torch-geometric-graph-neural-networks SKILL.md skillA
torch-geometric-graph-neural-networks from jaechang-hits/sciagent-skills is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add jaechang-hits/sciagent-skills/torch-geometric-graph-neural-networks@git:20260428.81ea2d2Pins git:20260428.81ea2d2 in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- jaechang-hits/sciagent-skills
- Path
skills/scientific-computing/torch-geometric-graph-neural-networks/SKILL.md- Versions recorded
- 2
- Latest version
- git:20260428.81ea2d2, committed Apr 28, 2026
- First version recorded
- Feb 18, 2026
- Size
- 20,581 bytes
- Repository stars
- 381
- License
- a license file GitHub does not identify
PyTorch Geometric (PyG) for graph neural networks: node/graph classification, link prediction with GCN, GAT, GraphSAGE, GIN. Message passing, mini-batches, heterogeneous graphs, neighbor sampling, explainability. Supports molecules (QM9, MoleculeNet), social/knowledge graphs, 3D point clouds. For non-graph DL use PyTorch; for classical graph algorithms use NetworkX.
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# PyTorch Geometric (PyG) — Graph Neural Networks ## Overview PyTorch Geometric is a library built on PyTorch for developing and training Graph Neural Networks (GNNs). It provides 40+ convolutional layers, mini-batch processing via block-diagonal adjacency matrices, neighbor sampling for large-scale graphs, and heterogeneous graph support for multi-type node/edge networks. ## When to Use - Node classification on citation, social, or biological networks - Graph-level classification (molecular activity, protein function) - Link prediction (knowledge graphs, recommendation systems) - Molecular property prediction (drug discovery, quantum chemistry) - 3D point cloud processing and mesh analysis - Large-scale graph learning with neighbor sampling (>100K nodes) - Heterogeneous graphs with multiple node/edge types - **For non-graph deep learning** → use PyTorch directly - **For traditional graph algorithms (shortest path, centrality)** → use NetworkX ## Prerequisites ```bash pip install torch torch_geometric # Optional sparse operations (recommended): # pip install pyg_lib torch_scatter torch_sparse torch_cluster ``` ```python import torch import torch.nn.functional as F …
Read the whole file at its exact version.
How to install
mdr add jaechang-hits/sciagent-skills/torch-geometric-graph-neural-networks@sha256:44558f5f29b44399The line at the top of this page pins the label git:20260428.81ea2d2, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
[](https://markdownregistry.com/a/art_bu4vovbi3m6d3y4q)
1 badge image fetches in 30 days. What the badge shows.
Versions
The registry has recorded 2 versions of this file, between Feb 18, 2026 and Apr 28, 2026, about one every 69 days.
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| git:20260428.81ea2d2 latest | 2026-04-28 | 81ea2d2 | 20,581 B | A | view · diff |
| git:20260218.e460066 | 2026-02-18 | e460066 | 20,706 B | A | view |
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (20581 bytes)
- pass: No zero-width or bidi control characters
- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
- pass: No base64 blob over 200 characters
- pass: No link to a raw IP address
- pass: No script tag
Source
jaechang-hits/sciagent-skills · 381 stars · license a license file GitHub does not identify · pushed 2026-10-16 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_bu4vovbi3m6d3y4q GET https://markdownregistry.com/api/v1/resolve?ref=jaechang-hits/sciagent-skills/torch-geometric-graph-neural-networks GET https://markdownregistry.com/api/v1/blob/44558f5f29b44399ca391d547822625fb3bb293672b269828aaaec58851f77dc
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Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.