frontend-design-review

$npx mdskill add microsoft/skills/frontend-design-review

Review and create production-grade frontend interfaces with high design quality.

  • Evaluates UI implementations against design system and quality standards.
  • Depends on design system documentation and accessibility guidelines.
  • Uses three pillars: frictionless insight-to-action, quality craft, trustworthy building.
  • Delivers actionable review feedback or generates distinctive frontend code.

SKILL.md

.github/skills/frontend-design-reviewView on GitHub ↗
---
name: frontend-design-review
description: >
  Review and create distinctive, production-grade frontend interfaces with high design quality and design system compliance.
  Evaluates using three pillars: frictionless insight-to-action, quality craft, and trustworthy building.
  USE FOR: PR reviews, design reviews, accessibility audits, design system compliance checks, creative frontend design,
  UI code review, component reviews, responsive design checks, theme testing, and creating memorable UI.
  DO NOT USE FOR: Backend API reviews, database schema reviews, infrastructure or DevOps work, pure business logic
  without UI, or non-frontend code.
acknowledgments: |
  Design review principles and quality pillar framework created by @Quirinevwm (https://github.com/Quirinevwm).
  Creative frontend guidance inspired by Anthropic's frontend-design skill
  (https://github.com/anthropics/skills/tree/main/skills/frontend-design). Licensed under respective terms.
---

# Frontend Design Review

Review UI implementations against design quality standards and your design system **OR** create distinctive, production-grade frontend interfaces from scratch.

## Two Modes

### Mode 1: Design Review
Evaluate existing UI for design system compliance, three quality pillars (Frictionless, Quality Craft, Trustworthy), accessibility, and code quality.

### Mode 2: Creative Frontend Design
Create distinctive interfaces that avoid generic "AI slop" aesthetics, have clear conceptual direction, and execute with precision.

---

## Creative Frontend Design

Before coding, commit to an aesthetic direction:
- **Purpose**: What problem does this solve? Who uses it?
- **Tone**: minimal, maximalist, retro-futuristic, organic, luxury, playful, editorial, brutalist, art deco, soft/pastel, industrial, etc.
- **Constraints**: Framework, performance, accessibility requirements.
- **Differentiation**: What makes this distinctive and context-appropriate?

### Aesthetics Guidelines

- **Typography**: Distinctive fonts that elevate aesthetics. Pair a display font with a refined body font. Avoid Inter, Roboto, Arial, Space Grotesk.
- **Color & Theme**: Cohesive palette with CSS variables. Dominant colors + sharp accents > timid, evenly-distributed palettes.
- **Motion**: CSS-only preferred. One well-orchestrated page load with staggered reveals > scattered micro-interactions.
- **Spatial Composition**: Asymmetry, overlap, diagonal flow, grid-breaking elements, generous negative space OR controlled density.
- **Backgrounds**: Gradient meshes, noise textures, geometric patterns, layered transparencies, dramatic shadows, grain overlays.

**AVOID**: Overused fonts, cliched color schemes, predictable layouts, cookie-cutter design without context-specific character.

Match implementation complexity to vision. Maximalist = elaborate code. Minimalist = restraint and precision.

---

## Design Review

### Design System Workflow

**Before implementing:**
1. Review component in your Storybook / component library for API and usage
2. Use Figma Dev Mode to get exact specs (spacing, tokens, properties)
3. Implement using design system components + design tokens

**During review:**
1. Compare implementation to Figma design
2. Verify design tokens are used (not hardcoded values)
3. Check all variants/states are implemented correctly
4. Flag deviations (needs design approval)

**If component doesn't exist:**
1. Check if existing component can be adapted
2. Reach out to design for new component creation
3. Document exception and rationale in code

### Review Process

1. Identify user task
2. Check design system for matching patterns
3. Evaluate aesthetic direction
4. Identify scope (component, feature, or flow)
5. Evaluate each pillar
6. Score and prioritize issues (blocking/major/minor)
7. Provide recommendations with design system examples

### Core Principles

- **Task completion**: Minimum clicks. Every screen answers "What can I do?" and "What happens next?"
- **Action hierarchy**: 1-2 primary actions per view. Progressive disclosure for secondary.
- **Onboarding**: Explain features on introduction. Smart defaults over configuration.
- **Navigation**: Clear entry/exit points. Back/cancel always available. Breadcrumbs for deep flows.

---

## Quality Pillars

### 1. Frictionless Insight to Action

**Evaluate:** Task completable in ≤3 interactions? Primary action obvious and singular?

**Red flags:** Excessive clicks, multiple competing primary buttons, buried actions, dead ends.

### 2. Quality is Craft

**Evaluate:**
- Design system compliance: matches Figma specs, uses design tokens
- Aesthetic direction: distinctive typography, cohesive colors, intentional motion
- Accessibility: Grade C minimum (WCAG 2.1 A), Grade B ideal (WCAG 2.1 AA)

**Red flags:** Generic AI aesthetics, hardcoded values, implementation doesn't match Figma, broken reflow, missing focus indicators.

### 3. Trustworthy Building

**Evaluate:**
- AI transparency: disclaimer on AI-generated content
- Error transparency: actionable error messages

**Red flags:** Missing AI disclaimers, opaque errors without guidance.

---

## Review Output Format

See [references/review-output-format.md](references/review-output-format.md) for the full review template.

## Review Type Modifiers

See [references/review-type-modifiers.md](references/review-type-modifiers.md) for context-specific review focus areas (PR, Creative, Design, Accessibility).

## Quick Checklist

See [references/quick-checklist.md](references/quick-checklist.md) for the pre-approval checklist covering design system compliance, aesthetic quality, frictionless, quality craft, and trustworthy pillars.

## Pattern Examples

See [references/pattern-examples.md](references/pattern-examples.md) for good/bad examples of creative frontend and design system review work.

---

## Acknowledgments

Creative frontend principles inspired by [Anthropic's frontend-design skill](https://github.com/anthropics/skills/tree/main/skills/frontend-design). Design review principles and quality pillar framework created by [@Quirinevwm](https://github.com/Quirinevwm) for systematic UI evaluation.

More from microsoft/skills

SkillDescription
agent-framework-azure-ai-pyBuild Azure AI Foundry agents using the Microsoft Agent Framework Python SDK (agent-framework-azure-ai). Use when creating persistent agents with AzureAIAgentsProvider, using hosted tools (code interpreter, file search, web search), integrating MCP servers, managing conversation threads, or implementing streaming responses. Covers function tools, structured outputs, and multi-tool agents.
airunway-aks-setupSet up AI Runway on AKS — from bare cluster to running model. Covers cluster verification, controller install, GPU assessment, provider setup, and first deployment. WHEN: \"setup AI Runway\", \"onboard AKS cluster\", \"install AI Runway\", \"airunway setup\", \"deploy model to AKS\", \"GPU inference on AKS\", \"KAITO setup on AKS\", \"run LLM on AKS\", \"vLLM on AKS\", \"set up model serving on AKS\", \"AI Runway controller\".
appinsights-instrumentationGuidance for instrumenting webapps with Azure Application Insights. Provides telemetry patterns, SDK setup, and configuration references. WHEN: how to instrument app, App Insights SDK, telemetry patterns, what is App Insights, Application Insights guidance, instrumentation examples, APM best practices.
applicationinsights-web-tsInstrument browser/web apps with the Application Insights JavaScript SDK (@microsoft/applicationinsights-web). Use for Real User Monitoring (RUM) — page views, clicks, AJAX/fetch dependencies, exceptions, custom events, and browser-side GenAI agent traces correlated to backend OpenTelemetry traces. Covers SDK Loader Script and npm setup, framework extensions (React, React Native, Angular), Click Analytics, telemetry initializers, and OTel GenAI semantic conventions for agent/tool/model spans emitted from the browser.
azure-aiUse for Azure AI: Search, Speech, OpenAI, Document Intelligence. Helps with search, vector/hybrid search, speech-to-text, text-to-speech, transcription, OCR. WHEN: AI Search, query search, vector search, hybrid search, semantic search, speech-to-text, text-to-speech, transcribe, OCR, convert text to speech.
azure-ai-agents-persistent-dotnet|
azure-ai-agents-persistent-java|
azure-ai-anomalydetector-javaBuild anomaly detection applications with Azure AI Anomaly Detector SDK for Java. Use when implementing univariate/multivariate anomaly detection, time-series analysis, or AI-powered monitoring.
azure-ai-contentsafety-javaBuild content moderation applications with Azure AI Content Safety SDK for Java. Use when implementing text/image analysis, blocklist management, or harm detection for hate, violence, sexual content, and self-harm.
azure-ai-contentsafety-py|