React and Next.js patterns for component composition, state management, performance optimization, and accessible UI.
Works with
Covers component patterns including composition, compound components, and render props for flexible, reusable UI architecture
Provides custom hooks for state management, async data fetching, debouncing, and form handling with validation
Includes performance techniques: memoization, code splitting with lazy loading, and virtualization for large lists
Demonstrates err
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionfrontend-patternsExecute the skills CLI command in your project's root directory to begin installation:
Fetches frontend-patterns from affaan-m/everything-claude-code and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate frontend-patterns. Access via /frontend-patterns in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
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Modern frontend patterns for React, Next.js, and performant user interfaces.
// PASS: GOOD: Component composition
interface CardProps {
children: React.ReactNode
variant?: 'default' | 'outlined'
}
export function Card({ children, variant = 'default' }: CardProps) {
return <div className={`card card-${variant}`}>{children}</div>
}
export function CardHeader({ children }: { children: React.ReactNode }) {
return <div className="card-header">{children}</div>
}
export function CardBody({ children }: { children: React.ReactNode }) {
return <div className="card-body">{children}</div>
}
// Usage
<Card>
<CardHeader>Title</CardHeader>
<CardBody>Content</CardBody>
</Card>
interface TabsContextValue {
activeTab: string
setActiveTab: (tab: string) => void
}
const TabsContext = createContext<TabsContextValue | undefined>(undefined)
export function Tabs({ children, defaultTab }: {
children: React.ReactNode
defaultTab: string
}) {
const [activeTab, setActiveTab] = useState(defaultTab)
return (
<TabsContext.Provider value={{ activeTab, setActiveTab }}>
{children}
</TabsContext.Provider>
)
}
export function TabList({ children }: { children: React.ReactNode }) {
return <div className="tab-list">{children}</div>
}
export function Tab({ id, children }: { id: string, children: React.ReactNode }) {
const context = useContext(TabsContext)
if (!context) throw new Error('Tab must be used within Tabs')
return (
<button
className={context.activeTab === id ? 'active' : ''}
onClick={() => context.setActiveTab(id)}
>
{children}
</button>
)
}
// Usage
<Tabs defaultTab="overview">
<TabList>
<Tab id="overview">Overview</Tab>
<Tab id="details">Details</Tab>
</TabList>
</Tabs>
interface DataLoaderProps<T> {
url: string
children: (data: T | null, loading: boolean, error: Error | null) => React.ReactNode
}
export function DataLoader<T>({ url, children }: DataLoaderProps<T>) {
const [data, setData] = useState<T | null>(null)
const [loading, setLoading] = useState(true)
const [error, setError] = useState<Error | null>(null)
useEffect(() => {
fetch(url)
.then(res => res.json())
.then(setData)
.catch(setError)
.finally(() => setLoading(false))
}, [url])
return <>{children(data, loading, error)}</>
}
// Usage
<DataLoader<Market[]> url="/api/markets">
{(markets, loading, error) => {
if (loading) return <Spinner />
if (error) return <Error error={error} />
return Implementation Guide
Prerequisites
- ›Claude Desktop or compatible AI client with skill support
- ›Clear understanding of task or problem to solve
- ›Willingness to iterate and refine outputs
Time Estimate
15-45 minutes depending on use case complexity
Steps
- 1Install skill using provided installation command
- 2Test with simple use case relevant to your work
- 3Evaluate output quality and relevance
- 4Iterate on prompts to improve results
- 5Integrate into regular workflow if valuable
Common Pitfalls
- ⚠Expecting perfect results without iteration
- ⚠Not providing enough context in prompts
- ⚠Using skill for tasks outside its intended scope
- ⚠Accepting outputs without review and validation
Best Practices
✓ Do
- +Start with clear, specific prompts
- +Provide relevant context and constraints
- +Review and refine all outputs before using
- +Iterate to improve output quality
- +Document successful prompt patterns
✗ Don't
- −Don't use without understanding skill limitations
- −Don't skip validation of outputs
- −Don't share sensitive information in prompts
- −Don't expect skill to replace human judgment
💡 Pro Tips
- ★Be specific about desired format and style
- ★Ask for multiple options to choose from
- ★Request explanations to understand reasoning
- ★Combine AI efficiency with human expertise
When to Use This
✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid when
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
Learning Path
- 1Familiarize yourself with skill capabilities and limitations
- 2Start with low-risk, non-critical tasks
- 3Progress to more complex and valuable use cases
- 4Build expertise through regular use and experimentation
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Frontendsame categoryReviews
4.8★★★★★34 reviews- MMichael Abebe★★★★★Dec 24, 2024
We added frontend-patterns from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- FFatima Iyer★★★★★Dec 16, 2024
Registry listing for frontend-patterns matched our evaluation — installs cleanly and behaves as described in the markdown.
- AAdvait Perez★★★★★Nov 15, 2024
frontend-patterns reduced setup friction for our internal harness; good balance of opinion and flexibility.
- YYusuf Abebe★★★★★Nov 7, 2024
frontend-patterns fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- YYusuf Farah★★★★★Oct 26, 2024
We added frontend-patterns from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- EEvelyn Bansal★★★★★Oct 6, 2024
Registry listing for frontend-patterns matched our evaluation — installs cleanly and behaves as described in the markdown.
- PPiyush G★★★★★Sep 13, 2024
We added frontend-patterns from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- AAnika Nasser★★★★★Sep 1, 2024
We added frontend-patterns from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- CChinedu Taylor★★★★★Aug 20, 2024
frontend-patterns fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- SShikha Mishra★★★★★Aug 4, 2024
frontend-patterns fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
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