prompt-ui-design
Guides an LLM to ask 5 clarifying questions before generating a complete UI design system with brand story, visual identity, voice, UX principles, and implementation guidelines.
What this file does
Guides an LLM to ask 5 clarifying questions before generating a complete UI design system with brand story, visual identity, voice, UX principles, and implementation guidelines.
When to use it
- Starting a new UI design system from scratch
- Rebranding an existing product with a fresh visual identity
- Creating a design system for a client project with specific brand requirements
- Standardizing design decisions across a team or organization
<clarification_questions>
-
Project Type & Industry: What type of application/website are you building and what industry does it serve? (e.g., fitness app, e-commerce, SaaS dashboard, portfolio site, etc.)
-
Target Audience: Who is your primary target audience? Please describe their demographics, technical proficiency, and main goals when using your product.
-
Brand Personality: How would you describe your brand's personality in 3-5 adjectives? (e.g., professional, playful, minimal, bold, trustworthy, innovative, etc.)
-
Visual Inspiration: Do you have any design references, color preferences, or visual styles that inspire you? (Describe existing apps/sites you admire or specific aesthetic directions)
-
Core Functionality: What are the 3 most important user actions or features your interface needs to support? (This helps prioritize the design hierarchy) </clarification_questions>
Once you have these answers, create a complete 'ui-design' cursor rule file that includes:
- Brand Story Analysis: Extract and articulate the core purpose, target audience, and unique value proposition
- Visual Identity System: Define comprehensive color palettes with hex codes, typography hierarchy, and visual elements
- Brand Voice Guidelines: Establish personality traits, tone guidelines, and messaging pillars with specific language examples
- User Experience Principles: Create design philosophy and interaction guidelines
- Implementation Guidelines: Provide practical application instructions for marketing and development
<output_format> Structure your response as a complete cursor rule file named 'ui-design' with the following sections:
- Core Brand Elements (Story, Visual Identity with colors/typography/visual elements)
- Brand Voice and Messaging (Personality, Tone, Key Pillars, Language Examples)
- User Experience Principles (Design Philosophy, Interaction Guidelines, Content Hierarchy)
- Application Guidelines (Development, Marketing, Content Creation) </output_format>
<technical_requirements>
- Always name the cursor rule file 'ui-design'
- Use Yarn for any package management references (never npm)
- Include specific hex color codes for all colors
- Provide concrete examples for do's and don'ts
- Structure content with clear headings and subheadings
- Include practical implementation details for developers </technical_requirements>
<quality_standards>
- Ensure consistency across all design elements
- Create scalable guidelines that work across different screen sizes
- Include accessibility considerations
- Provide measurable criteria for design decisions
- Balance creativity with usability </quality_standards> </instructions>
What's inside
5 clarification questions, 5 design system sections, output format, technical requirements, quality standards, and workflow steps
Change this for your project
- Replace
dnielgonzlz/Cursor-Ruleswith your own repository name - Replace
Yarnwith your preferred package manager if not using Yarn - Replace
Cursor IDEwith your target development environment if different
Where it goes
Keep in docs/ or alongside the feature. Agents read it to implement against a defined contract.
Worth borrowing
- Asking clarifying questions before generating output ensures the result is tailored to the user's needs
- Structuring a design system around brand story, visual identity, voice, UX principles, and implementation creates a complete and actionable guide
Related Documents
Community AI Agent Skills Discovery Sources
Catalogs 50+ platforms, repositories, directories, and communities for discovering and sharing AI agent skills across multiple coding tools.
GPU Selection Guide for Large Language Models (LLMs)
Guides GPU selection for LLM inference, fine-tuning, and training by mapping model sizes, precision levels, and budgets to VRAM requirements.
ReleaseKit - Technical Requirements Document
Specifies a Go library and CLI for release automation with conventional commit parsing, validation checks, and workflow orchestration.
Python Development Environment Setup with Ruff
Defines a complete Python development environment using Ruff for linting and formatting, with pytest, mypy, pre-commit hooks, and VSCode configuration.