Quantum computing development requires understanding complex circuit design, transpilation, and hardware-specific optimization. This skill provides comprehensive guidance for building quantum circuits, running algorithms like VQE and QAOA on simulators or real hardware, and visualizing results.

An AI skill for Claude, Codex, and Claude Code

Working with drug discovery datasets requires navigating scattered sources and inconsistent formats. PyTDC provides 50+ curated therapeutic ML datasets with standardized APIs, meaningful splits, and benchmark evaluation protocols.

Process next-generation sequencing data by reading and writing SAM/BAM/CRAM alignment files, VCF/BCF variant files, and FASTA/FASTQ sequences for bioinformatics analysis pipelines.

Mass spectrometry generates complex data requiring specialized tools for proteomics and metabolomics analysis. PyOpenMS provides Python bindings enabling automated LC-MS/MS processing, peptide identification, and quantitative analysis with full reproducibility.

Engineers and researchers need to find optimal trade-offs between conflicting objectives like cost, weight, and performance. This skill provides access to NSGA-II, NSGA-III, and other evolutionary algorithms through pymoo to discover Pareto-optimal solutions for complex design problems.

This skill provides tools for Bayesian statistical modeling using PyMC. It enables building hierarchical models, running MCMC sampling with NUTS, performing variational inference, and comparing models with LOO/WAIC metrics for principled uncertainty quantification.

Computational materials science requires analyzing crystal structures, phase diagrams, and electronic properties. This skill provides comprehensive access to pymatgen library capabilities including structure file conversion, symmetry analysis, and Materials Project database integration.

Automate complex laboratory workflows with a unified Python interface. Program liquid handling robots, integrate plate readers and lab equipment, and create reproducible protocols that work across Hamilton STAR, Opentrons OT-2, and simulated environments.

Developing machine learning models for healthcare requires understanding complex clinical data formats, medical coding systems, and specialized model architectures. This skill provides comprehensive guidance on using PyHealth to build, train, and evaluate clinical prediction models for mortality prediction, drug recommendation, and medical coding tasks.

Working with medical imaging data requires specialized handling for DICOM files, the standard format used in healthcare. This skill provides guidance on reading, converting, anonymizing, and extracting data from CT, MRI, X-ray, and ultrasound images.

Identify differentially expressed genes from bulk RNA-seq count data with statistical rigor. PyDESeq2 provides complete DESeq2 workflows including normalization, dispersion estimation, Wald testing, FDR correction, and publication-ready visualizations.

Training reinforcement learning agents requires managing complex parallel simulations and implementing efficient PPO algorithms. PufferLib provides high-performance vectorized environments and optimized training to achieve millions of steps per second.

Finding relevant biomedical research is time-consuming. This skill provides advanced search techniques, MeSH term guidance, and E-utilities API documentation to quickly locate articles, clinical trials, and systematic reviews in PubMed's database of millions of citations.

Finding chemical information requires navigating multiple databases and complex API queries. This skill provides unified access to PubChem database with simple search by name, structure, or identifier plus property retrieval and similarity searches for cheminformatics workflows.

Scientists spend hours searching for and documenting lab protocols manually. This skill provides complete integration with protocols.io API v3, enabling programmatic access to search, create, manage, and publish scientific protocols with team collaboration features.

Product leaders struggle to align company objectives across teams. This tool automatically cascades strategic OKRs from company level to product and team levels with alignment scoring.

Product managers need objective ways to rank feature requests and synthesize customer insights. This toolkit provides RICE scoring algorithms and NLP-based interview analysis to make data-driven prioritization decisions and document requirements clearly.

Teams need reliable ways to create and update PPTX files at scale. This skill provides workflows for building, editing, and inspecting presentations using HTML and OOXML tooling.

Pandas workflows are slow and memory-intensive on large datasets. This skill provides expert guidance on Polars, a lightning-fast DataFrame library built on Apache Arrow that delivers 10-100x performance improvements with lazy evaluation, parallel processing, and an intuitive expression API.