Discover Agent Skills for data science & ml. Browse 61 skills for Claude, ChatGPT & Codex.
Provides architectural patterns and implementation guides for building reliable autonomous AI agent systems.
Manages large-scale scientific dataset transfers between remote Globus endpoints and high-performance computing clusters.
Implements a systematic methodology for diagnosing, refining, and validating trading strategies to improve win rates and returns.
Provides structured methodologies and frameworks for market research, competitor analysis, and professional data synthesis.
Architects and implements sophisticated, stateful multi-agent LLM applications using LangGraph and Python.
Develops high-performance reinforcement learning systems with optimized PPO training, vectorized simulations, and multi-agent support.
Integrates the Google Gemini CLI into Claude to provide large-context analysis, safe sandbox execution, and structured code modifications.
Deploys machine learning models to Hugging Face Spaces using optimized configurations for Gradio, ZeroGPU, and LoRA adapters.
Builds type-safe, modular LLM applications using Ruby's programmatic prompt framework with signatures and automated optimization.
Transforms vague research interests into concrete, measurable, and tractable research questions through systematic refinement and feasibility analysis.
Generates rigorous experimental frameworks for scientific research and machine learning projects to ensure statistically significant and defensible results.
Processes and prepares whole slide pathology images for deep learning and digital pathology workflows.
Analyzes mass spectrometry data for proteomics and metabolomics workflows using the PyOpenMS library.
Simplifies text analysis and processing using modern NLP techniques including embeddings, tokenization, and transformer models.
Streamlines machine learning workflows in Python by providing expert guidance on scikit-learn algorithms, data preprocessing, and production-ready pipelines.
Builds, tunes, and evaluates production-ready classification and regression models using industry-standard machine learning algorithms.
Facilitates advanced probabilistic modeling and analysis of single-cell omics data using deep generative models.
Enables parallel and distributed computing for Python data science workflows to process datasets larger than available memory.
Generates professional, publication-quality statistical graphics and complex multi-panel data visualizations using Python's Seaborn library.
Fetches, searches, and manages academic papers from arXiv through a local CLI-based database.
Analyzes genomic VCF files to provide personalized insights on health, metabolism, and genetic traits.
Builds, optimizes, and executes quantum circuits and algorithms across various hardware providers and simulators.
Generates and transforms high-quality images using Google's Gemini models through customizable Python scripts.
Performs exact symbolic computation, calculus, and equation solving in Python to handle complex mathematical formulas without numerical approximation.
Guides the selection of the optimal Claude model for custom agent tasks based on cost, speed, and reasoning requirements.
Empowers AI agents to perform complex scientific research tasks using a unified ecosystem of 600+ specialized tools and databases.
Synchronizes and updates the latest LLM model specifications, pricing, and API documentation automatically.
Accesses and analyzes chemical data from the world's largest open chemical database using PUG-REST and PubChemPy.
Analyzes textual data to extract sentiments, keywords, and core topics using advanced natural language processing techniques.
Builds complex process-based discrete-event simulations in Python to model systems with shared resources and time-based events.
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