by Shubhamsaboo
visualization-expert is a lightweight skill for chart selection, visualization best practices, and example matplotlib or plotly code. Use it to choose better charts, critique dashboards, and apply clear, accessible data visualization guidance from a single SKILL.md file.
by K-Dense-AI
Use the sympy skill for exact symbolic math in Python, including algebra, calculus, matrices, physics formulas, number theory, geometry, and code generation. It helps you keep expressions exact, choose the right SymPy modules, and avoid float-heavy mistakes. Best for users who need a practical sympy guide for symbolic workflows and sympy for Data Analysis.
by K-Dense-AI
qutip is a Python quantum physics simulation skill for open quantum systems, dissipation, time evolution, and quantum optics. Use this qutip guide for master equations, Lindblad dynamics, decoherence, cavity QED, state/operator simulation, and Scientific Python examples. Not for circuit-based quantum computing.
by K-Dense-AI
shap skill for model interpretability and explainable AI. Use it to understand predictions, compute feature attributions, choose SHAP plots, and debug model behavior for Data Analysis across tree, linear, deep learning, and black-box models.
by K-Dense-AI
Seaborn is a seaborn skill for Python statistical visualization with pandas-friendly inputs and strong defaults. Use it for quick exploration of distributions, relationships, categorical comparisons, box plots, violin plots, pair plots, and heatmaps. Built on matplotlib for static, publication-ready charts.
by K-Dense-AI
scikit-learn helps you build classical machine learning workflows in Python. Use this scikit-learn skill for classification, regression, clustering, preprocessing, model evaluation, hyperparameter tuning, and pipelines. It’s a practical scikit-learn guide for tabular data and repeatable model development.
by K-Dense-AI
scientific-visualization is a meta-skill for publication-ready figures. Use it for journal submission plots with multi-panel layouts, significance annotations, error bars, colorblind-safe palettes, and Nature/Science/Cell-style formatting. It orchestrates matplotlib, seaborn, and plotly for scientific-visualization for Data Visualization work.
by K-Dense-AI
matplotlib skill for Python plotting with full control over axes, labels, legends, layouts, and export formats. Use it for scientific figures, multi-panel analyses, custom chart types, and reproducible visualizations when you need more precision than a generic chart prompt. It is a strong matplotlib guide for Data Analysis and publication-ready plots.
by K-Dense-AI
The matlab skill helps you generate, debug, and adapt MATLAB or GNU Octave code for matrix operations, data analysis, visualization, statistics, optimization, and scientific computing. Use it for runnable MATLAB usage, MATLAB for Data Analysis, MATLAB-to-Python translation, or Octave-compatible scripts when you need less trial-and-error than a generic prompt.
by K-Dense-AI
geopandas skill for Python geospatial vector data analysis, including shapefiles, GeoJSON, and GeoPackage files. Use it to read, clean, join, buffer, clip, reproject, and export spatial data with less guesswork.
