Skill UI

Guides Avalonia developers through ReactiveUI and Zafiro patterns for building ViewModels, command wiring, declarative SlimWizard flows, auto section discovery, and composition-root coordination.

Automate OpenAI API workflows through the Composio MCP integration, covering text and multimodal responses with structured outputs, embeddings, image generation, and model discovery.

Use AgentFolio to discover, compare, and research autonomous AI agents, frameworks, and tools before building or integrating your own. The directory helps you map capabilities, autonomy models, and deployment patterns while collecting concrete examples for positioning workflows or vendor evaluations.

Retrieve AlphaFold’s AI-predicted protein models via UniProt IDs, download CIF/PDB coordinates, inspect confidence metrics, and feed them into structural analysis or drug-discovery pipelines.

DeepChem is a Python library for molecular machine learning, bundling data loaders, featurizers, splitters, and models so researchers can rapidly predict molecular properties, benchmark on MoleculeNet, or build drug discovery and materials pipelines.

TorchDrug offers PyTorch-native graph neural networks, datasets, and tasks tailored to drug discovery, protein modeling, knowledge graphs, molecular generation, and retrosynthesis, letting researchers define custom GNN architectures for property prediction and synthesis planning.

Query the Monarch Initiative API to explore disease-gene-phenotype associations across species, enabling rare disease gene discovery, phenotype-to-gene mapping, and cross-species modeling via integrated HPO and model organism data.

Guides the discovery of concise RBAC roles through bottom-up clustering, formal concept analysis and graph techniques, transforming sprawling user-permission assignments into least-privilege-aligned role models.