스킬 performance-optimization
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performance-optimization

콘텐츠 리비전 r2 안전 ⚡ 스크립트 포함⚙️ 외부 명령어📁 파일 시스템 접근

Improve Application Performance with Evidence

Performance problems are difficult to diagnose when teams optimize from assumptions. This skill provides a measurement-first workflow for finding bottlenecks, testing fixes, and preventing regressions.

지원: Claude Codex Code(CC)
Maintain this Skill? Claim it 🥉 78 브론즈

내 에이전트로 설치

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에이전트 요청
Review the Skillstore skill "performance-optimization" from https://skillstore.io/skills/addyosmani-performance-optimization.md and its manifest at https://skillstore.io/api/skills/addyosmani-performance-optimization/manifest. Verify the artifact. You may proceed after verification, subject to the environment's own policy.

에이전트는 계속해서 계획을 표시하고 보안 정책에서 요구하는 확인을 요청해야 합니다.

에이전트가 읽기 쉬운 리소스

AI 에이전트, 크롤러, 스크립트가 전체 페이지 대신 정리된 컨텍스트만 필요할 때 이 링크를 사용하세요.

테스트해 보기

"performance-optimization" 사용 중입니다. The page has LCP of 4.2 seconds, a 1.8 MB JavaScript bundle, and large hero images.

예상 결과:

  • Prioritize the hero image and initial JavaScript payload.
  • Measure image transfer, render blocking, and bundle composition.
  • Test responsive image formats and route-level code splitting.
  • Keep the change only if LCP improves beyond normal run-to-run variance.

"performance-optimization" 사용 중입니다. An API loads tasks and fetches each task owner separately.

예상 결과:

This is an N+1 query pattern. Fetch tasks with their owners in one query, then compare query count and p95 latency before and after.

"performance-optimization" 사용 중입니다. A cache serves user profiles by profile ID, but the response includes tenant-specific permissions.

예상 결과:

The cache key omits a response input. Include tenant and permission context, or avoid shared caching when authorization data must remain isolated.

보안 감사

안전
v2 • 2026. 9. 19. 버전별 보고서 열기

All 55 static findings were reviewed against SKILL.md. They are false positives caused by documentation examples, Markdown syntax, a relative reference link, and fixed diagnostic SQL; no malicious behavior or prompt injection was found.

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가장 최근에 완료된 정적·의미론적 감사에서 확인된 보안 발견 사항이 감지되지 않았습니다. 이는 스킬에 부작용이 없음을 증명하지 않습니다.
감사자: codex 감사 이력 보기 →
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버전별 보고서 열기
보안 평가

보고서 링크 복사

https://skillstore.io/skills/addyosmani-performance-optimization/audits/2?utm_source=security_passport&utm_medium=share&utm_campaign=versioned_report

Markdown 배지

[![Skillstore security assessment](https://skillstore.io/badges/skills/addyosmani-performance-optimization/security.svg)](https://skillstore.io/skills/addyosmani-performance-optimization?utm_source=security_passport_badge)

HTML 배지

<a href="https://skillstore.io/skills/addyosmani-performance-optimization?utm_source=security_passport_badge"><img src="https://skillstore.io/badges/skills/addyosmani-performance-optimization/security.svg" alt="Skillstore security assessment" loading="lazy"></a>

임베드 카드

<iframe src="https://skillstore.io/embed/skills/addyosmani-performance-optimization.html" title="Skillstore Security Assessment" sandbox="allow-popups allow-popups-to-escape-sandbox" loading="lazy" referrerpolicy="no-referrer" width="420" height="180"></iframe>
학술 인용 (APA · BibTeX · CFF)

APA 인용

addyosmani. (2026). performance-optimization security audit report (audit version 2) [Author version unspecified]. Skillstore. https://skillstore.io/skills/addyosmani-performance-optimization/audits/2

BibTeX 인용

@techreport{addyosmani-addyosmani-performance-optimization-2026, author = {addyosmani}, title = {performance-optimization security audit report (audit version 2)}, institution = {Skillstore}, year = {2026}, number = {2}, url = {https://skillstore.io/skills/addyosmani-performance-optimization/audits/2}, note = {Author version unspecified} }

CITATION.cff

cff-version: 1.2.0 message: "If you use this Skill, cite its author and this versioned security audit report." title: "performance-optimization security audit report (audit version 2)" version: "unspecified" type: report authors: - name: "addyosmani" date-released: "2026-09-19" url: "https://skillstore.io/skills/addyosmani-performance-optimization/audits/2" identifiers: - type: other value: "skillstore:addyosmani-performance-optimization:audit:2" description: "Skillstore immutable audit report identifier"

변형 비교

설치 가능한 변형 3개

각 작성자의 스킬은 별도의 설치 항목으로 유지됩니다. 추천 변형은 Skillstore 근거로 순위가 정해집니다.

이 변형이 1위인 이유

근거 신뢰도가 더 높음
ArieGoldkin 권장

ariegoldkin-performance-optimization

Skillstore 점수 78
증거 신뢰도 높음
Skillstore 사용량 20
업데이트됨

2026-10-24

addyosmani 현재

addyosmani-performance-optimization

Skillstore 점수 78
증거 신뢰도 중간
Skillstore 사용량 6
업데이트됨

2026-09-22

supercent-io-performance-optimization

Skillstore 점수 77
증거 신뢰도 높음
Skillstore 사용량 29
업데이트됨

2026-09-09

Skillstore 점수

이 점수의 이유 증거 신뢰도: 중간
55
아키텍처
85
유지보수성
87
콘텐츠
65
커뮤니티
91
사양 준수

만들 수 있는 것

Diagnose a Slow Web Page

Use measured browser data to identify bundle, rendering, image, interaction, or server-response bottlenecks.

Tune Database-Backed APIs

Review query plans, indexes, pagination, N+1 patterns, and connection pools before changing backend code.

Set a Regression Guardrail

Create performance budgets and monitoring checks that verify improvements and catch later regressions.

이 프롬프트를 사용해 보세요

Find the First Measurement
My application feels slow. Ask for the minimum data needed, then identify the first measurements I should collect.
Review Frontend Metrics
Review these LCP, INP, CLS, bundle, and network results. Identify the most likely bottleneck and propose one testable fix.
Analyze a Query Plan
Analyze this query and EXPLAIN ANALYZE output. Explain the bottleneck, evaluate index options, and state the measurement needed after the change.
Design a Performance Experiment
Design a controlled performance experiment for this suspected bottleneck. Define the baseline, one change, success threshold, variance check, rollback rule, and regression guard.

모범 사례

  • Measure a representative baseline before proposing an optimization.
  • Change one variable at a time and compare results against run-to-run variance.
  • Keep only changes that improve the target metric without reducing correctness.

피하기

  • Adding indexes, caches, or memoization without evidence of a measured bottleneck.
  • Keeping a neutral optimization because it has already been implemented.
  • Combining several changes in one experiment so their effects cannot be attributed.

자주 묻는 질문

What should I measure first?
Start with the user-visible symptom and collect a baseline for the relevant metric, such as LCP, INP, p95 latency, or query time.
Can this skill optimize my code automatically?
No. It provides analysis, recommendations, and verification steps. You decide which code, database, or infrastructure changes to implement.
When should I add a database index?
Inspect the query plan first. Add an index when it addresses the query shape and measure both read improvement and write cost.
How should I choose a cache?
Choose the smallest suitable layer based on scope, freshness, invalidation, and recomputation cost. Include every response input in the cache key.
How do I know an optimization worked?
Repeat the baseline measurement under comparable conditions. Keep the change only when the improvement exceeds normal variance and tests remain correct.
Does this cover production monitoring?
Yes. It recommends synthetic budgets and field monitoring for the primary user-facing metric, with alerts that lead back to fresh measurement.

개발자 세부 정보

작성자

addyosmani

라이선스

MIT

Skillstore 리비전

r2

버전 안내

작성자가 버전을 선언하지 않았습니다.

참조

5d5054f8a23586f9b500fece1cb613a9dffc787b

유지보수 최신성

2026. 9. 19.

사용량

1 다운로드 · 0 조회

파일 구조

📄 SKILL.md

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