Performance

Performance

Comprehensive performance optimization patterns for frontend, backend, and LLM inference.

Quick Reference

Total: 23 rules across 9 categories

Core Web Vitals

Google's Core Web Vitals with 2026 stricter thresholds.

2026 Thresholds

Render Optimization

React render performance patterns for React 19+.

Lazy Loading

Code splitting and lazy loading with React.lazy and Suspense.

Image Optimization

Production image optimization for modern web applications.

Next.js Image component usage and the v16 image config defaults are first-party territory; see "Upstream coverage (do not restate)" below.

Profiling & Backend

Profiling tools and backend optimization patterns.

LLM Inference

High-performance LLM inference with vLLM, quantization, and speculative decoding.

Caching

Backend Redis caching and LLM prompt caching for cost savings and performance.

Query & Data Fetching

TanStack Query v5 patterns for prefetching and optimistic updates.

Sustainability

Digital sustainability patterns for reducing carbon footprint and energy usage.

Local Profiling Target

When profiling a local app (Lighthouse, Core Web Vitals, bundle analysis), use Portless named URLs for stable, self-documenting targets:

bashCopy code
# Discover services
portless list
# app → app.localhost (port 3000)

# Profile with agent-browser (preferred for visual metrics)
agent-browser open "https://app.localhost"
agent-browser profiler start
agent-browser wait --load networkidle
agent-browser profiler stop /tmp/profile.json

# Lighthouse via agent-browser
agent-browser open "https://app.localhost"
agent-browser screenshot /tmp/perf-baseline.png

# Or direct Lighthouse CLI
npx lighthouse https://app.localhost --output=json --output-path=/tmp/lighthouse.json

Named URLs are stable across restarts and self-documenting in performance reports. Install Portless with npm i -g portless.

Quick Start Example

tsxCopy code
// LCP: Priority hero image with SSR
import Image from 'next/image';

export default async function Page() {
  const data = await fetchHeroData();
  return (
    <Image
      src={data.heroImage}
      alt="Hero"
      priority
      placeholder="blur"
      sizes="100vw"
      fill
    />
  );
}

Key Decisions

Common Mistakes

1. Client-side fetching LCP content (delays render)
2. Images without explicit dimensions (causes CLS)
3. Lazy loading LCP images (delays largest paint)
4. Heavy computation in event handlers (blocks INP)
5. Layout-shifting animations (use transform instead)
6. Lazy loading tiny components < 5KB (overhead > savings)
7. Missing error boundaries on lazy components
8. Using GPTQ without calibration data
9. Not benchmarking actual workload patterns
10. Only measuring in lab environment (need RUM)

Related Skills

• ork:react-server-components-framework - Server-first rendering
• ork:vite-advanced - Build optimization
• browser-tools - Visual profiling with agent-browser + Portless
• caching - Cache strategies for responses
• ork:monitoring-observability - Production monitoring and alerting
• ork:database-patterns - Query and index optimization
• ork:llm-integration - Local inference with Ollama

Capability Details

lcp-optimization

Keywords: LCP, largest-contentful-paint, hero, preload, priority, SSR Solves:

• Optimize hero image loading
• Server-render critical content
• Preload and prioritize LCP resources

inp-optimization

Keywords: INP, interaction, responsiveness, long-task, transition, yield Solves:

• Break up long tasks with scheduler.yield
• Defer non-urgent updates with useTransition
• Optimize event handler performance

cls-prevention

Keywords: CLS, layout-shift, dimensions, aspect-ratio, font-display Solves:

• Reserve space for dynamic content
• Prevent font flash and image pop-in
• Use transform for animations

react-compiler

Keywords: react-compiler, auto-memo, memoization, React 19 Solves:

• Enable automatic memoization
• Identify when manual memoization needed
• Verify compiler is working

virtualization

Keywords: virtual, TanStack, large-list, scroll, overscan Solves:

• Render 100+ item lists efficiently
• Dynamic height virtualization
• Window scrolling patterns

lazy-loading

Keywords: React.lazy, Suspense, code-splitting, dynamic-import Solves:

• Route-based code splitting
• Component lazy loading with error boundaries
• Prefetch on hover and viewport

image-optimization

Keywords: next/image, AVIF, WebP, responsive, blur-placeholder Solves:

• Next.js Image component patterns
• Format selection and quality settings
• Responsive sizing and CDN configuration

profiling

Keywords: profiler, flame-graph, py-spy, DevTools, bundle-analyzer Solves:

• Profile React renders and backend code
• Generate and interpret flame graphs
• Analyze and optimize bundle size

inp-advanced

Keywords: INP, scheduler-yield, layout-thrashing, third-party-scripts, requestAnimationFrame Solves:

• Break long tasks with scheduler.yield()
• Audit and defer blocking third-party scripts
• Avoid synchronous layout thrashing in event handlers
• Optimize form submissions, dropdowns, accordions, filters

sustainability

Keywords: sustainability, carbon-footprint, page-weight, green-ux, dark-mode, lazy-loading Solves:

• Enforce page weight budgets (< 1MB)
• Eliminate auto-playing videos and heavy decorative animations
• Serve optimized image formats (AVIF/WebP)
• Implement cursor-based pagination to prevent over-fetching

llm-inference

Keywords: vllm, quantization, speculative-decoding, inference, throughput Solves:

• Deploy LLMs with vLLM for production
• Choose quantization method for hardware
• Accelerate generation with speculative decoding

Upstream coverage (do not restate)

These topics used to be restated in this skill's references, checklists, and examples. They are owned by first-party sources now; consult those instead of re-adding tutorials here. The ork-specific floors and scars that survived the cut live in references/ork-delta.md.

References

Load on demand with Read("references/<file>"):

Real production before/after evidence (cache hierarchy, cost math): examples/orchestkit-performance-wins.md.