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Found 7,435 Skills
Git worktree management with safe defaults and flexible placement strategies. Use when users ask to: (1) create a new worktree or work on multiple branches in parallel, (2) list existing worktrees, (3) remove or clean up worktrees, (4) manage worktree placement (subfolder vs sibling directory), or any other git worktree operations.
This skill should be used when working with Bun runtime, bun:sqlite, Bun.serve, bun:test, or when "Bun", "bun:test", or Bun-specific patterns are mentioned.
Build fast, SEO-optimized static sites with Docusaurus v3.9.2 using Markdown/MDX, SEO metadata, and plugins. Helps with setup, docs, SEO optimization, plugin integration, and GitHub Pages deployment.
A high-level interactive graphing library for Python. Ideal for web-based visualizations, 3D plots, and complex interactive dashboards. Built on plotly.js, it allows users to zoom, pan, and hover over data points in a browser-based environment. Use for interactive charts, web applications, Jupyter notebooks, 3D data visualization, geographic maps, financial charts, animations, time-series analysis, and building production-ready dashboards with Dash.
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.
The foundational library for creating static, animated, and interactive visualizations in Python. Highly customizable and the industry standard for publication-quality figures. Use for 2D plotting, scientific data visualization, heatmaps, contours, vector fields, multi-panel figures, LaTeX-formatted plots, custom visualization tools, and plotting from NumPy arrays or Pandas DataFrames.
Comprehensive guide for NumPy - the fundamental package for scientific computing in Python. Use for array operations, linear algebra, random number generation, Fourier transforms, mathematical functions, and high-performance numerical computing. Foundation for SciPy, pandas, scikit-learn, and all scientific Python.
Open-source Python package for exploring, visualizing, and analyzing human neurophysiological data including EEG, MEG, sEEG, and ECoG.
Provides comprehensive guidance for Lime ECharts including chart creation, configuration, data visualization, and interactive charts. Use when the user asks about Lime ECharts, needs to create charts, visualize data, or work with ECharts features.
Node.js backend expert including Express, NestJS, and async patterns
Unified skill that guides spec creation through structured, interactive process.
Professional sub-skill for Matplotlib focused on high-performance animations, complex multi-figure layouts (GridSpec), interactive widgets, and publication-ready typography (LaTeX/PGF).