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SkillsMP has collected 68 skills from tondevrel/scientific-agent-skills. Open a skill to review its source and details.
Showing 40 of 68 collected skills.
Atomic Simulation Environment - a set of tools for setting up, manipulating, running, visualizing, and analyzing atomistic simulations. Acts as a universal interface between Python and numerous quantum chemical and molecular dynamics codes. Use for building…
The core library for Astronomy and Astrophysics in Python. Provides data structures for coordinates, time, units, FITS files, and cosmological models. Essential for observational data reduction and theoretical astrophysics. Use when working with astronomical…
A Python package useful for chemistry (mainly physical/analytical/inorganic chemistry). Features include balancing chemical reactions, chemical kinetics (ODE integration), chemical equilibria, ionic strength calculations, and unit handling. Use when working…
Constraints-Based Reconstruction and Analysis for Python. Used for modeling large-scale metabolic networks in microorganisms.
Advanced sub-skill for Dask focused on distributed system performance, memory management, and task graph optimization. Covers cluster tuning, efficient serialization, data skew mitigation, and dashboard-driven debugging.
A flexible library for parallel computing in Python. It scales Python libraries like NumPy, pandas, and scikit-learn to multi-core systems or distributed clusters. Features lazy evaluation and task scheduling for data that exceeds RAM capacity. Use for…
Causal inference framework for answering "does X cause Y?" beyond correlation. DoWhy (Microsoft Research) provides the identify-estimate-refute loop: define a causal graph (DAG), identify the causal effect using backdoor/frontdoor/instrumental variable…
An analytical in-process SQL database management system. Designed for fast analytical queries (OLAP). Highly interoperable with Python's data ecosystem (Pandas, NumPy, Arrow, Polars). Supports querying files (CSV, Parquet, JSON) directly without an ingestion…
Dual skill for deploying scientific models. FastAPI provides a high-performance, asynchronous web framework for building APIs with automatic documentation. Streamlit enables rapid creation of interactive data applications and dashboards directly from Python…
Open source project to make working with geospatial data in python easier. Extends the datatypes used by pandas to allow spatial operations on geometric types. Built on top of Shapely, Fiona, and Pyproj. Use for reading and writing spatial formats (Shapefile,…
A Pythonic interface to the HDF5 binary data format. It allows you to store huge amounts of numerical data and easily manipulate that data from NumPy. Features a hierarchical structure similar to a file system. Use for storing datasets larger than RAM,…
Advanced sub-skill for JAX focused on solving Partial Differential Equations (PDEs) and Differentiable Physics. Covers Finite Difference Methods (FDM), Neural Operators, and Physics-Informed Neural Networks (PINNs).
Composable transformations of Python+NumPy programs. Differentiate, vectorize, JIT-compile to GPU/TPU. Built for high-performance machine learning research and complex scientific simulations. Use for automatic differentiation, GPU/TPU acceleration,…
Professional sub-skill for Matplotlib focused on high-performance animations, complex multi-figure layouts (GridSpec), interactive widgets, and publication-ready typography (LaTeX/PGF).
The foundational library for creating static, animated, and interactive visualizations in Python. Highly customizable and the industry standard for publication-quality figures. Use for 2D plotting, scientific data visualization, heatmaps, contours, vector…
Comprehensive guide for MDAnalysis - the Python library for analyzing molecular dynamics trajectories. Use for trajectory loading, RMSD/RMSF calculations, distance/angle/dihedral analysis, atom selections, hydrogen bonds, solvent accessible surface area,…
Open-source Python package for exploring, visualizing, and analyzing human neurophysiological data including EEG, MEG, sEEG, and ECoG.
Python package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks. Supports various graph types (Directed, Undirected, Multigraphs) and features a vast library of standard graph algorithms. Use for network…
A Just-In-Time (JIT) compiler for Python that translates a subset of Python and NumPy code into fast machine code. Developed by Anaconda, Inc. Highly effective for accelerating loops, custom mathematical functions, and complex numerical algorithms. Use for…
Advanced sub-skill for NumPy focused on internal memory management, stride manipulation, structured arrays, and interfacing with C/Cython. Covers zero-copy operations and SIMD vectorization principles.
A chemical toolbox designed to speak the many languages of chemical data. Supports over 110 formats and provides tools for conversion, 3D structure generation, molecular searching (SMARTS), and force field calculations. Use for chemical file format conversion…
Open Source Computer Vision Library (OpenCV) for real-time image processing, video analysis, object detection, face recognition, and camera calibration. Use when working with images, videos, cameras, edge detection, contours, feature detection, image…
Google Optimization Tools. An open-source software suite for optimization, specialized in vehicle routing, flows, integer and linear programming, and constraint programming. Features the world-class CP-SAT solver. Use for vehicle routing problems (VRP),…
Advanced sub-skill for pandas focused on memory optimization, execution speed, and handling large-scale datasets (10M+ rows). Covers low-level dtypes, efficient indexing, and vectorization of complex logic.
Cross-platform Python library for differentiable quantum computing. Integrated with machine learning libraries like PyTorch, TensorFlow, and JAX. Designed for quantum machine learning (QML), variational algorithms, and hardware-agnostic quantum programming.…
An Astropy coordinated package for detecting and performing photometry of astronomical sources. Provides tools for background estimation, source detection (DAOFIND, IRAF), aperture photometry, and PSF (Point Spread Function) fitting. Use when working with…
A high-level interactive graphing library for Python. Ideal for web-based visualizations, 3D plots, and complex interactive dashboards. Built on plotly.js, it allows users to zoom, pan, and hover over data points in a browser-based environment. Use for…
Blazingly fast DataFrame library written in Rust. Features a multi-threaded query engine, lazy evaluation, and efficient memory usage via Apache Arrow. Designed for high-performance data processing on a single machine. Use for large datasets (1GB-100GB+),…
Protein Dynamics, Evolution, and Structure analysis. Specialized in Normal Mode Analysis (NMA) using Anisotropic (ANM) and Gaussian Network Models (GNM). Features tools for structural ensemble analysis, PCA, and co-evolutionary analysis (Evol). Use for…
Python package for working with DICOM files. It allows you to read, modify, and write DICOM data in a Pythonic way. Essential for medical imaging processing, clinical data extraction, and AI in radiology.
Probabilistic programming for Bayesian statistical modeling and inference. PyMC provides declarative model specification with MCMC (NUTS) and variational inference samplers; NumPyro offers JAX-accelerated equivalent for large-scale problems. Use when:…
Python Optimization Modeling Objects. A high-level framework for formulating, solving, and analyzing optimization models. Supports Linear Programming (LP), Mixed-Integer Linear Programming (MILP), and Non-Linear Programming (NLP). Part of the COIN-OR project.…
Python interface to PROJ (cartographic projections and coordinate transformations library). Handles transformations between different Coordinate Reference Systems (CRS) and performs geodetic calculations (distance, area on ellipsoids). Use for coordinate…
Python module for reading, manipulating and writing genomic alignment formats (SAM/BAM/CRAM) and variant files (VCF/BCF). Wrapper for htslib.
Advanced sub-skill for PyTorch focused on model productionization and deployment. Covers TorchScript (JIT/Tracing), ONNX export, LibTorch (C++ API), and inference optimization (Quantization, Pruning).
Graph Neural Networks (GNN) for learning on graph-structured data. PyTorch Geometric (PyG) extends PyTorch with the MessagePassing framework — the core abstraction for all GNN layers — and provides standard convolutions (GCNConv, GATConv, GraphSAGEConv,…
Advanced sub-skill for PyTorch focused on deep research and production engineering. Covers custom Autograd functions, module hooks, advanced initialization, Distributed Data Parallel (DDP), and performance profiling.
Leading deep learning framework. Provides Tensors and Dynamic Computational Graphs with strong GPU acceleration. Widely used for research, neural networks, and differentiable programming.
Advanced sub-skill for Qiskit focused on executing circuits on physical quantum processing units (QPUs). Covers IBM Quantum Runtime, error mitigation techniques (TREX, ZNE), hardware-aware transpilation, and low-level pulse control (OpenPulse).
Quantum Toolbox in Python. Framework for simulating the dynamics of open quantum systems. Provides data structures for quantum objects (kets, bras, operators) and solvers for master equations, Monte Carlo trajectories, and time-dependent Hamiltonians. Use for…