This one gives Claude the ability to apply dimensionality reduction techniques to your data, which is helpful when you're dealing with datasets that have too many features or when you need to visualize high-dimensional data in 2D or 3D. It covers the standard approaches like PCA, t-SNE, and UMAP. Most useful during the exploratory phase when you're trying to understand your data's structure or as a preprocessing step before training models. Part of aj-geddes's useful-ai-prompts collection, which has 245 stars on GitHub. If you're regularly working with datasets that have dozens or hundreds of features, this saves you from writing out the same dimensionality reduction instructions every time.
npx skills add https://github.com/aj-geddes/useful-ai-prompts --skill dimensionality-reduction