Apply React and Next.js performance optimization guidelines from Vercel Engineering — 40+ rules covering components, data fetching, bundle optimization, and rendering. Triggers on React components, Next.js pages, bundle optimization, performance improvements, refactoring React code.
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Comprehensive performance optimization guide for React and Next.js applications, containing 40+ rules across 8 categories. Rules are prioritized by impact to guide automated refactoring and code generation.
Reference these guidelines when:
Rules are prioritized by impact:
| Priority | Category | Impact |
|---|---|---|
| 1 | Eliminating Waterfalls | CRITICAL |
| 2 | Bundle Size Optimization | CRITICAL |
| 3 | Server-Side Performance | HIGH |
| 4 | Client-Side Data Fetching | MEDIUM-HIGH |
| 5 | Re-render Optimization | MEDIUM |
| 6 | Rendering Performance | MEDIUM |
| 7 | JavaScript Performance | LOW-MEDIUM |
| 8 | Advanced Patterns | LOW |
Eliminate Waterfalls:
Promise.all() for independent async operationsbetter-all for partial dependenciesReduce Bundle Size:
next/dynamic for heavy componentsReact.cache() for per-request deduplicationstartTransition for non-urgent updatescontent-visibility: auto for long lists? : not &&)toSorted() instead of sort() for immutabilityFull documentation with code examples is available in:
references/react-performance-guidelines.md - Complete guide with all patternsTo look up a specific pattern, grep the references:
grep -l "suspense" references/
grep -l "barrel" references/
grep -l "swr" references/
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Search academic papers, build literature reviews, and synthesize research findings — combines Exa search (publication category, domain and date filters) with arxiv-mcp-server for paper discovery, download, and deep analysis. Triggers on academic paper, literature review, research synthesis, arxiv, find papers, scholarly search.
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Automates browser interactions for web testing, form filling, screenshots, and data extraction. Use when the user needs to navigate websites, interact with web pages, fill forms, take screenshots, test web applications, or extract information from web pages.
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This skill should be used when creating, auditing, or maintaining AGENTS.md files and Codex CLI configuration for any project—including initializing AGENTS.md for cross-agent compatibility (Codex, Cursor, Copilot, Devin, Jules, Amp, Gemini CLI), generating config.toml or .rules files, scaffolding .agents/skills/, converting CLAUDE.md to AGENTS.md, or auditing existing agent configs for bloat and staleness. Complementary to codex-orchestrator (which executes subagents; this skill creates the config files they consume).
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Academic research skill for Biblical Hebrew, Semitic linguistics, cuneiform studies, and comparative Ancient Near Eastern research. Provides Sefaria API for Hebrew Bible, CDLI/ORACC for cuneiform databases, and web discovery via Omnisearch, Exa, Firecrawl, and Obscura for finding scholarly sources across JSTOR, Perseus, Persée, Google Scholar, and academia.edu. Triggers on Hebrew quotes, cuneiform, Sefaria, ANE research, Minoan, search for scholarship, find papers, literature review, scholarly search, academic search, Genesis/Tehom, Ugaritic, Talmudic sources, extract from PDF, OCR academic.
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Build comprehensive ARCHITECTURE.md files following matklad's canonical guidelines — bird's-eye views, ASCII/Mermaid diagrams, codemaps, invariants, and layer boundaries. Triggers on document the architecture, create ARCHITECTURE.md, map this codebase, architectural overview.
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Generate physically-based atmospheric scattering shaders — sky domes, planetary atmospheres, LUT-optimized pipelines, depth-aware post-processing. Four modes — sky-dome, atmosphere-post, planet, lut. Triggers on atmospheric scattering, sky shader, sunset rendering, planet atmosphere, Rayleigh scattering, Mie scattering, volumetric sky, sky dome, atmosphere post-processing, aerial perspective, transmittance LUT, sky rendering, realistic sky, planetary rendering.
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