Discover Agent Skills for data science & ml. Browse 61 skills for Claude, ChatGPT & Codex.
Performs high-precision cartographic projections and coordinate transformations using the PROJ library.
Converts and processes chemical data across 110+ formats for molecular modeling, informatics, and 3D structure generation.
Performs ab initio quantum chemistry calculations and molecular simulations using the PySCF framework.
Performs advanced statistical modeling, hypothesis testing, and rigorous data inference using R-style formulas.
Generates high-performance animations, publication-quality scientific figures, and interactive data visualization tools using advanced Matplotlib techniques.
Generates interactive, web-based charts and complex data dashboards using Python's high-level Plotly library.
Provides specialized tools for reading, modifying, and writing DICOM medical imaging data within Python environments.
Streamlines computational biology workflows with specialized guidance for sequence analysis, file parsing, and biological database integration using Biopython.
Accelerates Python and NumPy code using Just-In-Time (JIT) compilation for machine-speed execution.
Generates sophisticated, publication-quality statistical graphics and exploratory data visualizations using the Python Seaborn library.
Enables advanced solar data processing, coordinate transformations, and multi-instrument analysis using the SunPy ecosystem.
Generates publication-quality 2D plots, scientific visualizations, and complex multi-panel figures using industry-standard Python patterns.
Detects astronomical sources and performs high-precision photometry on digital images using the Astropy ecosystem.
Simplifies astronomical data analysis and physical calculations using standardized units, coordinates, and cosmological models.
Scales Python's data science stack to multi-core systems and distributed clusters using lazy evaluation and task scheduling.
Deploys and optimizes PyTorch models for production environments, edge devices, and high-performance C++ applications.
Optimizes and executes quantum circuits on physical IBM Quantum hardware using advanced error mitigation and pulse-level control.
Integrates differentiable quantum computing circuits into classical machine learning workflows for hybrid model development.
Analyzes molecular dynamics trajectories and structural data using the MDAnalysis Python library for biophysical research.
Facilitates the design, simulation, and execution of quantum circuits and algorithms using IBM's Qiskit framework.
Provides specialized guidance for implementing differentiable physics simulations and solving partial differential equations using JAX.
Provides specialized tools for molecular manipulation, chemical property calculation, and machine learning in drug discovery workflows.
Performs advanced survival analysis and time-to-event modeling using the lifelines library for medical, clinical, and epidemiological research.
Provides specialized guidance and code patterns for interpreting machine learning models using scikit-learn, SHAP, and advanced diagnostic tools.
Accelerates data manipulation and analysis using the blazingly fast Polars DataFrame library for Python and Rust.
Optimizes numerical computing tasks in Python using high-performance array operations and vectorized mathematical functions.
Optimizes NumPy performance through advanced memory management, stride manipulation, and zero-copy operations.
Automates the creation of standardized Python-based AI agents for autonomous career-focused tasks.
Simplifies scientific image processing and analysis using Python-based algorithms and NumPy-compatible workflows.
Implements a decentralized context-sharing protocol for multi-agent systems using cryptographic sharding and Byzantine fault tolerance.
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