Discover Agent Skills for data science & ml. Browse 61skills for Claude, ChatGPT & Codex.
Accesses the comprehensive BRENDA enzyme database to retrieve kinetic parameters, reaction equations, and biochemical data for metabolic research.
Processes and analyzes complex physiological signals including ECG, EEG, EDA, and more using the NeuroKit2 Python library.
Builds professional investment banking-standard discounted cash flow (DCF) models in Excel with automated financial projections and sensitivity analysis.
Scales Python data processing and scientific computing across multiple cores or clusters for datasets that exceed available memory.
Provides programmatic access to global statistical datasets including demographic, economic, and environmental indicators via the Data Commons API.
Queries the Ensembl REST API to retrieve gene data, sequences, and variant analysis for over 250 species.
Performs constraint-based metabolic modeling and systems biology simulations using the COBRApy framework.
Constructs and configures custom neural network architectures including CNNs, RNNs, and Transformers directly within the Claude Code environment.
Automates the creation of professional-grade Leveraged Buyout (LBO) models in Excel for private equity and investment analysis.
Integrates Codex CLI command patterns into Claude Code to enable advanced multi-agent planning and high-reasoning execution.
Provides deep insights and interpretability for machine learning models using advanced techniques like SHAP and LIME.
Accesses and analyzes comprehensive pharmaceutical data from DrugBank for research, drug discovery, and interaction analysis.
Simplifies astronomical data analysis and astrophysical calculations using the comprehensive Astropy Python library.
Builds, fits, and validates robust Bayesian statistical models using the PyMC probabilistic programming framework.
Provides comprehensive cheminformatics capabilities for molecular analysis, structural manipulation, and computational chemistry workflows.
Performs differential gene expression analysis for bulk RNA-seq data using the Python implementation of DESeq2.
Facilitates biological pathway analysis and gene-mapping by querying the Reactome open-source database and REST API.
Automates the creation, editing, and analysis of professional spreadsheets with support for complex formulas and financial modeling standards.
Manages academic citations and BibTeX entries by searching scholarly databases and validating metadata for research papers.
Generates professional, publication-quality plots and charts using Python's foundational visualization library.
Generates publication-quality scientific diagrams and neural network architectures using AI-driven iterative refinement.
Constructs and configures custom neural network architectures including CNNs, RNNs, and Transformers directly within the Claude Code environment.
Implements probabilistic deep learning models for comprehensive single-cell omics data analysis and multimodal integration.
Automates the complete scientific research lifecycle from initial data analysis to publication-ready LaTeX manuscripts.
Implements rigorous evaluation frameworks for Large Language Model applications using automated metrics, LLM-as-judge patterns, and human feedback loops.
Configures and manages Mozilla Llamafile to run high-performance GGUF models locally with an OpenAI-compatible API.
Provides programmatic access to over 40 bioinformatics web services and databases for integrated biological data analysis and workflow automation.
Runs machine learning model inference, including detection, classification, and segmentation, directly on FiftyOne datasets.
Evaluates computer vision model predictions against ground truth using industry-standard protocols like COCO and Open Images.
Automates the detection and ingestion of computer vision datasets into FiftyOne with support for multimodal data and complex label formats.
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