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Found 2,021 Skills
Based on collected materials, we provide high-quality blog post writing (especially technical blogs), SEO optimization, and structure proposals.
Expert in quality assurance and testing. Responsible for bug detection, edge case validation, test planning, and automated test creation to ensure software reliability.
Infrastructure and CI/CD specialist. Responsible for environment setup, pipeline construction, and security management to deploy applications safely and reliably. Platform-agnostic (supports AWS/GCP/Cloudflare, etc.).
Expert in implementation and coding. Implements high-quality code while complying with project conventions and structure based on design documents. Acts as a specialist in the corresponding programming language according to the language being used.
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.
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.
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
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.
A Python data visualization library based on matplotlib. It provides a high-level interface for drawing attractive and informative statistical graphics. Great for exploring relationships between variables and visualizing distributions. Use for statistical data visualization, exploratory data analysis (EDA), relationship plots, distribution plots, categorical comparisons, regression visualization, heatmaps, cluster maps, and creating publication-quality statistical graphics from Pandas DataFrames.