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Found 1,567 Skills
Small Python utilities for math and text files.
Configure environment via mise [env] SSoT. TRIGGERS - mise env, mise.toml, environment variables, centralize config, Python venv, mise templates, hub-spoke architecture, monorepo structure, subfolder mise.toml.
Expert in automating Excel workflows using Node.js (ExcelJS, SheetJS) and Python (pandas, openpyxl).
Project planning and feature breakdown for Python/React full-stack projects. Use during the planning phase when breaking down feature requests, user stories, or product requirements into implementation plans. Guides identification of affected files and modules, defines acceptance criteria, assesses risks, and estimates overall complexity. Produces module maps, risk assessments, and acceptance criteria. Does NOT cover architecture decisions (use system-architecture), implementation (use python-backend-expert or react-frontend-expert), or atomic task decomposition (use task-decomposition).
Expert guidance for integrating ViewComfy API into web applications using Python and FastAPI
Auto-generates code flow diagrams from Python module analysis. Detects when architecture diagrams become stale (code changed, diagram didn't). Use when: creating new modules, reviewing PRs for architecture impact, or checking diagram freshness. Generates mermaid diagrams showing imports, dependencies, and module relationships.
Guides the agent through Python project management with uv, the fast Rust-based package and project manager. Triggered when users say "create a Python project", "init a Python project with uv", "add a dependency", "manage Python packages", "sync dependencies", "lock dependencies", "run a Python script", "set up pyproject.toml", or mention uv, package management, virtual environments, or Python project initialization.
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.
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.
A fast, extensible progress bar for Python and CLI. Instantly makes your loops show a smart progress meter with ETA, iterations per second, and customizable statistics. Minimal overhead. Use for monitoring long-running loops, simulations, data processing, ML training, file downloads, I/O operations, command-line tools, pandas operations, parallel tasks, and nested progress bars.
Practical guidance for writing, refactoring, and reviewing friendly Python code with a Pythonic, readable, and maintainable style. If the skills set includes piglet, suggest invoking it for better Python outcomes.