Skill UI

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.

Guides ML engineers through dataset prep, PEFT strategy selection, LoRA/QLoRA adapter setup, training monitoring, and deployment checks for practical LLM fine-tuning, quantization, and adapter merge workflows.

This guide provides comprehensive principles for modern game development, covering engine selection (Unity, Unreal, Godot), platform integration (Steam features, console compliance), input abstraction, and performance optimization techniques. It helps developers make informed decisions when building cross-platform games for PC and console environments.

Expert in designing and implementing advanced Retrieval-Augmented Generation (RAG) pipelines. This role focuses on optimizing the entire information retrieval process—from document chunking and embedding model selection to vector database architectures and hybrid search strategies. The goal is to bridge the gap between raw knowledge documents and accurate LLM understanding, drastically reducing hallucination and enhancing context relevance for enterprise applications.

A comprehensive toolkit for the full software development lifecycle. It guides stack selection using a detailed decision engine, automatically scaffolds complex boilerplate projects across multiple popular stacks (Next.js, MERN, FastAPI, Django), and provides deep code quality analysis. Features include security vulnerability detection, complexity scoring, and dependency auditing, ensuring high-quality development from the start.

This comprehensive guide outlines the core principles for developing immersive Virtual and Augmented Reality (VR/AR) applications. It covers critical aspects such as platform selection (Quest, ARKit, ARCore), mandatory performance metrics (FPS, frame budget), user comfort techniques (motion sickness prevention), and best practices for spatial interaction and world design. Essential reading for engineers building next-generation spatial computing experiences.

This skill acts as a Go ecosystem expert, guiding developers through the process of selecting and vetting production-ready third-party libraries and frameworks for Go projects. It enforces best practices by prioritizing the standard library, ensuring library maturity, and evaluating performance and simplicity to avoid over-engineering. Use this when you need to compare alternatives or choose the optimal dependency for a specific task.

This comprehensive guide details advanced workflows for high-quality video generation using platforms like Runway. Learn essential techniques including advanced prompt engineering (Subject + Action + Setting + Style), optimal model selection (e.g., gen4_turbo), and parameter tuning for duration and aspect ratio. The workflow also demonstrates efficient batch generation for creating multiple, consistent video assets.