Discover Agent Skills for data science & ml. Browse 61 skills for Claude, ChatGPT & Codex.
Queries the ClinicalTrials.gov API v2 to search, filter, and extract global clinical study data for medical research and patient matching.
Simplifies molecular cheminformatics and drug discovery workflows using a Pythonic wrapper for RDKit.
Orchestrates over 48 specialized AI agents for autonomous cryptocurrency trading, market analysis, and backtesting across multiple exchanges.
Queries the ClinicalTrials.gov API v2 to search, retrieve, and analyze clinical trial data for research and patient matching.
Automates complex biomedical research tasks including genomics, drug discovery, and clinical data analysis using an autonomous AI agent framework.
Queries and analyzes over 240 million scholarly works, authors, and institutions via the OpenAlex API.
Performs comprehensive single-cell RNA-seq analysis including quality control, clustering, and cell type annotation using the Scanpy framework.
Automates life sciences research data management by integrating Claude with the Benchling R&D platform's registry, inventory, and notebooks.
Provides programmatic access and comprehensive analysis of the DrugBank database for pharmaceutical research and bioinformatics workflows.
Provides specialized algorithms and workflows for advanced time series tasks including forecasting, classification, and anomaly detection.
Automates life sciences research workflows by integrating Benchling's registry, inventory, and notebook systems via Python SDK and REST API.
Automates laboratory data management and life sciences R&D workflows by integrating with the Benchling platform via Python SDK and REST API.
Queries the ClinicalTrials.gov API to search for medical studies, retrieve trial details, and export structured clinical research data.
Searches the arXiv preprint repository for scholarly articles in computer science, physics, mathematics, and quantitative biology.
Executes complex autonomous biomedical research tasks including genomics, drug discovery, and clinical data analysis.
Automates end-to-end scientific research workflows from initial data analysis and hypothesis generation to the production of publication-ready LaTeX manuscripts.
Retrieves genomic, transcriptomic, and proteomic data from 20+ bioinformatics databases using a unified interface.
Accesses and analyzes comprehensive pharmaceutical data from DrugBank, including drug properties, interactions, targets, and chemical structures.
Generates publication-quality scientific visualizations and data plots locally using Python's Matplotlib and Seaborn libraries.
Builds high-performance Retrieval-Augmented Generation systems using vector databases, semantic search, and advanced retrieval patterns.
Queries the Ensembl REST API to retrieve gene annotations, sequences, variants, and comparative genomics data for over 250 species.
Builds end-to-end MLOps pipelines for data preparation, model training, validation, and production deployment.
Trains and deploys sophisticated neural network architectures across distributed E2B sandbox environments.
Infers gene regulatory networks from transcriptomics data using scalable machine learning algorithms like GRNBoost2 and GENIE3.
Accesses and searches the bioRxiv preprint server to retrieve life sciences research metadata and download full-text PDFs.
Accesses and analyzes comprehensive pharmaceutical data from DrugBank including drug properties, interactions, and molecular structures.
Builds end-to-end MLOps pipelines from data preparation through model training, validation, and production deployment.
Implements ultra-high-performance semantic vector search and document retrieval for Claude-powered RAG systems and intelligent knowledge bases.
Automates the end-to-end scientific research lifecycle from data analysis and hypothesis generation to publication-ready LaTeX manuscripts.
Implements comprehensive evaluation strategies for LLM applications using automated metrics, human feedback, and benchmarking.
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