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Skill

perf-expert

by hardikpandya

AI Summary

perf-expert is a frontend performance auditing skill that analyzes websites for Core Web Vitals, accessibility, and SEO issues, then provides actionable improvement plans. It's ideal for developers and teams looking to optimize website performance and user experience.

Install

Copy this and paste it into Claude Code, Cursor, or any AI assistant:

I want to install the "perf-expert" skill in my project.

Please run this command in my terminal:
# Install skill into the correct directory
mkdir -p .claude/skills/perf-analyzer && curl --retry 3 --retry-delay 2 --retry-all-errors -o .claude/skills/perf-analyzer/SKILL.md "https://raw.githubusercontent.com/hardikpandya/perf-analyzer/main/SKILL.md"

Then restart Claude Code (or reload the window in Cursor) so the skill is picked up.

Description

Comprehensive frontend performance auditing. Analyzes websites for Core Web Vitals, accessibility, and SEO issues, then delivers a clear actionable improvement plan.

Usage

` /perf-expert # Full audit /perf-expert performance # Performance focus /perf-expert a11y # Accessibility focus /perf-expert seo # SEO focus `

Performance expert

You are a senior frontend performance engineer. When this skill is invoked, conduct a comprehensive audit and deliver an actionable improvement plan.

What you deliver

Every audit must include: • Current state assessment — Run Lighthouse, identify the tech stack, note existing optimizations • Issues found — Categorized by severity (critical, moderate, minor) • Actionable fixes — Specific code changes with file paths and line numbers • Expected impact — What each fix improves and by how much • Priority order — What to fix first for maximum impact

Step 1: Establish baselines

Run Lighthouse and note current scores: `bash npx lighthouse https://yoursite.com --output json --output-path baseline.json ` Extract the metrics that matter: | Metric | Target | Google ranking factor? | |--------|--------|------------------------| | LCP (Largest contentful paint) | < 2.5s | Yes | | INP (Interaction to next paint) | < 200ms | Yes | | CLS (Cumulative layout shift) | < 0.1 | Yes | | TTFB (Time to first byte) | < 800ms | No, but affects LCP |

Discussion

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Health Signals

MaintenanceCommitted 2mo ago
Active
AdoptionUnder 100 stars
11 ★ · Niche
DocsREADME + description
Well-documented

GitHub Signals

Stars11
Forks1
Issues0
Updated2mo ago
View on GitHub
MIT License

My Fox Den

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Works With

Claude Code