Discover Agent Skills for data science & ml. Browse 61 skills for Claude, ChatGPT & Codex.
Deploys machine learning models to Hugging Face Spaces using optimized configurations for Gradio, ZeroGPU, and LoRA adapters.
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.
Provides a comprehensive suite of statistical modeling tools for rigorous inference, hypothesis testing, and econometric analysis in Python.
Simplifies text analysis and processing using modern NLP techniques including embeddings, tokenization, and transformer models.
Automates biomedical literature searches and data retrieval from the PubMed database using advanced MeSH queries and the E-utilities API.
Builds, tunes, and evaluates production-ready classification and regression models using industry-standard machine learning algorithms.
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.
Provides architectural patterns and implementation guides for building reliable autonomous AI agent systems.
Provides structured methodologies and frameworks for market research, competitor analysis, and professional data synthesis.
Analyzes genomic VCF files to provide personalized insights on health, metabolism, and genetic traits.
Implements a systematic methodology for diagnosing, refining, and validating trading strategies to improve win rates and returns.
Architects and implements sophisticated, stateful multi-agent LLM applications using LangGraph and Python.
Builds type-safe, modular LLM applications using Ruby's programmatic prompt framework with signatures and automated optimization.
Develops high-performance reinforcement learning systems with optimized PPO training, vectorized simulations, and multi-agent support.
Analyzes textual data to extract sentiments, keywords, and core topics using advanced natural language processing techniques.
Fetches, searches, and manages academic papers from arXiv through a local CLI-based database.
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.
Generates and transforms high-quality images using Google's Gemini models through customizable Python scripts.
Analyzes mass spectrometry data for proteomics and metabolomics workflows using the PyOpenMS library.
Guides the selection of the optimal Claude model for custom agent tasks based on cost, speed, and reasoning requirements.
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.
Synchronizes and updates the latest LLM model specifications, pricing, and API documentation automatically.
Empowers AI agents to perform complex scientific research tasks using a unified ecosystem of 600+ specialized tools and databases.
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