Discover Agent Skills for data science & ml. Browse 61skills for Claude, ChatGPT & Codex.
Processes and prepares whole slide pathology images for deep learning and digital pathology workflows.
Evaluates scientific research rigor and methodology through systematic analysis of experimental design, statistical validity, and potential biases.
Provides expert guidance and implementation patterns for crafting highly effective LLM prompts using advanced techniques like chain-of-thought and few-shot learning.
Develops high-performance reinforcement learning systems with optimized PPO training, vectorized simulations, and multi-agent support.
Creates, modifies, and analyzes Excel spreadsheets with production-grade formulas, professional formatting, and financial modeling standards.
Performs hydrological modeling and streamflow forecasting using Julia-based classical and machine learning models.
Optimizes AI agent performance through Anthropic-based context engineering and prompt structure standards.
Provides specialized functions for hydrological modeling and climate data processing within the Julia environment.
Automates laboratory workflows and controls liquid handling robots, plate readers, and analytical equipment through a unified Python interface.
Streamlines the design and architecture of domain-specific AI agents using Claude Agent SDK patterns.
Automates biomedical literature searches and data retrieval from the PubMed database using advanced MeSH queries and the E-utilities API.
Analyzes CSV files automatically to generate comprehensive statistical summaries and tailored visualizations using Python and pandas.
Provides a comprehensive suite of statistical modeling tools for rigorous inference, hypothesis testing, and econometric analysis in Python.
Processes and analyzes complex physiological data including ECG, EEG, and EDA for scientific research and health applications.
Integrates Hugging Face Transformers for advanced natural language processing, computer vision, and audio tasks within development workflows.
Facilitates advanced materials analysis, crystal structure manipulation, and computational workflows using the Python Materials Genomics library.
Simplifies querying the openFDA API to analyze regulatory data, drug safety profiles, medical device clearances, and food recalls.
Processes and analyzes massive tabular datasets with billions of rows using out-of-core DataFrame operations and lazy evaluation.
Provides comprehensive guidance and implementation patterns for data science, machine learning engineering, and AI application development.
Integrates with the NIH Metabolomics Workbench REST API to query metabolite data, standardized nomenclature, and experimental studies for biomarker discovery.
Accesses the Human Metabolome Database (HMDB) to retrieve metabolite data, chemical properties, and clinical biomarkers for metabolomics research.
Automates professional-grade spreadsheet creation, editing, and analysis with a focus on formula integrity and financial modeling standards.
Performs high-performance nonlinear dimensionality reduction for data visualization, clustering preprocessing, and supervised manifold learning.
Accesses the ClinicalTrials.gov API v2 to search, filter, and export global clinical research data for medical analysis.
Queries the NHGRI-EBI GWAS Catalog to retrieve SNP-trait associations, genetic variant data, and genome-wide association study summary statistics.
Facilitates collaborative research ideation by generating hypotheses, identifying research gaps, and exploring interdisciplinary connections for scientific problem-solving.
Provides comprehensive cheminformatics capabilities for molecular analysis, manipulation, and drug discovery workflows.
Accesses the Ensembl REST API to retrieve genomic sequences, gene annotations, and variant data for over 250 species.
Systematically evaluates research papers, literature reviews, and academic methodologies using the ScholarEval framework to ensure scientific rigor and novelty.
Builds and deploys robust machine learning models, data pipelines, and intelligent LLM applications using Python and industry-standard frameworks.
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