Improve package descriptions

scientific-packages/pytorch-lightning/SKILL.md

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 name: pytorch-lightning
-description: Comprehensive toolkit for PyTorch Lightning, a deep learning framework for organizing PyTorch code. Use this skill when working with PyTorch Lightning for training deep learning models, implementing LightningModules, configuring Trainers, setting up distributed training, creating DataModules, or converting existing PyTorch code to Lightning format. The skill provides templates, reference documentation, and best practices for efficient deep learning workflows.
+description: PyTorch Lightning deep learning framework skill for organizing PyTorch code and automating training workflows. Use this skill for: creating LightningModules with training_step/validation_step hooks, implementing DataModules for data loading and preprocessing, configuring Trainer with accelerators/devices/strategies, setting up distributed training (DDP/FSDP/DeepSpeed), implementing callbacks (ModelCheckpoint/EarlyStopping), configuring loggers (TensorBoard/WandB/MLflow), converting PyTorch code to Lightning format, optimizing performance with mixed precision/gradient accumulation, debugging with fast_dev_run/overfit_batches, checkpointing and resuming training, hyperparameter tuning with Tuner, handling multi-GPU/multi-node training, memory optimization for large models, experiment tracking and reproducibility, custom training loops, validation/testing workflows, prediction pipelines, and production deployment. Includes templates, API references, distributed training guides, and best practices for efficient deep learning development.
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 # PyTorch Lightning