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Get Started Free →Comprehensive React and Next.js performance optimization guide with 40+ rules for eliminating waterfalls, optimizing bundles, and improving rendering. Use when optimizing React apps, reviewing performance, or refactoring components.
.claude/skills/davila7-react-best-practices/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-01 | ✗→✓ | ▲ Improved | 13% | 0% |
| case-02 | ✓→✓ | = Same ✓ | 37% | 0% |
| case-03 | ✓→✓ | = Same ✓ | 14% | 0% |
| case-04 | ✓→✓ | = Same ✓ | 45% | 0% |
| case-05 | ✓→✓ | = Same ✓ | 56% | 0% |
Comprehensive performance optimization guide for React and Next.js applications with 40+ rules organized by impact level. Designed to help developers eliminate performance bottlenecks and follow best practices.
Use React Best Practices when:
Key areas covered:
Parallel data fetching:
typescriptconst [user, posts, comments] = await Promise.all([ fetchUser(), fetchPosts(), fetchComments() ])
Direct imports:
tsx// ❌ Loads entire library import { Check } from 'lucide-react' // ✅ Loads only what you need import Check from 'lucide-react/dist/esm/icons/check'
Dynamic components:
tsximport dynamic from 'next/dynamic' const MonacoEditor = dynamic( () => import('./monaco-editor'), { ssr: false } )
The complete performance guidelines are available in the references folder:
Each rule includes:
Waterfalls are the #1 performance killer. Each sequential await adds full network latency.
Reducing initial bundle size improves Time to Interactive and Largest Contentful Paint.
Optimize server-side rendering and data fetching.
Automatic deduplication and efficient data fetching patterns.
Reduce unnecessary re-renders to minimize wasted computation.
Optimize the browser rendering process.
Micro-optimizations for hot paths.
Specialized techniques for edge cases.
When optimizing a React application:
❌ Don't:
✅ Do:
v0.1.0 (January 2026)
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→pass | 21,322 | 17,798 | -17% | 1 | 1 | 0% | 4,087 | 4,622 | +13% | 0 | 0 | — |
case-02 | pass→pass | 10,974 | 6,601 | -40% | 1 | 1 | 0% | 2,034 | 2,788 | +37% | 0 | 0 | — |
case-03 | pass→pass | 11,701 | 4,614 | -61% | 1 | 1 | 0% | 2,056 | 2,335 | +14% | 0 | 0 | — |
case-04 | pass→pass | 9,663 | 5,279 | -45% | 1 | 1 | 0% | 1,754 | 2,551 | +45% | 0 | 0 | — |
case-05 | pass→pass | 9,244 | 7,169 | -22% | 1 | 1 | 0% | 1,801 | 2,801 | +56% | 0 | 0 | — |
case-06 | pass→pass | 13,467 | 13,445 | -0% | 1 | 1 | 0% | 2,475 | 4,054 | +64% | 0 | 0 | — |
case-07 | pass→pass | 11,535 | 11,341 | -2% | 1 | 1 | 0% | 2,090 | 3,619 | +73% | 0 | 0 | — |
case-08 | pass→pass | 9,453 | 7,571 | -20% | 1 | 1 | 0% | 1,681 | 2,881 | +71% | 0 | 0 | — |
case-09 | pass→pass | 4,137 | 6,275 | +52% | 1 | 1 | 0% | 723 | 2,702 | +274% | 0 | 0 | — |
case-10 | pass→pass | 5,065 | 5,862 | +16% | 1 | 1 | 0% | 892 | 2,629 | +195% | 0 | 0 | — |
case-11 | pass→pass | 5,171 | 13,044 | +152% | 1 | 1 | 0% | 1,051 | 2,591 | +147% | 0 | 0 | — |
case-12 | pass→pass | 8,926 | 7,773 | -13% | 1 | 1 | 0% | 1,536 | 2,832 | +84% | 0 | 0 | — |
case-13 | pass→pass | 11,719 | 8,685 | -26% | 1 | 1 | 0% | 2,039 | 3,165 | +55% | 0 | 0 | — |
case-14 | pass→pass | 16,525 | 9,196 | -44% | 1 | 1 | 0% | 2,649 | 3,220 | +22% | 0 | 0 | — |
case-15 | pass→pass | 14,016 | 12,817 | -9% | 1 | 1 | 0% | 2,521 | 3,890 | +54% | 0 | 0 | — |
case-16 | pass→pass | 4,684 | 4,842 | +3% | 1 | 1 | 0% | 756 | 2,260 | +199% | 0 | 0 | — |
case-17 | pass→pass | 15,366 | 8,087 | -47% | 1 | 1 | 0% | 2,625 | 3,112 | +19% | 0 | 0 | — |
case-18 | pass→pass | 8,817 | 6,516 | -26% | 1 | 1 | 0% | 1,606 | 2,686 | +67% | 0 | 0 | — |
case-19 | pass→pass | 12,803 | 10,823 | -15% | 1 | 1 | 0% | 2,311 | 3,464 | +50% | 0 | 0 | — |
case-20 | pass→pass | 9,204 | 6,475 | -30% | 1 | 1 | 0% | 1,776 | 2,734 | +54% | 0 | 0 | — |
case-21 | pass→pass | 11,551 | 10,328 | -11% | 1 | 1 | 0% | 2,464 | 3,732 | +51% | 0 | 0 | — |
case-22 | pass→pass | 15,660 | 10,723 | -32% | 1 | 1 | 0% | 3,207 | 3,806 | +19% | 0 | 0 | — |
case-23 | pass→pass | 10,743 | 9,228 | -14% | 1 | 1 | 0% | 2,072 | 3,404 | +64% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 23 cases were attempted. The headline lift of +4 percentage points is the difference between those two pass rates over the 23 comparable cases.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.