Skill UI

PyTDC (Therapeutics Data Commons) is an open-science platform providing comprehensive, AI-ready datasets and benchmarks for the entire drug discovery and development pipeline. It supports single-instance prediction (e.g., ADME, toxicity), multi-instance prediction (DTI, DDI, PPI), and novel molecule generation (MolGen). Use this skill for benchmarking machine learning models and predicting complex biomedical properties.

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.

A comprehensive AI tutor for K-12 students covering Physics, Chemistry, and Biology. This skill employs Socratic Questioning, the 5E Model, and phenomenon-based learning to guide students toward scientific discovery. It adapts to various curricula (US, IB, Chinese) and focuses on building deep, conceptual understanding rather than simply providing answers.

A powerful command-line interface (CLI) tool, modeled after kubectl/docker, designed for comprehensive management of GPU compute jobs on the Qizhi platform. It supports job submission (interactive/non-interactive), resource discovery, node availability checking, and batch processing for distributed training and HPC workloads. Ideal for machine learning engineers and data scientists running large-scale scientific computations.

Rowan is a cloud-native workflow platform accessed via Python API, designed for molecular simulation, medicinal chemistry, and structure-based drug design. It enables programmatic batch screening of properties (like pKa, descriptors), conformer generation, molecular docking, and protein cofolding without requiring local HPC/GPU infrastructure. Ideal for scalable, multi-step chemistry pipelines in drug discovery.

A comprehensive resource hub for ML researchers working in scientific domains such as biology, chemistry, genetics, and medicine. It provides a curated catalog of high-signal datasets, pre-trained models, and interactive demos, streamlining the discovery and use of specialized AI/ML resources beyond general search.

This skill provides a comprehensive, step-by-step workflow for generating complete Power BI reports from scratch using the pbir CLI. It covers everything from initial model discovery and defining design briefs to visual placement, formatting, filtering, validation, and final publishing in Fabric or Power BI Desktop. It ensures best practices are followed to create robust, professional, and interactive dashboards.