사용 방법
- 설치 명령을 복사하고 자신의 에이전트 환경에 설치하기 전에 소스 패키지를 확인하세요.
- 필요한 도구, 인증 정보, 지원 환경은 원본 문서에서 확인하세요.
- 입력과 원하는 산출물을 설명하고 출처와 결과를 대조하세요.
npx skills add https://github.com/spencerpauly/awesome-cursor-skills --skill profiling-performance시작 전 확인
- 설치에는 모델 구독, API 한도, 파일 접근 권한이 포함되지 않습니다.
- 별점 수와 설치 수는 활동 지표이며 독립적인 품질·보안 검증이 아닙니다.
원본 저장소의 제목, 예시, 코드, 표, 링크, 이미지를 유지해 표시합니다.
Performance Profile
Use this skill when a web application feels slow, janky, or unresponsive. Cursor's built-in browser has CPU profiling tools that capture real call stacks and timing data.
How It Works
The cursor-ide-browser MCP provides browser_profile_start and browser_profile_stop tools that capture Chrome DevTools-format CPU profiles. Profile data is written to ~/.cursor/browser-logs/ as both raw JSON and a human-readable summary.
Steps
- Ensure the app is running — start the dev server if it isn't already running.
- Navigate to the slow page:
Tool: browser_navigate
Arguments: { "url": "http://localhost:3000/slow-page" }- Start profiling:
Tool: browser_profile_start- Reproduce the slow interaction — use browser tools to trigger the slow behavior:
- Click buttons, scroll, type in inputs, navigate between pages
- Use
browser_click,browser_scroll,browser_fillto interact - Wait a few seconds for the interaction to complete
- Stop profiling:
Tool: browser_profile_stopThis writes two files to ~/.cursor/browser-logs/:
cpu-profile-{timestamp}.json— raw Chrome DevTools profilecpu-profile-{timestamp}-summary.md— human-readable summary
- Analyze the results — read both files. Key things to look for in the raw JSON:
profile.nodes[].hitCount— how many samples hit each functionprofile.nodes[].callFrame.functionName— the function namesprofile.samples.length— total number of samples collected
Cross-reference with the summary to identify:
- Functions consuming the most CPU time
- Unexpected re-renders or layout thrashing
- Expensive third-party library calls
- Synchronous operations blocking the main thread
- Suggest fixes — based on the profile data, recommend specific optimizations:
- Memoize expensive computations
- Debounce rapid event handlers
- Move heavy work to a Web Worker
- Lazy-load components or routes
- Virtualize long lists
Notes
- Always read the raw
.jsonprofile to verify the summary — the summary can miss nuances. - Profile in development mode first, but be aware that React dev mode adds overhead. For accurate measurements, profile a production build.
- Short profiles (2-5 seconds of interaction) are usually more useful than long ones.
- Compare before/after profiles to verify your optimization actually helped.





