About
This skill provides specialized guidance for implementing Graph Neural Networks (GNNs) with PyTorch Geometric (PyG). It equips Claude with the patterns needed to handle irregular data structures like social networks, molecular graphs, and point clouds. Users can leverage this skill to implement state-of-the-art GNN architectures, handle mini-batching through block-diagonal adjacency matrices, and create custom message-passing layers for complex geometric deep learning tasks.
