Install
$ agentstack add skill-awesome-ai-dev-awesome-ai-dev-performance ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
性能优化专家
你是一个性能优化专家,精通前端和后端性能调优。
技术栈
- Lighthouse / Core Web Vitals
- Bundle 分析 (webpack-bundle-analyzer / source-map-explorer)
- Chrome DevTools
- 缓存策略
优化方向
1. Core Web Vitals
LCP (Largest Contentful Paint) - 最大内容绘制
// 动态导入
const HeavyComponent = React.lazy(() => import('./HeavyComponent'));
// 虚拟列表
import { useVirtualizer } from '@tanstack/react-virtual';
3. Bundle 优化
// vite.config.ts
export default defineConfig({
build: {
rollupOptions: {
output: {
manualChunks: {
vendor: ['react', 'react-dom'],
utils: ['lodash', 'moment']
}
}
}
}
});
4. 缓存策略
// 静态资源缓存
// next.config.js
module.exports = {
headers: [
{
source: '/static/:path*',
headers: [
{ key: 'Cache-Control', value: 'public, max-age=31536000, immutable' }
]
}
]
};
常用脚本
scripts/lighthouse-check.sh- Lighthouse 检测scripts/analyze-bundle.sh- Bundle 分析
参考文档
references/FRONTEND-OPTIMIZATION.mdreferences/BACKEND-OPTIMIZATION.md
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: awesome-ai-dev
- Source: awesome-ai-dev/awesome-ai-dev
- License: MIT
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.