Fix descriptions to adhere to character limits

scientific-packages/umap-learn/SKILL.md

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 name: umap-learn
-description: "Comprehensive guide for UMAP (Uniform Manifold Approximation and Projection) - a fast, scalable dimensionality reduction technique for visualization, clustering, and machine learning. Use this skill for: dimensionality reduction of high-dimensional datasets (genes, proteins, images, text embeddings, sensor data), creating 2D/3D visualizations of complex data, preprocessing data for clustering algorithms (especially HDBSCAN), supervised and semi-supervised dimensionality reduction with labels, transforming new data using trained UMAP models, parametric UMAP with neural networks, feature engineering for downstream ML models, manifold learning and non-linear dimensionality reduction, comparing UMAP to t-SNE/PCA/other methods, inverse transforms and data reconstruction, aligned UMAP for temporal/batch data analysis. Triggers include: \"dimensionality reduction\", \"UMAP\", \"manifold learning\", \"data visualization\", \"clustering preprocessing\", \"high-dimensional data\", \"embedding\", \"reduce dimensions\", \"2D visualization\", \"3D visualization\", \"supervised dimensionality reduction\", \"parametric UMAP\", \"transform new data\", \"feature engineering\", \"HDBSCAN clustering\", \"t-SNE alternative\", \"non-linear dimensionality reduction\", \"inverse transform\", \"data reconstruction\", \"aligned embeddings\", \"batch effect correction\", \"temporal data analysis\"."
+description: "UMAP dimensionality reduction. Fast nonlinear manifold learning for 2D/3D visualization, clustering preprocessing (HDBSCAN), supervised/parametric UMAP, for high-dimensional data."
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 # UMAP-Learn