tondevrel
@tondevrel
Public Skills
ase
by tondevrel
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 atomic structures, geometry optimization, molecular dynamics simulations, transition state searches (NEB), file format conversion (CIF, XYZ, POSCAR, PDB), electronic property calculations (DOS, band structures), and automating simulation workflows with DFT/MD codes like VASP, GPAW, Quantum ESPRESSO, LAMMPS.
duckdb
by tondevrel
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 step. Use for complex SQL queries on Pandas/Polars data, querying large Parquet/CSV files directly, joining data from different sources, analytical pipelines, local datasets too big for Excel, intermediate data storage and feature engineering for ML.
pytorch
by tondevrel
Leading deep learning framework. Provides Tensors and Dynamic Computational Graphs with strong GPU acceleration. Widely used for research, neural networks, and differentiable programming.
h5py
by tondevrel
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, organizing complex scientific data hierarchically, storing numerical arrays with high-speed random access, keeping metadata attached to data, sharing data between languages, and reading/writing large datasets in chunks.
jax
by tondevrel
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, higher-order derivatives, physics-informed machine learning, differentiable simulations, and automatic vectorization.
numba
by tondevrel
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 @njit, @vectorize, prange, cuda.jit, numba.typed, JIT compilation, parallel loops, GPU acceleration with CUDA, Monte Carlo simulations, numerical algorithms, and high-performance Python computing.
mne
by tondevrel
Open-source Python package for exploring, visualizing, and analyzing human neurophysiological data including EEG, MEG, sEEG, and ECoG.
opencv
by tondevrel
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 transformations, object tracking, optical flow, or any computer vision task.
lifelines
by tondevrel
Complete survival analysis library in Python. Handles right-censored data, Kaplan-Meier curves, and Cox regression. Standard for clinical trial analysis and epidemiology.
openbabel
by tondevrel
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 (SDF, PDB, SMILES, CIF, Gaussian), 3D coordinate generation from 2D structures, substructure searching with SMARTS patterns, molecular docking preparation, force field minimizations (UFF, GAFF, MMFF94), molecular fingerprints and Tanimoto coefficients, and batch processing of chemical databases.
polars
by tondevrel
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+), fast data transformations, Parquet/CSV processing, complex query pipelines, memory-efficient operations, and when speed is critical (10-100x faster than pandas).
pysam
by tondevrel
Python module for reading, manipulating and writing genomic alignment formats (SAM/BAM/CRAM) and variant files (VCF/BCF). Wrapper for htslib.
qiskit-hardware
by tondevrel
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).
mdanalysis
by tondevrel
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, protein structure analysis, membrane analysis, and integration with Biopython. Essential for MD simulation analysis.
ortools
by tondevrel
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), scheduling, bin packing, knapsack problems, linear programming (LP), integer programming (MIP), network flows, constraint programming, combinatorial optimization, resource allocation, shift scheduling, job-shop scheduling, and discrete optimization problems.
numpy-low-level
by tondevrel
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.
qiskit
by tondevrel
Comprehensive guide for Qiskit - IBM's quantum computing framework. Use for quantum circuit design, quantum algorithms (VQE, QAOA, Grover, Shor), quantum simulation, noise modeling, quantum machine learning, and quantum chemistry calculations. Essential for quantum computing research and applications.
numpy
by tondevrel
Comprehensive guide for NumPy - the fundamental package for scientific computing in Python. Use for array operations, linear algebra, random number generation, Fourier transforms, mathematical functions, and high-performance numerical computing. Foundation for SciPy, pandas, scikit-learn, and all scientific Python.
pyscf
by tondevrel
Comprehensive guide for PySCF - Python-based Simulations of Chemistry Framework. Use for ab initio quantum chemistry calculations including Hartree-Fock, DFT, MP2, CCSD, geometry optimization, excited states, and molecular properties. Industry-standard library for electronic structure calculations.
biopython
by tondevrel
Comprehensive guide for Biopython - the premier Python library for computational biology and bioinformatics. Use for DNA/RNA/protein sequence analysis, file I/O (FASTA, FASTQ, GenBank, PDB), sequence alignment, BLAST searches, phylogenetic analysis, structure analysis, and NCBI database access.
example-skill
by tondevrel
Example skill template. Replace this description with keywords and triggers for your actual skill. This description determines when the skill auto-loads based on conversation context.