Skill UI

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.

A comprehensive guide to mastering AI-powered coding assistance within the IDE. Learn to use the chat panel for conversational debugging and architectural discussion, and utilize inline editing for surgical code refactoring. Features advanced context referencing using @-mentions (e.g., @Files, @Codebase) to improve code understanding and generation accuracy.

This bundle provides a comprehensive framework for diagnosing and fixing common issues when AI code generation is incorrect within Cursor. It systematically covers the root causes of poor suggestions, including context mismanagement (missing, wrong, or overflowing context), model hallucinations, and ambiguous prompting. Use this guide to improve the accuracy and reliability of AI-assisted coding workflows.

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 users through writing, reviewing, and editing documentation with consistent structure, tone, and accuracy; ideal when creating README files, updating docs folders, or refining markdown drafts per contribution standards.

This expert skill specializes in creating comprehensive, maintainable technical documentation directly from existing codebase, configurations, and comments. It can generate various artifacts, including API specifications, system architecture diagrams, detailed user guides, and technical references, ensuring consistency and accuracy using AI-powered analysis and industry best practices. Ideal for building robust documentation pipelines and standardizing documentation across large repositories.

Feature Engineering Toolkit automates creating, selecting, and transforming dataset features to improve machine learning models; use it whenever you need new interactions, automatic selection, scaling, or encoding to boost accuracy and interpretability.

Provides detailed evaluation of machine learning models using plugin metrics to assess accuracy, precision, recall, F1, and other key indicators, helping users compare models and validate performance before deployment.

Provides comprehensive guidance on building robust evaluation frameworks for complex agent systems. It addresses the inherent challenges of non-determinism and multiple valid paths, enabling systematic performance testing, validating context engineering choices, and measuring continuous improvements across multiple quality dimensions (e.g., factual accuracy, tool efficiency).

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.

A comprehensive guide to optimizing Granola's output quality across three dimensions: audio transcription accuracy, AI enhancement quality, and overall processing speed. Learn best practices for hardware setup, ideal meeting habits, and structuring your templates to maximize AI output reliability and efficiency.

A comprehensive toolkit designed to monitor the health and performance of Guidewire InsuranceSuite. It tracks critical operational metrics including claim processing times, policy synchronization rates, billing accuracy, API latency, and batch job statuses. The system provides real-time alerting, structured logging, and health checks to maintain high service level agreements (SLAs) for complex insurance workflows.