Discover Agent Skills for data science & ml. Browse 61 skills for Claude, ChatGPT & Codex.
Accesses and analyzes global public statistical data through the Data Commons knowledge graph and Python API.
Optimizes large language models to communicate natively through the Slipstream inter-agent protocol using efficient finetuning workflows.
Streamlines genomics pipeline development and data management on the DNAnexus cloud platform using the dxpy Python SDK.
Connects Claude to cloud laboratory services for automated protein testing, sequence optimization, and wet-lab validation.
Searches and retrieves life sciences preprints from the bioRxiv database with advanced filtering and PDF download capabilities.
Enables development and training of Graph Neural Networks (GNNs) using the PyTorch Geometric library.
Queries the NHGRI-EBI GWAS Catalog to retrieve SNP-trait associations, genetic variant data, and genome-wide association study summary statistics.
Accesses the Human Metabolome Database (HMDB) to retrieve metabolite data, chemical properties, and clinical biomarkers for metabolomics research.
Simplifies querying the openFDA API to analyze regulatory data, drug safety profiles, medical device clearances, and food recalls.
Integrates Hugging Face Transformers for advanced natural language processing, computer vision, and audio tasks within development workflows.
Provides a comprehensive suite of statistical modeling tools for rigorous inference, hypothesis testing, and econometric analysis in Python.
Automates biomedical literature searches and data retrieval from the PubMed database using advanced MeSH queries and the E-utilities API.
Streamlines the design and architecture of domain-specific AI agents using Claude Agent SDK patterns.
Automates laboratory workflows and controls liquid handling robots, plate readers, and analytical equipment through a unified Python interface.
Develops high-performance reinforcement learning systems with optimized PPO training, vectorized simulations, and multi-agent support.
Processes and prepares whole slide pathology images for deep learning and digital pathology workflows.
Streamlines machine learning workflows in Python by providing expert guidance on scikit-learn algorithms, data preprocessing, and production-ready pipelines.
Analyzes mass spectrometry data for proteomics and metabolomics workflows using the PyOpenMS library.
Facilitates advanced probabilistic modeling and analysis of single-cell omics data using deep generative models.
Generates professional, publication-quality statistical graphics and complex multi-panel data visualizations using Python's Seaborn library.
Enables parallel and distributed computing for Python data science workflows to process datasets larger than available memory.
Builds, optimizes, and executes quantum circuits and algorithms across various hardware providers and simulators.
Performs exact symbolic computation, calculus, and equation solving in Python to handle complex mathematical formulas without numerical approximation.
Empowers AI agents to perform complex scientific research tasks using a unified ecosystem of 600+ specialized tools and databases.
Accesses and analyzes chemical data from the world's largest open chemical database using PUG-REST and PubChemPy.
Builds complex process-based discrete-event simulations in Python to model systems with shared resources and time-based events.
Optimizes Radio Access Network performance using autonomous swarm coordination and cognitive temporal reasoning.
Empowers researchers to generate novel hypotheses, explore interdisciplinary connections, and overcome creative blocks through collaborative ideation.
Transforms Claude into a specialized prompt architect for designing, optimizing, and debugging complex AI instructions and agent behaviors.
Streamlines AILANG programming for AI agents by providing real-time syntax rules, capability-based execution, and a searchable library of 90+ code examples.
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