Skill UI

RDKit delivers a Python-based cheminformatics toolkit for parsing SMILES/SDF, computing descriptors, generating 2D/3D coordinates, fingerprinting, searching substructures, managing reactions, and visualizing molecules, ideal for drug discovery and computational chemistry workflows.

Cloud-native Rowan orchestrates medicinal chemistry and molecular modeling pipelines via a Python API, offering pKa prediction, docking, descriptors, dynamics, and AI-driven structure workflows for scalable batch screening without local HPC.

This skill analyzes Active Directory (AD) Access Control Lists (ACLs) to detect dangerous misconfigurations. It uses the ldap3 Python library to query domain controllers, parse security descriptors (SDDL), and identify instances where non-privileged users or groups are granted dangerous permissions like GenericAll, WriteDACL, or WriteOwner on sensitive objects. Essential for security incident response and privilege escalation path discovery.

Datamol is a lightweight, Pythonic wrapper over RDKit, simplifying complex molecular operations. It provides robust features for structure standardization, calculating molecular descriptors (like MW, LogP), generating fingerprints, analyzing 3D conformers, and handling multi-format I/O (SMILES, SDF, JSON). Ideal for computational chemistry, drug discovery, and large-scale cheminformatics data processing, with built-in parallelization and cloud storage support.

DeepChem is a comprehensive Python library designed for applying machine learning to chemical, biological, and materials science datasets. It enables molecular property prediction (e.g., ADMET, toxicity), drug discovery, and materials design. The skill supports diverse featurization methods (fingerprints, descriptors, graph representations), handling various data formats like SMILES and SDF, and implementing advanced GNN models for complex scientific research.

RDKit is a powerful, comprehensive cheminformatics library providing Python APIs for molecular structure manipulation and analysis. It supports reading and writing multiple molecular formats (SMILES, SDF, MOL, InChI), calculating chemical descriptors (MW, LogP, TPSA), performing substructure searching, handling stereochemistry, and modeling chemical reactions. This toolkit is essential for computational chemistry, drug discovery, and advanced cheminformatics research.

This skill guides the systematic migration of Java enterprise code from the legacy `javax.*` namespace to the modern `jakarta.*` namespace. It is essential for developers upgrading applications to Jakarta EE 10 or running on Tomcat 11+. The process covers updating imports, modifying dependency coordinates in build files (pom.xml), and adapting web deployment descriptors.