home / skills / shaul1991 / shaul-agents-plugin / frontend-perf

frontend-perf skill

/skills/frontend-perf

This skill analyzes frontend performance and optimizes bundles, rendering, memoization, and Core Web Vitals to improve user experience.

npx playbooks add skill shaul1991/shaul-agents-plugin --skill frontend-perf

Review the files below or copy the command above to add this skill to your agents.

Files (1)
SKILL.md
530 B
---
name: frontend-perf
description: 성능 최적화 에이전트. 프론트엔드 성능을 분석하고 최적화합니다.
allowed-tools: Read, Write, Edit, Glob, Grep, Bash
---

# Frontend Performance Agent

## 역할
프론트엔드 성능을 분석하고 최적화합니다.

## 담당 업무
- 번들 크기 분석
- 렌더링 최적화
- 메모이제이션 적용
- Core Web Vitals 개선

## 트리거 키워드
성능, performance, 최적화, 번들, 속도

## 산출물 위치
- 분석 리포트: `docs/performance/`

Overview

This skill analyzes and optimizes frontend application performance to reduce load times and improve user experience. It targets bundle size, rendering efficiency, memoization opportunities, and Core Web Vitals to deliver measurable improvements. The output is a practical analysis report stored under docs/performance/.

How this skill works

The agent runs static and runtime inspections to identify large bundles, slow rendering paths, and wasted re-renders. It suggests concrete optimizations: code-splitting, tree-shaking, lazy loading, memoization, and layout/paint improvements tied to Core Web Vitals metrics. Recommendations include actionable code changes, prioritized fixes, and estimated impact on key metrics.

When to use it

  • Before major releases to cut load time and shipping size
  • When Core Web Vitals scores are low or dropping
  • After adding new dependencies or large components
  • When users report slow page loads or janky interactions
  • During performance budgets or optimization sprints

Best practices

  • Establish performance budgets for bundle size and TTFB/CLS/LCP
  • Prioritize fixes that yield high metric improvements with low effort
  • Measure before and after changes with lab and field data
  • Apply memoization and pure-component patterns to reduce re-renders
  • Split code and lazy-load noncritical routes and components

Example use cases

  • Analyze a bundle that grew after a dependency update and recommend tree-shaking or replacement
  • Find and fix long-running render functions causing high TBT and jank
  • Suggest memoization and useCallback/useMemo placements to reduce unnecessary work
  • Recommend asset delivery changes (compression, caching, preload) to improve LCP
  • Create a prioritized action list to meet a 200 KB initial bundle budget

FAQ

What outputs does the skill produce?

A prioritized analysis report with findings, suggested code changes, and estimated metric impacts saved to docs/performance/.

Does it modify code automatically?

The agent provides concrete patch suggestions and snippets but does not auto-commit changes; developers review and apply them.

Which metrics are targeted?

Core Web Vitals (LCP, CLS, FID/TBT) plus bundle size, time-to-interactive, and render-blocking issues.