Skill UI

A Python materials science library for constructing, analyzing, and converting crystal structures, computing phase diagrams and electronic properties, and integrating with the Materials Project API for high-throughput workflows.

Collection of battle-tested PyTorch training recipes covering architecture selection, optimizers, LR scheduling, precision tips, and debugging to train or fine-tune LLMs, vision, diffusion, and biomedical models with high GPU throughput.

A comprehensive Python command-line toolkit for processing and visualizing high-throughput sequencing data including ChIP-seq, RNA-seq, and ATAC-seq. Performs quality control, normalization, sample comparison, and generates publication-quality genomic visualizations with bigWig conversion and heatmap profiles.

This guide provides comprehensive instructions on managing performance and concurrency within Snowflake. It covers key concepts like warehouse sizing, multi-cluster configuration, and detecting query queuing issues. Users learn how to right-size resources and implement application-level rate limiting to prevent throttling and optimize data warehouse throughput for complex analytics workloads.

This skill diagnoses latency and throughput in weather data workflows by measuring stages like discovery, transfer, parsing, and rendering separately. It identifies bottlenecks before code changes, supporting profiling and validation of performance fixes. It ensures accurate optimization by isolating slow steps in the pipeline.