Agent skill

torch-geometric

Graph Neural Networks (PyG). Node/graph classification, link prediction, GCN, GAT, GraphSAGE, heterogeneous graphs, molecular property prediction, for geometric deep learning.

foryourhealth111-pixelgithub.com/foryourhealth111-pixelGitHub ↗
claude-codecodexships scriptsApache-2.0
Install
npx skills add foryourhealth111-pixel/Vibe-Skills --skill torch-geometric --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 7
SKILL.md size: 20 KB
Bundled scripts: yes
Path: bundled/skills/torch-geometric/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 2,593
Language: Python
Read our review of the source →

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# PyTorch Geometric (PyG) ## Routing Boundary Use this skill only for PyTorch Geometric, torch_geometric, PyG, graph neural networks, GCN/GAT, graph classification, node classification, link prediction, and heterogeneous graph learning. Do not use it for generic neural networks, CNN/image classification, graph visualization, or molecule-only tasks unless PyG or graph neural network modeling is exp

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About this skill
What does the torch-geometric skill do?

Graph Neural Networks (PyG). Node/graph classification, link prediction, GCN, GAT, GraphSAGE, heterogeneous graphs, molecular property prediction, for geometric deep learning.

How do I install it?

Run `npx skills add foryourhealth111-pixel/Vibe-Skills --skill torch-geometric --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From foryourhealth111-pixel/Vibe-Skills, a repository with 2,593 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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