Skill UI

An expert guide for building high-performance, cross-platform games using Unity 6 LTS. This skill covers advanced C# programming (DOTS, Job System), modern rendering pipelines (URP/HDRP), comprehensive performance optimization (Profiling, Culling), advanced game architecture (ECS, MVC), and networked multiplayer implementation. Ideal for professional game developers tackling complex, large-scale projects.

TorchDrug is a PyTorch-native toolbox for building graph neural networks tailored to molecules, proteins, and biomedical knowledge graphs, covering property prediction, generation, retrosynthesis, and knowledge graph reasoning with curated datasets and models.

A comprehensive utility for handling asset loading within Three.js environments. It supports various formats, including GLTF/GLB models, textures, HDR environments, and complex image assets. Features include robust asynchronous loading patterns, progress tracking via LoadingManager, and detailed configuration for PBR materials and environment mapping.

A comprehensive guide covering texture management in Three.js. Learn how to load various texture types (regular, data, video, KTX2), configure critical properties like UV mapping, color space, wrapping modes, filtering, and mipmapping. Includes advanced workflows for generating and utilizing cubemaps and HDR environment maps.

TorchDrug is a comprehensive PyTorch-based ML toolbox designed for molecular and protein science. It leverages Graph Neural Networks (GNNs) to tackle complex tasks including molecular property prediction, protein structure modeling, drug-target binding prediction, knowledge graph reasoning, and de novo molecular generation. It provides robust capabilities for accelerating drug discovery research.

This技能 is used when analyzing complex propositions, debating, or reviewing arguments within the CrossFrame Suite. It helps users deconstruct claims into testable arguments, identifying hidden premises, strongest counterarguments, evidence requirements, and conditions for withdrawal, ensuring conclusions are robust and non-judgmental.