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Found 20 Skills
Hardware-agnostic quantum ML framework with automatic differentiation. Use when training quantum circuits via gradients, building hybrid quantum-classical models, or needing device portability across IBM/Google/Rigetti/IonQ. Best for variational algorithms (VQE, QAOA), quantum neural networks, and integration with PyTorch/JAX/TensorFlow. For hardware-specific optimizations use qiskit (IBM) or cirq (Google); for open quantum systems use qutip.
Expert guide for participating in the SOMA network — a decentralized system that trains a foundation model through competition. Provides data submission workflows, model training pipelines, reward claiming, SDK code generation, CLI command guidance, and competitive strategy optimization. Use when user mentions "SOMA", "soma-sdk", "soma-models", "submit data to SOMA", "train a SOMA model", "SOMA targets", "SOMA rewards", "next-byte prediction network", "decentralized model training", or asks about earning SOMA tokens through data or model contributions. Do NOT use for general machine learning, PyTorch, or JAX questions unrelated to the SOMA network.
Complete Shopify development reference for Liquid templating, theme development (OS 2.0), GraphQL Admin API, Storefront API, custom app development, Shopify Functions, Hydrogen, performance optimisation, and debugging. Use when working with .liquid files, creating theme sections and blocks, writing GraphQL queries or mutations for Shopify, building Shopify apps with CLI and Polaris, implementing cart operations via Ajax API, optimising Core Web Vitals for Shopify stores, debugging Liquid or API errors, configuring settings_schema.json, accessing Shopify objects (product, collection, cart, customer), using Liquid filters, creating app extensions, working with webhooks, migrating from Scripts to Functions, or building headless storefronts with Hydrogen and React Router 7. Covers API version 2026-01.
Cross-platform Python library for quantum computing, quantum machine learning, and quantum chemistry. Enables building and training quantum circuits with automatic differentiation, seamless integration with PyTorch/JAX/TensorFlow, and device-independent execution across simulators and quantum hardware (IBM, Amazon Braket, Google, Rigetti, IonQ, etc.). Use when working with quantum circuits, variational quantum algorithms (VQE, QAOA), quantum neural networks, hybrid quantum-classical models, molecular simulations, quantum chemistry calculations, or any quantum computing tasks requiring gradient-based optimization, hardware-agnostic programming, or quantum machine learning workflows.
This skill should be used at the start of any computationally intensive scientific task to detect and report available system resources (CPU cores, GPUs, memory, disk space). It creates a JSON file with resource information and strategic recommendations that inform computational approach decisions such as whether to use parallel processing (joblib, multiprocessing), out-of-core computing (Dask, Zarr), GPU acceleration (PyTorch, JAX), or memory-efficient strategies. Use this skill before running analyses, training models, processing large datasets, or any task where resource constraints matter.
Complete API integration guide for Shopify including GraphQL Admin API, REST Admin API, Storefront API, Ajax API, OAuth authentication, rate limiting, and webhooks. Use when making API calls to Shopify, authenticating apps, fetching product/order/customer data programmatically, implementing cart operations, handling webhooks, or working with API version 2025-10. Requires fetch or axios for JavaScript implementations.
State-of-the-art Machine Learning for PyTorch, TensorFlow, and JAX. Provides thousands of pretrained models to perform tasks on different modalities such as text, vision, and audio. The industry standard for Large Language Models (LLMs) and foundation models in science.
Apply Web Scraping with Python practices (Ryan Mitchell). Covers First Scrapers (Ch 1: urllib, BeautifulSoup), HTML Parsing (Ch 2: find, findAll, CSS selectors, regex, lambda), Crawling (Ch 3-4: single-domain, cross-site, crawl models), Scrapy (Ch 5: spiders, items, pipelines, rules), Storing Data (Ch 6: CSV, MySQL, files, email), Reading Documents (Ch 7: PDF, Word, encoding), Cleaning Data (Ch 8: normalization, OpenRefine), NLP (Ch 9: n-grams, Markov, NLTK), Forms & Logins (Ch 10: POST, sessions, cookies), JavaScript (Ch 11: Selenium, headless, Ajax), APIs (Ch 12: REST, undocumented), Image/OCR (Ch 13: Pillow, Tesseract), Avoiding Traps (Ch 14: headers, honeypots), Testing (Ch 15: unittest, Selenium), Parallel (Ch 16: threads, processes), Remote (Ch 17: Tor, proxies), Legalities (Ch 18: robots.txt, CFAA, ethics). Trigger on "web scraping", "BeautifulSoup", "Scrapy", "crawler", "spider", "scraper", "parse HTML", "Selenium scraping", "data extraction".