Agent skill

Prompt Engineering UI

by HermeticOrmus in HermeticOrmus/LibreUIUX-Claude-Code

Prompt patterns for consistent UI generation: stating design intent precisely, component specification formats, few-shot examples, and structured refinement loops.

MITAuto-check passedAI & LLM Engineering

Install Prompt Engineering UI

skills CLI
$ npx skills add HermeticOrmus/LibreUIUX-Claude-Code --skill prompt-engineering-ui -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install HermeticOrmus/LibreUIUX-Claude-Code prompt-engineering-ui --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/HermeticOrmus/LibreUIUX-Claude-Code.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/llm-application-dev/skills/prompt-engineering-ui .claude/skills/prompt-engineering-ui && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
prompt-engineering-ui
GitHub stars
112
Token cost
~3.6k tokens
SKILL.md length
598 words
Files
1
Skills in repo
15
Repo updated
First seen
Licence
MIT

At a glance

Prompt patterns for consistent UI generation: stating design intent precisely, component specification formats, few-shot examples, and structured refinement loops.

  • Works in 5 steps: Vague Aesthetic Descriptions → Missing State Coverage → No Design System Context → …
  • UI output from an LLM is inconsistent
  • SKILL.md covers When to Use This Skill, The UI Prompting Challenge, Core Prompt Patterns and Requirements, plus 7 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Prompt Engineering UI is an agent skill from HermeticOrmus/LibreUIUX-Claude-Code. Prompt patterns for consistent UI generation: stating design intent precisely, component specification formats, few-shot examples, and structured refinement loops. Use when UI output from an LLM is inconsistent or generic, or when building reusable prompt templates for a design system.

Its SKILL.md is about 3.6k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in AI & LLM Engineering, covering Prompt engineering. The repository describes itself as: UI/UX system for Claude Code: 71 plugins, 93 agents, 74 skills. Design mastery, archetypal design, accessibility, and frontend workflows in one validated plugin marketplace. The licence is MIT.

When your agent uses it

  • UI output from an LLM is inconsistent
  • Building reusable prompt templates for a design system

Example prompts

  • “/prompt-engineering-ui”

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. Vague Aesthetic Descriptions
  2. Missing State Coverage
  3. No Design System Context
  4. Implicit Accessibility
  5. One-Shot Expectation

What it can do on your machine

Read from SKILL.md and the folder at commit 41a968c. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown and typescript).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Prompt Engineering UI loads about 3.6k tokens when it runs. Until then it costs about 77 tokens; SKILL.md has 598 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~77
When it runs · the whole SKILL.md, loaded when a task matches
~3.6k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from HermeticOrmus/LibreUIUX-Claude-Code at commit 41a968c, republished under its MIT licence (© HermeticOrmus). 598 words, ~3,582 tokens.

Download SKILL.mdSave it as .claude/skills/prompt-engineering-ui/SKILL.md (or your agent's skills folder).
name
prompt-engineering-ui
description
Prompt patterns for consistent UI generation: stating design intent precisely, component specification formats, few-shot examples, and structured refinement loops. Use when UI output from an LLM is inconsistent or generic, or when building reusable prompt templates for a design system.

Prompt Engineering for UI Generation

Master the art of communicating design intent to LLMs. This skill covers prompt patterns specifically optimized for generating consistent, high-quality user interfaces.


When to Use This Skill

  • Writing prompts that generate consistent UI components
  • Describing design intent precisely to AI systems
  • Building reusable prompt templates for design systems
  • Iterating on UI generation with structured feedback
  • Creating few-shot examples for UI patterns
  • Debugging inconsistent UI generation outputs

The UI Prompting Challenge

UI generation is uniquely challenging because it requires:

  1. Visual precision - Exact spacing, colors, typography
  2. Behavioral specification - Interactions, states, animations
  3. Contextual coherence - Fitting within a design system
  4. Accessibility compliance - WCAG, ARIA, keyboard navigation
  5. Responsive adaptation - Multiple breakpoints, devices
  6. Code quality - Clean, maintainable output

Standard prompting techniques often fail because UI is simultaneously visual, behavioral, and technical.


Core Prompt Patterns

Pattern 1: The Component Contract

Define components as contracts with explicit input/output specifications.

markdown
## Component Contract: DataTable

### Purpose
Display tabular data with sorting, filtering, and pagination.

### Props (Inputs)
| Prop | Type | Required | Default | Description |
|------|------|----------|---------|-------------|
| data | T[] | Yes | - | Array of data objects |
| columns | ColumnDef[] | Yes | - | Column configuration |
| pageSize | number | No | 10 | Rows per page |
| sortable | boolean | No | true | Enable column sorting |
| filterable | boolean | No | false | Show filter inputs |

### Visual Specification
- **Container**: bg-white rounded-lg shadow-sm border border-gray-200
- **Header row**: bg-gray-50 text-gray-600 text-sm font-medium
- **Data rows**: hover:bg-gray-50 border-b border-gray-100
- **Typography**: Font-sans, body text 14px, headers 12px uppercase
- **Spacing**: Cell padding 12px horizontal, 8px vertical

### States
1. **Loading**: Skeleton rows with pulse animation
2. **Empty**: Centered message with icon
3. **Error**: Red border, error message below
4. **Selected**: bg-blue-50, left border accent

### Accessibility Requirements
- role="table" on container
- Sortable columns announce sort direction
- Focus visible on all interactive elements
- Keyboard navigation: Tab through headers, Enter to sort

### Output Format
React TypeScript component using Tailwind CSS.
Include JSDoc comments and prop types.

Why This Works:

  • Explicit contract eliminates ambiguity
  • Visual specs use actual CSS values
  • States prevent incomplete implementations
  • Accessibility is non-negotiable requirement

Pattern 2: Design Token Injection

Embed design tokens directly in prompts for consistency.

markdown
Generate a Card component following these design tokens:

## Tokens
```json
{
  "spacing": {
    "xs": "4px",
    "sm": "8px",
    "md": "16px",
    "lg": "24px",
    "xl": "32px"
  },
  "colors": {
    "surface": {
      "primary": "#FFFFFF",
      "secondary": "#F9FAFB",
      "elevated": "#FFFFFF"
    },
    "border": {
      "subtle": "#E5E7EB",
      "default": "#D1D5DB"
    },
    "shadow": {
      "sm": "0 1px 2px rgba(0,0,0,0.05)",
      "md": "0 4px 6px rgba(0,0,0,0.1)"
    }
  },
  "radius": {
    "sm": "4px",
    "md": "8px",
    "lg": "12px"
  }
}

Requirements

  • Card uses surface.elevated background
  • Border uses border.subtle
  • Padding uses spacing.lg
  • Border radius uses radius.lg
  • Shadow uses shadow.md

Map these tokens to Tailwind classes where possible.


**Token Mapping Strategy**:
```typescript
// Prompt can include this mapping guide
const tokenToTailwind = {
  "spacing.xs": "p-1",
  "spacing.sm": "p-2",
  "spacing.md": "p-4",
  "spacing.lg": "p-6",
  "spacing.xl": "p-8",
  "colors.surface.primary": "bg-white",
  "colors.surface.secondary": "bg-gray-50",
  "colors.border.subtle": "border-gray-200",
  "radius.lg": "rounded-xl",
  "shadow.md": "shadow-md",
};

Pattern 3: Visual Reference Chain

Chain visual descriptions from abstract to concrete.

markdown
## Component: Hero Section

### Mood (Abstract)
Confident, minimal, focused. The user should feel capable and unintimidated.

### Aesthetic (Semi-Abstract)
- Clean sans-serif typography
- Generous whitespace (40% of viewport)
- Single accent color for CTAs
- Photography: abstract, not literal

### Visual Details (Concrete)
- **Layout**: Centered, max-width 1200px, py-24
- **Headline**: text-5xl font-bold tracking-tight text-gray-900
- **Subheadline**: text-xl text-gray-600 max-w-2xl mx-auto mt-6
- **CTA Group**: mt-10 flex gap-4 justify-center
- **Primary CTA**: bg-indigo-600 hover:bg-indigo-700 text-white px-8 py-4 rounded-lg
- **Secondary CTA**: border border-gray-300 text-gray-700 px-8 py-4 rounded-lg

### Content
- Headline: "Build interfaces that inspire"
- Subheadline: "The design system that empowers creators to ship beautiful products faster."
- Primary CTA: "Get Started"
- Secondary CTA: "Learn More"

The Chain:

Mood → Aesthetic → Visual Details → Content
 ↓         ↓            ↓            ↓
Emotion   Style     CSS Values    Text

This pattern works because it builds from intention to implementation.


Pattern 4: State Machine Specification

Define component states as a state machine.

markdown
## Button Component States

### State Machine

idle → hover → pressed → idle ↓ ↓ ↓ focus focus focus ↓ ↓ ↓ disabled (terminal) loading (blocks all transitions)


### State Definitions

| State | Visual Treatment | Tailwind Classes |
|-------|------------------|------------------|
| idle | Default appearance | bg-blue-600 text-white |
| hover | Slightly darker | hover:bg-blue-700 |
| focus | Ring indicator | focus:ring-2 focus:ring-blue-500 focus:ring-offset-2 |
| pressed | Darker, slight scale | active:bg-blue-800 active:scale-[0.98] |
| disabled | Muted, no pointer | disabled:bg-gray-300 disabled:cursor-not-allowed |
| loading | Spinner, no text | Spinner SVG, opacity-50, pointer-events-none |

### Transitions
- All transitions: `transition-all duration-150 ease-in-out`
- Scale transitions: spring-like (use framer-motion if available)

### Implementation Notes
- Use `<button>` element, never `<div>`
- disabled state must be set via HTML attribute
- loading should set aria-busy="true"

Pattern 5: Constraint-First Prompting

Lead with constraints to narrow the solution space.

markdown
## Constraints (Non-Negotiable)

### Technical Constraints
- React 18+ with TypeScript strict mode
- Tailwind CSS only (no CSS-in-JS)
- No external component libraries
- Bundle size: component must be < 5KB gzipped

### Design Constraints
- Must pass WCAG 2.1 AA
- Must work without JavaScript (progressive enhancement)
- Must support RTL layouts
- Color contrast ratio >= 4.5:1

### Browser Support
- Chrome 90+, Firefox 88+, Safari 14+, Edge 90+
- No IE11 support required

### Performance Constraints
- First paint < 100ms
- No layout shift on load
- Images must be lazy-loaded

---

## Now, generate a Modal component that satisfies all constraints above.

Why Constraints First:

  • Eliminates invalid solutions immediately
  • Focuses generation on viable approaches
  • Makes review easier (checklist validation)
  • Prevents "creative" solutions that break requirements

Iterative Refinement Patterns

The Feedback Loop Protocol

Structure feedback for effective iteration:

markdown
## Iteration 1 Feedback

### What Works
- Component structure is correct
- Props interface is well-typed
- Basic styling matches tokens

### What Needs Fixing

#### Critical (Must Fix)
1. **Missing keyboard navigation**
   - Current: Only mouse interaction works
   - Required: Arrow keys to navigate, Enter to select
   - Reference: WAI-ARIA Listbox pattern

2. **Color contrast failure**
   - Current: text-gray-400 on bg-white (ratio 2.5:1)
   - Required: Minimum 4.5:1 for body text
   - Fix: Use text-gray-600 (ratio 5.7:1)

#### Important (Should Fix)
3. **Animation too fast**
   - Current: duration-75
   - Recommended: duration-150 for better perception

#### Nice to Have
4. Consider adding subtle shadow on hover

### Revised Requirements
Regenerate the component addressing Critical and Important items.

The Diff-Based Refinement

Request specific changes rather than full regeneration:

markdown
## Current Component

```tsx
<button className="bg-blue-500 text-white px-4 py-2 rounded">
  Click me
</button>

Requested Changes

  1. Add hover state: bg-blue-600 on hover
  2. Add focus ring: ring-2 ring-blue-500 ring-offset-2 on focus
  3. Add disabled state: Prop + visual treatment
  4. Add loading state: Spinner + loading prop

Output Format

Show only the modified code with inline comments explaining each change.


---

### The A/B Variant Request

Request multiple options for comparison:

```markdown
Generate 3 variants of a Card component:

## Variant A: Minimal
- No shadow
- Hairline border only
- Maximum whitespace

## Variant B: Elevated
- Pronounced shadow
- No visible border
- Subtle hover lift effect

## Variant C: Outlined
- Thick left accent border
- Light background fill
- Category color coding

## Common Requirements (All Variants)
- Same prop interface
- Same content structure
- Same responsive behavior
- Same accessibility

## Output
Provide all three variants as separate components.
Include a brief rationale for when to use each.

Show full SKILL.md (235 more words)Show less

Few-Shot Examples for UI

Example: Button Variants
markdown
## Few-Shot Examples: Button Component

### Example 1: Primary Button
Input: Primary action button with "Submit" text
Output:
```tsx
<button className="bg-indigo-600 hover:bg-indigo-700 text-white font-medium py-2.5 px-5 rounded-lg transition-colors focus:ring-2 focus:ring-indigo-500 focus:ring-offset-2">
  Submit
</button>
Example 2: Secondary Button

Input: Secondary action button with "Cancel" text Output:

tsx
<button className="bg-white hover:bg-gray-50 text-gray-700 font-medium py-2.5 px-5 rounded-lg border border-gray-300 transition-colors focus:ring-2 focus:ring-gray-500 focus:ring-offset-2">
  Cancel
</button>
Example 3: Danger Button

Input: Destructive action button with "Delete" text Output:

tsx
<button className="bg-red-600 hover:bg-red-700 text-white font-medium py-2.5 px-5 rounded-lg transition-colors focus:ring-2 focus:ring-red-500 focus:ring-offset-2">
  Delete
</button>

Now generate: Ghost button with "Learn More" text


**Pattern Recognition**:
- Consistent class structure across examples
- Clear input-output mapping
- Similar complexity level
- Demonstrates the pattern, not just the answer

---

## Prompt Templates

### Template: Component Generation

```markdown
# Generate: {ComponentName}

## Context
Project: {ProjectDescription}
Design System: {DesignSystemName}
Framework: React + TypeScript + Tailwind

## Design Tokens
{DesignTokensJSON}

## Component Specification
Purpose: {ComponentPurpose}
Props: {PropsTable}
States: {StatesList}
Variants: {VariantsList}

## Visual Requirements
Layout: {LayoutDescription}
Typography: {TypographySpecs}
Colors: {ColorSpecs}
Spacing: {SpacingSpecs}

## Behavior
Interactions: {InteractionList}
Animations: {AnimationSpecs}
Accessibility: {A11yRequirements}

## Constraints
{ConstraintsList}

## Output
Provide production-ready React TypeScript component.
Include prop types, JSDoc comments, and usage example.
Template: Design Review
markdown
# Review: {ComponentCode}

## Review Criteria

### Design Fidelity
- Does it match the design tokens?
- Is spacing consistent?
- Are colors correct?

### Accessibility
- Keyboard navigable?
- Screen reader friendly?
- Color contrast sufficient?

### Code Quality
- Types correct?
- Props well-named?
- Logic clear?

### Performance
- Unnecessary re-renders?
- Bundle size reasonable?
- Animations performant?

## Output Format
For each criterion, provide:
- Score (1-5)
- Issues found
- Specific fixes needed

Anti-Patterns in UI Prompting

1. Vague Aesthetic Descriptions

Bad: "Make it look modern and clean" Good: "Use Inter font, 16px base, 1.5 line-height, 24px vertical rhythm"

2. Missing State Coverage

Bad: "Create a button" Good: "Create a button with idle, hover, focus, active, disabled, and loading states"

3. No Design System Context

Bad: "Use a nice blue" Good: "Use the primary color from the design tokens: #4F46E5"

4. Implicit Accessibility

Bad: "Make it accessible" Good: "Include ARIA labels, keyboard navigation per WAI-ARIA Listbox pattern, focus indicators"

5. One-Shot Expectation

Bad: Expecting perfect output on first try Good: Plan for 2-3 refinement iterations with structured feedback


Quick Reference

SituationPattern to Use
New componentComponent Contract
Ensure consistencyDesign Token Injection
Explain visual intentVisual Reference Chain
Complex interactionsState Machine Specification
Avoid reworkConstraint-First Prompting
Improving outputFeedback Loop Protocol
Minor adjustmentsDiff-Based Refinement
Exploring optionsA/B Variant Request

Integration with Other Skills

This skill pairs well with:

  • agent-orchestration/ui-agent-patterns - Prompt patterns for agent delegation
  • context-management/design-system-context - Loading tokens into prompts
  • llm-application-dev/prompt-engineering-patterns - General prompting foundations
  • design-mastery/design-principles - Visual vocabulary for descriptions

"A precise prompt is a precise thought. The UI emerges from the clarity of intention."

© HermeticOrmus, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in plugins/llm-application-dev/skills/prompt-engineering-ui of HermeticOrmus/LibreUIUX-Claude-Code.

Open the folder on GitHubat commit 41a968c

Compare with similar skills

Prompt Engineering UI next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Prompt Engineering UI compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Prompt Engineering UI this skillHermeticOrmus/LibreUIUX-Claude-Code112—~3.6kAutomated safety check: PassMIT
Prompt Engineer Toolkitalirezarezvani/claude-skills28k—~1.4kAutomated safety check: PassMIT
Prompt Improverseverity1/claude-code-prompt-improver1.9k1 repos~1.7kAutomated safety check: PassMIT
Prompt Engineering Patternsynulihao/AgentSkillOS61814 repos~1.7kAutomated safety check: PassNone
Patch CreationPiebald-AI/tweakcc2.5k—~1.6kAutomated safety check: PassMIT
Senior Prompt Engineermaslennikov-ig/claude-code-orchestrator-kit2603 repos~1.4kAutomated safety check: PassCustom licence

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Questions about Prompt Engineering UI

What does Prompt Engineering UI do?

Prompt patterns for consistent UI generation: stating design intent precisely, component specification formats, few-shot examples, and structured refinement loops. Prompt Engineering UI is an agent skill from HermeticOrmus/LibreUIUX-Claude-Code. Prompt patterns for consistent UI generation: stating design intent precisely, component specification formats, few-shot examples, and structured refinement loops.

When should I use Prompt Engineering UI?

Prompt Engineering UI fits situations like: UI output from an LLM is inconsistent; building reusable prompt templates for a design system.

How do I install Prompt Engineering UI in Claude Code?

Run `npx skills add HermeticOrmus/LibreUIUX-Claude-Code --skill prompt-engineering-ui -a claude-code`. Or copy the skill folder (plugins/llm-application-dev/skills/prompt-engineering-ui in HermeticOrmus/LibreUIUX-Claude-Code) into .claude/skills/prompt-engineering-ui in your project. Claude Code loads it when a task matches its description.

How do I install Prompt Engineering UI in Codex?

Run `npx skills add HermeticOrmus/LibreUIUX-Claude-Code --skill prompt-engineering-ui -a codex`. Or copy the skill folder (plugins/llm-application-dev/skills/prompt-engineering-ui in HermeticOrmus/LibreUIUX-Claude-Code) into .agents/skills/prompt-engineering-ui in your project. Codex loads it when a task matches its description.

Can I use Prompt Engineering UI in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add HermeticOrmus/LibreUIUX-Claude-Code --skill prompt-engineering-ui -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/prompt-engineering-ui, .gemini/skills/prompt-engineering-ui, .github/skills/prompt-engineering-ui and .opencode/skills/prompt-engineering-ui in your project.

What does Prompt Engineering UI need to run?

SKILL.md names no scripts, command-line tools or credentials: Prompt Engineering UI is instructions for the agent only.

Does Prompt Engineering UI access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Prompt Engineering UI safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Prompt Engineering UI use?

Prompt Engineering UI is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Prompt Engineering UI use?

About 3.6k tokens (SKILL.md is roughly 14k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Prompt Engineering UI?

Skills that share tags, products or a category with Prompt Engineering UI: Prompt Engineer Toolkit (alirezarezvani/claude-skills, 28k stars), Prompt Improver (severity1/claude-code-prompt-improver, 1.9k stars), Prompt Engineering Patterns (ynulihao/AgentSkillOS, 618 stars) and Patch Creation (Piebald-AI/tweakcc, 2.5k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Prompt Engineering UI?

HermeticOrmus (a GitHub user) maintains it in HermeticOrmus/LibreUIUX-Claude-Code, which has 112 GitHub stars. The repository holds 15 skills in this directory. The repository was last updated on October 4, 2026.

Source: HermeticOrmus/LibreUIUX-Claude-Code on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.