Claude Skills Online Marketplace

Automates publication-quality scientific diagrams (e.g., flowcharts, architectures, pathways) when you need journal/poster-ready visuals from a natural-language description.

Automated LLM-driven hypothesis generation and testing for tabular datasets; use when you need systematic exploration of empirical patterns (e.g., fraud detection, content...

Toolkit for protein language models (ESM3 for multimodal generative protein design; ESM C for efficient embeddings). Use when you need sequence/structure/function generation or...

A Pythonic wrapper around RDKit with simplified interfaces and sensible defaults. Preferred for standard drug discovery workflows including SMILES parsing, standardization,...

Mine unstructured clinical text from MIMIC-IV to extract diagnostic logic.

Therapeutics Data Commons (PyTDC) for AI-ready therapeutic ML datasets and benchmarks; use it when you need standardized dataset loading, meaningful splits (e.g.,...

Diffusion-based molecular docking to predict 3D ligand–protein binding poses (blind docking) with confidence scoring; use when you need pose prediction for drug discovery or...

Access ChEA3 and Harmonizome ChEA data for transcription factor enrichment analysis and metadata retrieval. Use when the user needs to perform ChEA3 enrichment analysis on a gene...

Programmatically query the CZ CELLxGENE Census (61M+ cells) when you need cross-tissue, disease, or cell-type expression data for population-scale queries and reference atlas...

Infer gene regulatory networks (GRNs) from gene expression matrices using GRNBoost2 or GENIE3; use when analyzing bulk or single-cell RNA-seq to identify TF→target regulatory...

Model interpretability and explainability using SHAP (SHapley Additive exPlanations). Feature importance, dependence plots, interaction effects, and fairness analysis for any...

Deep generative models for single-cell omics; use when you need probabilistic batch correction (scVI), transfer learning, uncertainty-aware differential expression, or multimodal...

Cloud-based quantum chemistry platform providing a Python API. Preferred for computational chemistry workflows including pKa prediction, geometry optimization, conformational...

Healthcare AI toolkit for clinical ML. EHR processing, clinical prediction (mortality, readmission, drug recommendation), medical coding (ICD/NDC/ATC), signals (EEG/ECG), datasets...

A full-featured computational pathology toolkit for advanced WSI analysis, including multiplexed immunofluorescence (CODEX, Vectra), nuclei segmentation, tissue graph...

Predict neoantigens that may be recognized by the immune system based.

Machine learning toolkit for genomic interval (BED) data; use it when you need to tokenize BED collections and train embeddings for regions/cells/labels, build consensus peak...

Analyze data with using a reproducible workflow, explicit validation, and structured outputs for review-ready interpretation.

PyTorch-native Graph Neural Network framework for molecules and proteins. Suitable for building custom GNN architectures for drug discovery, protein modeling, or knowledge graph...

Use semantic consistency auditor for academic writing workflows that need structured execution, explicit assumptions, and clear output boundaries.