Skill UI

Enables Claude to examine EXPLAIN plans, spot slow queries or missing indexes, and deliver concrete optimization steps—ideal for improving database query speed and resource usage when performance issues arise.

Activation-aware weight quantization that compresses 7B-70B models to 4-bit with minimal accuracy loss, delivering ~3x inference speedups and memory reductions for constrained GPU deployments while integrating with vLLM and Marlin kernels.

This comprehensive guide details how to utilize the Bun runtime for modern, high-performance JavaScript and TypeScript development. It covers everything from initial setup and project scaffolding to advanced package management, running code, and leveraging built-in APIs like file system operations. It is designed for developers migrating from Node.js seeking superior speed and native tooling.

This skill is designed to enhance the reading efficiency of AI-generated text, such as responses from large language models. It utilizes Rapid Serial Visual Presentation (RSVP) combined with Spritz-style Optimal Reading Pace (ORP) highlighting. By employing this method, users can significantly increase their reading speed to over 600 WPM, allowing for rapid consumption and comprehension of vast amounts of digital text.

This guide provides a comprehensive method for optimizing CodeRabbit's review process, focusing on improving speed, relevance, and the signal-to-noise ratio. Learn best practices for managing PR size, selecting the right review profile (e.g., 'assertive' vs. 'chill'), using path instructions to guide feedback, and filtering out low-value files. Ideal for teams looking to reduce review fatigue and ensure consistent code quality checks.

A comprehensive guide designed to diagnose and optimize Cursor IDE performance. Learn advanced strategies for minimizing memory usage, speeding up indexing, tuning AI features, and managing large codebases to eliminate lag and maximize development efficiency.

Master Cursor's AI-powered Tab completion system, generating instant, context-aware 'ghost text' suggestions. This tool predicts the next code lines based on the current file, open tabs, and even comments, allowing developers to accept or modify suggestions with minimal effort. It is designed to significantly boost coding speed and maintain coding consistency.

This guide provides advanced techniques to optimize Deepgram API performance. Learn how to preprocess audio using ffmpeg (resampling, noise reduction), select optimal transcription models (speed vs. accuracy), and implement efficient streaming or parallel batch processing to achieve high throughput and low latency.

Guides engineers through DeepSpeed distributed training and NVMe I/O optimizations, covering ZeRO, pipeline parallelism, mixed precision, and DeepNVMe handles for synchronous and asynchronous tensor storage.

A comprehensive guide for optimizing Documenso usage costs and managing subscription efficiency. Covers selecting the optimal plan tier (Free to Enterprise/Self-hosted), implementing templates to boost development speed, monitoring usage patterns, and analyzing self-hosting costs to ensure maximum resource efficiency without compromising functionality.

FAISS (Facebook AI Similarity Search) is a library designed for efficient similarity search and clustering of dense vectors. It supports indexing and searching on billions of vectors at scale, featuring GPU acceleration and multiple index types (Flat, IVF, HNSW, PQ) to balance speed and accuracy. It is essential for building high-performance, large-scale applications requiring fast k-NN retrieval or pure vector similarity matching, especially in fields like RAG and recommendation systems.

This comprehensive guide details advanced techniques to significantly boost Firecrawl scraping speed and efficiency. Learn how to optimize performance by selecting the most efficient output formats (e.g., Markdown over HTML), implementing URL caching, utilizing batch scraping for multiple URLs, and tuning delay parameters for dynamic Single Page Applications (SPAs). Mastering these methods is crucial for building high-throughput, cost-effective web scraping pipelines.