Discover Agent Skills for data science & ml. Browse 61 skills for Claude, ChatGPT & Codex.
Parses and creates Flow Cytometry Standard (FCS) files for seamless integration with Python data science workflows.
Facilitates the research, modeling, and implementation of complex artificial life systems, from cellular automata to evolutionary dynamics.
Searches and retrieves life sciences preprints from the bioRxiv database with support for metadata extraction and PDF downloads.
Accelerates reinforcement learning workflows through high-performance parallel environment simulation and optimized PPO training.
Automates the creation, editing, and analysis of professional Excel spreadsheets with advanced formula support and financial modeling standards.
Automates programmable chemical synthesis using the XDL language and modular robotic hardware instructions.
Analyzes complex dynamical systems and strange attractors with sensitive dependence on initial conditions.
Implements a 3×3×3 matrix execution framework using the TiDAR pattern with GF(3) conservation invariants.
Optimizes training epochs for machine learning models using Walk-Forward Efficiency and efficient frontier analysis.
Evaluates financial models using state-of-the-art metrics specifically designed for range bar (price-based sampling) data.
Implements topological sheaf theory to manage distributed coordination and data consistency across multi-agent systems.
Analyzes neural network training dynamics using Stochastic Differential Equations (SDEs) to optimize convergence, temperature control, and exploration.
Calculates Möbius functions and alternating sums on posets to solve complex combinatorial, graph theory, and network centrality problems.
Guides R developers in choosing and implementing the optimal OOP system, including S7, S3, S4, and vctrs.
Analyzes single-cell omics data using probabilistic models for tasks like batch correction, dimensionality reduction, and differential expression.
Queries and analyzes over 240 million scholarly works, authors, and institutions using the OpenAlex API.
Optimizes LLM performance by implementing token-efficient context management strategies for AI agents and tools.
Accesses and analyzes comprehensive pharmaceutical data from DrugBank for drug discovery, pharmacology research, and chemical informatics.
Standardizes and catalogs diverse Gymnasium and OpenAI Gym environments for reinforcement learning across physics, robotics, chemistry, and gaming domains.
Leverages a multi-model ensemble to provide diverse, parallel insights from GPT, Gemini, and Claude for complex problem-solving.
Performs fast, scalable non-linear dimensionality reduction for high-dimensional data visualization, clustering preprocessing, and feature engineering.
Resolves architectural and algorithmic paradigm tensions using OpenModelica Microgrid Gym dynamics as a physical substrate.
Simulates and analyzes quantum mechanical systems using the Quantum Toolbox in Python (QuTiP).
Optimizes Mojo tensor and array operations using SIMD vectorization to maximize computational throughput on modern hardware.
Unifies topos-theoretic resources, categorical databases, and infinity-topoi for advanced mathematical modeling and cognitive agent development.
Accesses the comprehensive BRENDA enzyme database via SOAP API to retrieve kinetic parameters, reaction equations, and biochemical data for metabolic research.
Analyzes and implements stationary measures for the KPZ equation using Liouville quantum gravity and matrix product ansatz.
Automates scientific hypothesis generation and empirical testing using large language models and research literature integration.
Connects Claude to the Data Commons Knowledge Graph to retrieve and analyze global statistical, economic, and environmental data.
Performs constraint-based reconstruction and analysis (COBRA) of metabolic models for systems biology and metabolic engineering.
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