFF, #E5E5E5, #999999) with one accent color derived from {{brand-color}}

## Motion Language
- **Tempo**: Strict 120 BPM (0.5s per beat, 2s per phrase)
- **Easing**: Sharp and snappy — use `cubic-bezier(0.34, 1.56, 0.64, 1)` for entrances, `ease-out-expo` for exits
- **Camera**: Quick cuts disguised as motion — whip-pan transitions at 8 frames, snap-zoom on key moments (1.2× scale max)
- **No hard cuts**: Every transition is motio

Dark Mode UI Motion Timeline Spec

Generate a detailed After Effects or Lottie animation specification for high-quality dark-mode UI motion timelines with emphasis on smooth transitions and kinetic typography.

4

Interactive Ocean Platform Rocket Launch

Generates a single-file, interactive 3D rocket launch scene using Three.js, designed for self-contained delivery in Chrome.

4

Procedural Golden Hour Manor Scene

Generate a procedural golden-hour manor scene using WebGL/Canvas with no external models. Produces a browser application with animated elements and detailed lighting transitions.

3

Procedural Physics-Driven Cow In Browser

Generate a fully animated cow using procedural code and real-time physics within a browser environment. Produces a code-based simulation without external assets.

3
You are an elite creative technologist building a viral Three.js demo that showcases cutting-edge WebGL capabilities. Your goal is to create code so visually stunning and technically impressive that it stops scrollers mid-feed and compels them to like and share.

## Context
Demo focus: {{demo-concept}}
Target impression: {{target-vibe}}

## Virality Requirements
Your demo must achieve social media traction through:

**Visual Impact** - Immediate "wow" factor in the first 2 seconds; rich colors, dynamic motion, or mind-bending effects that photograph/screen-record beautifully

**Technical Showcase** - Demonstrate advanced Three.js patterns: custom shaders (GLSL), particle systems (100k+ particles), post-processing (bloom/chromatic aberration/depth-of-field), physics integration, or procedural generation

**Performance** - Smooth 60fps on modern hardware; use instancing, LOD, frustum culli

Viral Three.js Self Demo

Generate a viral Three.js demo showcasing advanced WebGL capabilities with a strong social media impact.

3

What are AI prompts for Frontend & UI?

AI prompts for Frontend & UI are engineered instructions that already work. These are not one-line questions. Each one fixes the role, the context, the task and the output format before you type a word, so you get a usable result on the first run instead of the fourth.

They cover the work Frontend & UI actually get asked for: research and briefs, copy and content, analysis and reporting, planning, outreach and the admin that eats the day. Open a card to see the full prompt and the output it returns.

Popular on this page right now: "E-Commerce Navigation Menu Design Prompt", "Multi-Step Checkout UI Design Prompt", "Microinteraction Design Strategy Prompt".

118 on this page, every one scoped to Frontend & UI. Free to read, free to copy.

Why these prompts work for Frontend & UI

A weak prompt costs you the hour you were trying to save: you rewrite it three times, get something generic, then finish the job by hand. An engineered prompt front-loads that thinking once.

In Frontend & UI that means first drafts you can send, analysis you can act on, and the repetitive work handed off, so the time goes into judgement instead of typing.

Every prompt here was written for a real job and tested against the models people actually use. Nothing scraped from a thread.

How to use these prompts

Open a prompt, copy it, and replace the [bracketed] variables with your own product, audience or topic. The structure around them stays as is. That structure is the part doing the work.

Paste it into ChatGPT, Claude, Gemini, Grok or the model you already use. If the output drifts, tighten the context line instead of rewriting the whole prompt.

No account needed to copy one. No setup, no extension, nothing to install.

Which AI tool works best for Frontend & UI prompts?

Text prompts here run well in ChatGPT, Claude, Gemini and Grok; image prompts target Midjourney and Nano Banana. Each card lists the models it was tested with.

Are these AI prompts free to use?

A big part of the library is free: open a prompt, copy it, use it. Premium packs and the Complete AI Bundle unlock the full collection with lifetime updates.

How do I adapt these prompts to my use case?

Start with the [variables]: niche, audience, constraints. If the result still misses, add one example of the output you want. A single good example beats three extra instructions.

For a prompt built from scratch, the Start Now card above opens the custom prompt generator.

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UI prompts for real components

UI prompts fail when they describe a mood instead of a component. The prompts here name the component, its states, the breakpoints and the library in use, so the output is code you can run, not a screenshot you cannot. A good UI prompt also says what the component must not do: no new dependencies, no inline styles, no placeholder text.

Build a [component] in [React/Vue/Svelte] with [Tailwind/CSS modules]. States: default, hover, focus, disabled, loading, error. Mobile first, breakpoints at 640 and 1024. Accessible: keyboard reachable, visible focus ring, aria labels where needed. No new dependencies. Return the component file only, with a short comment on each prop.

Follow with a second prompt that pastes the output back and asks for the three most likely bugs. The review pass catches most layout breaks before you see them.