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am-will/vercel-react-best-practices

Vercel 엔지니어링 팀의 React 및 Next.js 성능 최적화 가이드라인입니다. React/Next.js 코드를 작성, 리뷰 또는 리팩토링할 때 최적의 성능 패턴을 보장하기 위해 이 스킬을 사용하세요.

vercel-react-best-practices란 무엇인가요?

이 스킬은 Vercel 엔지니어링 팀이 제공하는 React 및 Next.js 성능 최적화 가이드라인으로, 개발자가 React 컴포넌트, Next.js 페이지, 데이터 페칭, 번들 최적화, 성능 개선 작업을 수행할 때 최적의 성능 패턴을 적용할 수 있도록 도와줍니다. 주요 목표는 React 애플리케이션의 렌더링 성능을 극대화하고, Next.js의 서버 사이드 렌더링(SSR) 및 정적 사이트 생성(SSG) 기능을 효과적으로 활용하며, 번들 크기를 최소화하여 사용자 경험을 향상시키는 것입니다. 이 스킬은 Claude Code, Cursor, Codex와 같은 AI 에이전트 플랫폼에서 사용하도록 설계되었으며, 코드 리뷰, 리팩토링, 또는 새로운 기능 개발 시 자동으로 트리거되어 관련 권장 사항을 제시합니다. 가이드라인은 React 메모이제이션(memo, useMemo, useCallback), 데이터 페칭 최적화(SWR, React Query), 코드 스플리팅, 이미지 최적화, Next.js App Router 사용법 등 최신 모범 사례를 포함하여 확장성과 유지보수성을 고려한 실제 전략을 제공합니다.

지원 대상~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/am-will/codex-skills/tree/main/skills/vercel-react-best-practices

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vercel-react-best-practices은(는) 무엇을 하나요?

Vercel 엔지니어링 팀의 React 및 Next.js 성능 최적화 가이드라인입니다. 이 스킬은 React/Next.js 코드를 작성, 리뷰 또는 리팩토링할 때 최적의 성능 패턴을 보장하기 위해 사용해야 합니다. React 컴포넌트, Next.js 페이지, 데이터 페칭, 번들 최적화 또는 성능 개선과 관련된 작업에서 트리거됩니다.

Individual skills in this repo

This repo contains 17 individual skills — each has its own dedicated page.

am-will/agent-browser

A fast Rust-based headless browser automation CLI with Node.js fallback that enables AI agents to navigate, click, type, and snapshot pages via structured commands.

am-will/context7

Fetch up-to-date library documentation via Context7 CLI. Use PROACTIVELY when: (1) Working with ANY external library (React, Next.js, Supabase, etc.) (2) User asks about library APIs, patterns, or best practices (3) Implementing features that rely on third-party packages (4) Debugging library-specific issues (5) Need current documentation beyond training data cutoff (6) AND MOST IMPORTANTLY, when you are installing dependencies, libraries, or frameworks you should ALWAYS check the docs to see what the latest versions are. Do not rely on outdated knowledge. Always prefer this over guessing library APIs or using outdated knowledge.

am-will/frontend-design

Create distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, or applications. Generates creative, polished code that avoids generic AI aesthetics.

am-will/frontend-responsive-design-standards

Build responsive, mobile-first layouts using fluid containers, flexible units, media queries, and touch-friendly design that works across all screen sizes. Use this skill when creating or modifying UI layouts, responsive grids, breakpoint styles, mobile navigation, or any interface that needs to adapt to different screen sizes. Apply when working with responsive CSS, media queries, viewport settings, flexbox/grid layouts, mobile-first styling, breakpoint definitions (mobile, tablet, desktop), touch target sizing, relative units (rem, em, %), image optimization for different screens, or testing layouts across multiple devices. Use for any task involving multi-device support, responsive design patterns, or adaptive layouts.

am-will/gemini-computer-use

Build and run Gemini 2.5 Computer Use browser-control agents with Playwright. Use when a user wants to automate web browser tasks via the Gemini Computer Use model, needs an agent loop (screenshot → function_call → action → function_response), or asks to integrate safety confirmation for risky UI actions.

am-will/llm-council

Orchestrate a configurable, multi-member CLI planning council (Codex, Claude Code, Gemini, OpenCode, or custom) to produce independent implementation plans, anonymize and randomize them, then judge and merge into one final plan. Use when you need a robust, bias-resistant planning workflow, structured JSON outputs, retries, and failure handling across multiple CLI agents.

am-will/markdown-url

Route any website you need to visit through markdown.new by prefixing the URL. **WHEN TO USE:** - You would normally open a website link to read content (docs, blog posts, changelogs, GitHub issues, etc.) - You need a cleaner, Markdown-friendly view for copying notes or summarizing

am-will/openai-docs-skill

Query the OpenAI developer documentation via the OpenAI Docs MCP server using CLI (curl/jq). Use whenever a task involves the OpenAI API (Responses, Chat Completions, Realtime, etc.), OpenAI SDKs, ChatGPT Apps SDK, Codex, MCP integrations, endpoint schemas, parameters, limits, or migrations and you need up-to-date official guidance.

am-will/parallel-task

Only to be triggered by explicit /parallel-task commands.

am-will/parallel-task-spark

Only to be triggered by explicit /parallel-task-spark commands.

am-will/plan-harder

Use when user specfically says 'plan harder'.

am-will/planner

Create comprehensive, phased implementation plans with sprints and atomic tasks. Use when user says: "make a plan", "create a plan", "plan this out", "plan the implementation", "help me plan", "design a plan", "draft a plan", "write a plan", "outline the steps", "break this down into tasks", "what's the plan for", or any similar planning request. Also triggers on explicit "/planner" or "/plan" commands.

am-will/read-github

Read and search GitHub repository documentation via gitmcp.io MCP service. **WHEN TO USE:** - User provides a GitHub URL - User mentions a specific repo in owner/repo format - User asks "what does this repo do?", "read the docs for X repo", or similar - User wants to search code or docs within a repo

am-will/role-creator

Create and update Codex custom agents using standalone custom-agent TOML files.

am-will/super-swarm-spark

Only to be triggered by explicit super-swarm-spark commands.

am-will/swarm-planner

[EXPLICIT INVOCATION ONLY] Creates dependency-aware implementation plans optimized for parallel multi-agent execution.

am-will/tdd-test-writer

Writes failing tests first for test-driven development and hands off a strict implementation contract that requires agents to make those tests pass without weakening the tests. Use when users ask for test-first workflows, RED/GREEN cycles, or behavior-gating tasks with automated tests.

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