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performance-optimization

/performance-optimization

Optymalizuje wydajność aplikacji przy wymaganiach wydajnościowych, podejrzeniu regresji, słabych Core Web Vitals lub wąskich gardłach wskazanych przez profilowanie.

Licencja
MIT
Ostatnia zmiana repozytorium
26.10.2026

Ocena i bezpieczeństwo

100/ 100Klasa: dobry
Format25 / 25
Frontmatter z nazwą i opisem, poprawna nazwa, opis do 1024 znaków, nazwa zgodna z folderem.
Odkrywalność25 / 25
Opis mówi, kiedy użyć skilla, ma sensowną długość i jest w 3. osobie.
Treść35 / 35
Co najmniej 150 słów i do 500 linii, nagłówki, listy kroków, przykłady albo kod.
Higiena15 / 15
Bez zaślepek typu TODO, bez ścieżek Windows, z licencją.
Ryzykobrak sygnałów w skanie
Pliki w paczce
1
Skrypty
0
Komentarze HTML
6
Adresy URL w SKILL.md
3
Przestarzałość

Brak sygnałów. Repozytorium zmienione 26.10.2026, bez odwołań do wycofanych modeli i API.

Licencja

MIT, otwarta: można używać i zmieniać, z zachowaniem informacji o autorze.

Co sprawdzić przed instalacją
  • SKILL.md zawiera komentarze HTML (6). Nie widać ich w podglądzie Markdown, a model je czyta.

Co robi i kiedy

Optymalizuje wydajność aplikacji przy wymaganiach wydajnościowych, podejrzeniu regresji, słabych Core Web Vitals lub wąskich gardłach wskazanych przez profilowanie.

Oryginalny opis (EN)

Optimizes application performance. Use when performance requirements exist, when you suspect performance regressions, or when Core Web Vitals or load times need improvement. Use when profiling reveals bottlenecks that need fixing.

Jak działa

  1. Supporting material availability
  2. Overview
  3. When to Use
  4. Core Web Vitals Targets
  5. The Optimization Workflow
  6. Performance Budget
  7. See Also
  8. Common Rationalizations
  9. Red Flags
  10. Verification
Sekcje z nagłówków SKILL.md, w oryginale · 361 linii, 1 739 słów
Podgląd SKILL.md
---
name: performance-optimization
description: Optimizes application performance. Use when performance requirements exist, when you suspect performance regressions, or when Core Web Vitals or load times need improvement. Use when profiling reveals bottlenecks that need fixing.
risk: critical
source: https://github.com/addyosmani/agent-skills/tree/main/skills/performance-optimization
source_repo: addyosmani/agent-skills
source_type: community
date_added: 2026-07-01
license: MIT
license_source: https://github.com/addyosmani/agent-skills/blob/main/LICENSE
---
## Supporting material availability

This catalog copy contains the inline guidance below, but does not include the following supporting paths. They are external prerequisites, not bundled files:

- `<support-root>/references/performance-checklist.md`

Obtain the required material from the [declared upstream source](https://github.com/addyosmani/agent-skills), or from a user-provided installation of that source. Resolve each path relative to that installation, inspect its contents, and verify any applicable license and execution prerequisites. Do not run a command or claim a referenced procedure was followed until its required file exists. Do not fabricate the missing scripts or treat an unrelated file with the same name as equivalent. Independent steps fully documented here can proceed within the user’s authorized scope; report any dependent step as unavailable.


# Performance Optimization

## Overview

Measure before optimizing. Performance work without measurement is guessing — and guessing leads to premature optimization that adds complexity without improving what matters. Profile first, identify the actual bottleneck, fix it, measure again. Optimize only what measurements prove matters.

## When to Use

- Performance requirements exist in the spec (load time budgets, response time SLAs)
- Users or monitoring report slow behavior
- Core Web Vitals scores are below thresholds
- You suspect a change introduced a regression
- Building features that handle large datasets or high traffic

**When NOT to use:** Don't optimize before you have evidence of a problem. Premature optimization adds complexity that costs more than the performance it gains.

## Core Web Vitals Targets

| Metric | Good | Needs Improvement | Poor |
|--------|------|-------------------|------|
| **LCP** (Largest Contentful Paint) | ≤ 2.5s | ≤ 4.0s | > 4.0s |
| **INP** (Interaction to Next Paint) | ≤ 200ms | ≤ 500ms | > 500ms |
| **CLS** (Cumulative Layout Shift) | ≤ 0.1 | ≤ 0.25 | > 0.25 |

## The Optimization Workflow

```
1. MEASURE  → Establish baseline with real data
2. IDENTIFY → Find the actual bottleneck (not assumed)
3. FIX      → Address the specific bottleneck
4. VERIFY   → Measure again, confirm improvement
5. GUARD    → Add monitoring or tests to prevent regression
```

### Step 1: Measure

Two complementary approaches — use both:

- **Synthetic (Lighthouse, DevTools Performance tab):** Controlled conditions, reproducible. Best for CI regression detection and isolating specific issues.
- **RUM (web-vitals library, CrUX):** Real user data in real conditions. Required to validate that a fix actually improved user experience.

**Frontend:**
```bash
# Synthetic: Lighthouse in Chrome DevTools (or CI)
# Chrome DevTools → Performance tab → Record
# Chrome DevTools MCP → Performance trace

# RUM: Web Vitals library in code
import { onLCP, onINP, onCLS } from 'web-vitals';

onLCP(console.log);
onINP(console.log);
onCLS(console.log);
```

**Backend:**
```bash
# Response time logging
# Application Performance Monitoring (APM)
# Database query logging with timing

# Simple timing
console.time('db-query');
const result = await db.query(...);
console.timeEnd('db-query');
```

### Where to Start Measuring

Use the symptom to decide what to measure first:

```
What is slow?
├── First page load
│   ├── Large bundle? --> Measure bundle size, check code splitting
│   ├── Slow server response? --> Measure TTFB in DevTools Network waterfall
│   │   ├── DNS long? --> Add dns-prefetch / preconnect for known origins
│   │   ├── TCP/TLS long? --> Enable HTTP/2, check edge deployment, keep-alive
│   │   └── Waiting (server) long? --> Profile backend, check queries and caching
│   └── Render-blocking resources? --> Check network waterfall for CSS/JS blocking
├── Interaction feels sluggish
│   ├── UI freezes on click? --> Profile main thread, look for long tasks (>50ms)
│   ├── Form input lag? --> Check re-renders, controlled component overhead
│   └── Animation jank? --> Check layout thrashing, forced reflows
├── Page after navigation
│   ├── Data loading? --> Measure API response times, check for waterfalls
│   └── Client rendering? --> Profile component render time, check for N+1 fetches
└── Backend / API
    ├── Single endpoint slow? --> Profile database queries, check indexes
    ├── All endpoints slow? --> Check connection pool, memory, CPU
    └── Intermittent slowness? --> Check for lock contention, GC pauses, external deps
```

### Step 2: Identify the Bottleneck

Common bottlenecks by category:

**Frontend:**

| Symptom | Likely Cause | Investigation |
|---------|-------------|---------------|
| Slow LCP | Large images, render-blocking resources, slow server | Check network waterfall, image sizes |
| High CLS | Images without dimensions, late-loading content, font shifts | Check layout shift attribution |
| Poor INP | Heavy JavaScript on main thread, large DOM updates | Check long tasks in Performance trace |
| Slow initial load | Large bundle, many network requests | Check bundle size, code splitting |

**Backend:**

| Symptom | Likely Cause | Investigation |
|---------|-------------|---------------|
| Slow API responses | N+1 queries, missing indexes, unoptimized queries | Check database query log |
| Memory growth | Leaked references, unbounded caches, large payloads | Heap snapshot analysis |
| CPU spikes | Synchronous heavy computation, regex backtracking | CPU profiling |
| High latency | Missing caching, redundant computation, network hops | Trace requests through the stack |

### Step 3: Fix Common Anti-Patterns

#### N+1 Queries (Backend)

```typescript
// BAD: N+1 — one query per task for the owner
const tasks = await db.tasks.findMany();
for (const task of tasks) {
  task.owner = await db.users.findUnique({ where: { id: task.ownerId } });
}

// GOOD: Single query with join/include
const tasks = await db.tasks.findMany({
  include: { owner: true },
});
```

#### Unbounded Data Fetching

```typescript
// BAD: Fetching all records
const allTasks = await db.tasks.findMany();

// GOOD: Paginated with limits
const tasks = await db.tasks.findMany({
  take: 20,
  skip: (page - 1) * 20,
  orderBy: { createdAt: 'desc' },
});
```

#### Missing Image Optimization (Frontend)

```html
<!-- BAD: No dimensions, no format optimization -->
<img src="/hero.jpg" />

<!-- GOOD: Hero / LCP image — art direction + resolution switching, high priority -->
<!--
  Two techniques combined:
  - Art direction (media): different crop/composition per breakpoint
  - Resolution switching (srcset + sizes): right file size per screen density
-->
<picture>
  <!-- Mobile: portrait crop (8:10) -->
  <source
    media="(max-width: 767px)"
    srcset="/hero-mobile-400.avif 400w, /hero-mobile-800.avif 800w"
    sizes="100vw"
    width="800"
    height="1000"
    type="image/avif"
  />
  <source
    media="(max-width: 767px)"
    srcset="/hero-mobile-400.webp 400w, /hero-mobile-800.webp 800w"
    sizes="100vw"
    width="800"
    height="1000"
    type="image/webp"
  />
  <!-- Desktop: landscape crop (2:1) -->
  <source
    srcset="/hero-800.avif 800w, /hero-1200.avif 1200w, /hero-1600.avif 1600w"
    sizes="(max-width: 1200px) 100vw, 1200px"
    width="1200"
    height="600"
    type="image/avif"
  />
  <source
    srcset="/hero-800.webp 800w, /hero-1200.webp 1200w, /hero-1600.webp 1600w"
    sizes="(max-width: 1200px) 100vw, 1200px"
    width="1200"
    height="600"
    type="image/webp"
  />
  <img
    src="/hero-desktop.jpg"
    width="1200"
    height="600"
    fetchpriority="high"
    alt="Hero image description"
  />
</picture>

<!-- GOOD: Below-the-fold image — lazy loaded + async decoding -->
<img
  src="/content.webp"
  width="800"
  height="400"
  loading="lazy"
  decoding="async"
  alt="Content image description"
/>
```

#### Unnecessary Re-renders (React)

```tsx
// BAD: Creates new object on every render, causing children to re-render
function TaskList() {
  return <TaskFilters options={{ sortBy: 'date', order: 'desc' }} />;
}

// GOOD: Stable reference
const DEFAULT_OPTIONS = { sortBy: 'date', order: 'desc' } as const;
function TaskList() {
  return <TaskFilters options={DEFAULT_OPTIONS} />;
}

// Use React.memo for expensive components
const TaskItem = React.memo(function TaskItem({ task }: Props) {
  return <div>{/* expensive render */}</div>;
});

// Use useMemo for expensive computations
function TaskStats({ tasks }: Props) {
  const stats = useMemo(() => calculateStats(tasks), [tasks]);
  return <div>{stats.completed} / {stats.total}</div>;
}
```

#### Large Bundle Size

```typescript
// Modern bundlers (Vite, webpack 5+) handle named imports with tree-shaking automatically,
// provided the dependency ships ESM and is marked `sideEffects: false` in package.json.
// Profile before changing import styles — the real gains come from splitting and lazy loading.

// GOOD: Dynamic import for heavy, rarely-used features
const ChartLibrary = lazy(() => import('./ChartLibrary'));

// GOOD: Route-level code splitting wrapped in Suspense
const SettingsPage = lazy(() => import('./pages/Settings'));

function App() {
  return (
    <Suspense fallback={<Spinner />}>
      <SettingsPage />
    </Suspense>
  );
}
```

#### Missing Caching (Backend)

```typescript
// Cache frequently-read, rarely-changed data
const CACHE_TTL = 5 * 60 * 1000; // 5 minutes
let cachedConfig: AppConfig | null = null;
let cacheExpiry = 0;

async function getAppConfig(): Promise<AppConfig> {
  if (cachedConfig && Date.now() < cacheExpiry) {
    return cachedConfig;
  }
  cachedConfig = await db.config.findFirst();
  cacheExpiry = Date.now() + CACHE_TTL;
  return cachedConfig;
}

// HTTP caching headers for static assets
app.use('/static', express.static('public', {
  maxAge: '1y',           // Cache for 1 year
  immutable: true,        // Never revalidate (use content hashing in filenames)
}));

// Cache-Control for API responses
res.set('Cache-Control', 'public, max-age=300'); // 5 minutes
```

## Performance Budget

Set budgets and enforce them:

```
JavaScript bundle: < 200KB gzipped (initial load)
CSS: < 50KB gzipped
Images: < 200KB per image (above the fold)
Fonts: < 100KB total
API response time: < 200ms (p95)
Time to Interactive: < 3.5s on 4G
Lighthouse Performance score: ≥ 90
```

**Enforce in CI:**
```bash
# Bundle size check
npx bundlesize --config bundlesize.config.json

# Lighthouse CI
npx lhci autorun
```

## See Also

For detailed performance checklists, optimization commands, and anti-pattern reference, see `references/performance-checklist.md`.


## Common Rationalizations

| Rationalization | Reality |
|---|---|
| "We'll optimize later" | Performance debt compounds. Fix obvious anti-patterns now, defer micro-optimizations. |
| "It's fast on my machine" | Your machine isn't the user's. Profile on representative hardware and networks. |
| "This optimization is obvious" | If you didn't measure, you don't know. Profile first. |
| "Users won't notice 100ms" | Research shows 100ms delays impact conversion rates. Users notice more than you think. |
| "The framework handles performance" | Frameworks prevent some issues but can't fix N+1 queries or oversized bundles. |

## Red Flags

- Optimization without profiling data to justify it
- N+1 query patterns in data fetching
- List endpoints without pagination
- Images without dimensions, lazy loading, or responsive sizes
- Bundle size growing without review
- No performance monitoring in production
- `React.memo` and `useMemo` everywhere (overusing is as bad as underusing)

## Verification

After any performance-related change:

- [ ] Before and after measurements exist (specific numbers)
- [ ] The specific bottleneck is identified and addressed
- [ ] Core Web Vitals are within "Good" thresholds
- [ ] Bundle size hasn't increased significantly
- [ ] No N+1 queries in new data fetching code
- [ ] Performance budget passes in CI (if configured)
- [ ] Existing tests still pass (optimization didn't break behavior)

## Limitations

- Use this skill only when the task clearly matches its upstream source and local project context.
- Verify commands, generated code, dependencies, credentials, and external service behavior before applying changes.
- Do not treat examples as a substitute for environment-specific tests, security review, or user approval for destructive or costly actions.

Wersje

RepozytoriumWynikLicencja
Ta strona · FrancoStino/opencode-skills-collection100MIT
zeative/satgas100AGPL-3.0
TheAstroByte/astrobyte-agent-skills100MIT
sanity-io/sanity100MIT
magnus919/agent-skills100MIT
drvoss/everything-copilot-cli100MIT
atc-net/atc-agentic-toolkit100MIT
DnsQueen/orcinus-skills100MIT
usermahiro/opencodee100MIT

Migawka bazy z 13.11.2026 · wersja paczki 900eae5a37dc (skrót SHA-256 całej paczki)

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