optimizing-performance

Identify and optimize performance bottlenecks across web, API, database, and mobile systems.

Updated Aug 23, 2026

Search Tags:#performance #caching #database #optimization #backend #LCP #core-web-vitals

Ready to run

npx skills add https://github.com/sekka/dotfiles --skill optimizing-performance-sekka

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: optimizing-performance
Source: https://github.com/sekka/dotfiles/tree/main/home/.claude/skills/optimizing-performance
Command: npx skills add https://github.com/sekka/dotfiles --skill optimizing-performance-sekka

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Web/モバイル/バックエンド全体のパフォーマンス最適化を包括的に支援します。Core Web Vitals の改善、データベースクエリの最適化、インフラリソースの最適化を提供します。

Core Features & Use Cases

現状測定とベースライン確立
ボトルネック特定と優先度付け
クイックウィン/中期/長期の最適化提案
プラットフォーム別最適化（フロントエンド/バックエンド/データベース/モバイル）

Quick Start

現在のアプリのベースラインを測定して、初期の最適化提案リストを作成してください。

Frequently Asked Questions about optimizing-performance

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I measure and identify performance bottlenecks across my web and backend systems?▼

Performance bottleneck identification starts with baseline measurement: collect Core Web Vitals (LCP, FID, CLS, FCP, TTI) for frontend, API latency percentiles (p50/p95/p99) for backend, and database query times. Profile CPU, memory, and network I/O to pinpoint the slowest components, then prioritize by user impact and fix effort.

What metrics should I track to optimize Core Web Vitals and API performance?▼

Track Largest Contentful Paint (LCP), First Input Delay (FID), Cumulative Layout Shift (CLS), First Contentful Paint (FCP), and Time to Interactive (TTI) for frontend. For backend and databases, measure API response time percentiles (p50/p95/p99), query execution times, and resource consumption (CPU, memory, I/O) to establish performance budgets.

How do I create a staged optimization plan with quick wins and long-term improvements?▼

Staged optimization prioritizes fixes by impact and effort: quick wins target easy, high-impact improvements (caching, query optimization); mid-term focuses on architectural changes (database indexing, API redesign); long-term addresses infrastructure scaling and resource allocation. Measure each stage against your performance budgets.

Can I optimize performance across frontend, backend, database, and mobile simultaneously?▼

Yes. Performance optimization applies platform-specific targets: frontend focuses on Core Web Vitals and asset delivery; backend addresses API latency and throughput; databases optimize query performance and indexing; mobile targets resource usage and network efficiency. Use unified benchmark reports to coordinate improvements across all layers.

What outputs do I get from a performance optimization analysis?▼

Performance analysis delivers benchmark reports documenting baseline metrics, a prioritized bottleneck list with root causes, optimization proposals with effort/impact estimates, and performance budgets defining acceptable thresholds for LCP, API p99, query times, and resource usage across your system.

Do I need existing monitoring tools to start performance optimization?▼

No. Performance optimization begins with baseline measurement using built-in browser DevTools, database query logs, and application profilers. Establish initial benchmarks from these sources, then identify bottlenecks and propose optimization proposals before investing in advanced monitoring infrastructure.