react-native-best-practices
Provides React Native performance optimization guidelines for FPS, TTI, bundle size, memory leaks, re-renders, and animations. Applies to tasks involving Hermes optimization, JS thread blocking, bridg...
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139,042 skills indexed with the new KISS metadata standard.
Provides React Native performance optimization guidelines for FPS, TTI, bundle size, memory leaks, re-renders, and animations. Applies to tasks involving Hermes optimization, JS thread blocking, bridg...
React best-practices reviewer for TSX files. Triggers after editing multiple TSX components to run a condensed quality checklist covering component structure, hooks usage, accessibility, performance,...
React Native renderer for json-render that turns JSON specs into native mobile UIs. Use when working with @json-render/react-native, building React Native UIs from JSON, creating mobile component cata...
React renderer for json-render that turns JSON specs into React components. Use when working with @json-render/react, building React UIs from JSON, creating component catalogs, or rendering AI-generat...
React PDF renderer for json-render. Use when generating PDF documents from JSON specs, working with @json-render/react-pdf, or rendering specs to PDF buffers/streams/files.
React Three Fiber 3D renderer for json-render. Use when working with @json-render/react-three-fiber, building 3D scenes from JSON specs, rendering meshes/lights/models/environments, or integrating Thr...
The actual workflow guides, reference docs, and prompt helpers live inside
The actual skill content (workflow guides, reference docs, prompt helpers)
Where to author new skill content:
globs:
globs:
Research and write a complete blog post
Process multiple keywords automatically in a loop
Schedule a draft blog post for future publication
Research a keyword without writing the full article
View the current keyword queue status and upcoming articles
Publish a draft blog post to Sanity CMS
Cancel the active Super-Leo loop
Feature engineering for text: embeddings, TF-IDF, tokenization, text preprocessing pipelines.
Train NLP models: sentiment, classification, NER, topic modeling.
Analyze text data: distributions, vocabulary, language detection, quality assessment.
Project architecture, structure, and key patterns for the RAG Knowledge Base app
Frontend code patterns for components, pages, and api.ts
Patterns for service modules (ingest, rag, storage, vectorstore)