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Found 7,430 Skills
pytest, data validation, Great Expectations, and quality assurance for data systems
React Query v4 (TanStack Query) best practices, patterns, and troubleshooting. Use when working with useQuery, useMutation, query invalidation, caching, WebSocket integration, or any async state management in React. Based on TkDodo's comprehensive blog series.
Set up Kysely with TiDB Cloud (TiDB X), including @tidbcloud/kysely over the TiDB Cloud serverless HTTP driver for serverless or edge environments, plus standard TCP usage. Use for Kysely + TiDB Cloud connection setup, demo snippets, and environment-specific guidance.
Manage containers using Podman, the daemonless container engine. Run rootless containers, create pods, manage images, and use Docker-compatible commands. Use when working with Podman or requiring rootless container operations.
Implement scalable CSS architecture patterns - BEM, SMACSS, ITCSS, design tokens
Write, review, and adapt SQL for TiDB with correct handling of TiDB-vs-MySQL differences (VECTOR type + vector indexes/functions, full-text search, AUTO_RANDOM, optimistic/pessimistic transactions, foreign keys, views, DDL limitations, and unsupported MySQL features like procedures/triggers/events/GEOMETRY/SPATIAL). Use when generating SQL that must run on TiDB, migrating MySQL SQL to TiDB, or debugging TiDB SQL compatibility errors.
AWS ECS container orchestration for running Docker containers. Use when deploying containerized applications, configuring task definitions, setting up services, managing clusters, or troubleshooting container issues.
Creating an outline of a piece of writing according to a strategy of Ayn Rand art of non-fiction/fiction
Use this skill to send a message over Discord to the operator
Design or audit AI-first help centers/knowledge bases/FAQs, including taxonomy, article templates, analytics, and AI support (RAG, chatbot, escalation), using 2025-2026 best practices
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.
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.