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Found 2,021 Skills
Generate Flutter applications using Clean Architecture with feature-first structure, Riverpod state management, Dio + Retrofit for networking, and fpdart error handling. Use this skill when creating Flutter apps, implementing features with clean architecture patterns, setting up Riverpod providers, handling data with Either type for functional error handling, making HTTP requests with type-safe API clients, or structuring projects with domain/data/presentation layers. Triggers include "Flutter app", "clean architecture", "Riverpod", "feature-first", "state management", "API client", "Retrofit", "Dio", "REST API", or requests to build Flutter features with separation of concerns.
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 protein flexibility prediction, collective motions, structural ensemble comparison, hinge region identification, binding site analysis, MD trajectory filtering, and evolutionary analysis.
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.
Library for bioinformatics and community ecology statistics. Provides data structures and algorithms for sequences, alignments, phylogenetics, and diversity analysis. Essential for microbiome research and ecological data science. Use for alpha/beta diversity metrics, ordination (PCoA), phylogenetic trees, sequence manipulation (DNA/RNA/Protein), distance matrices, PERMANOVA, and community ecology analysis.
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.
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.
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.
Scaffold and guide creation of H5P content types. Use when asked "build an H5P type", "create an H5P content type", "scaffold an H5P library", or "start a new H5P".
Complete survival analysis library in Python. Handles right-censored data, Kaplan-Meier curves, and Cox regression. Standard for clinical trial analysis and epidemiology.
Advanced sub-skill for scikit-learn focused on model interpretability, feature importance, and diagnostic tools. Covers global and local explanations using built-in inspection tools and SHAP/LIME integrations.
Open-source cheminformatics and machine learning toolkit for drug discovery, molecular manipulation, and chemical property calculation. RDKit handles SMILES, molecular fingerprints, substructure searching, 3D conformer generation, pharmacophore modeling, and QSAR. Use when working with chemical structures, drug-like properties, molecular similarity, virtual screening, or computational chemistry workflows.
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 scripts. Load when working with web APIs, model serving, REST endpoints, interactive dashboards, data visualization UIs, scientific app deployment, async web frameworks, Pydantic validation, uvicorn, or building production-ready scientific tools.