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Guide for building Graph Neural Networks with PyTorch Geometric (PyG).
Install Torch Geometric
$ npx skills add BioTender-max/awesome-bio-agent-skills --skill torch-geometric -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install BioTender-max/awesome-bio-agent-skills torch-geometric --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/BioTender-max/awesome-bio-agent-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/kdense/torch-geometric .claude/skills/torch-geometric && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "torch-geometric" agent skill from https://github.com/BioTender-max/awesome-bio-agent-skills/tree/main/skills/kdense/torch-geometric into .claude/skills/torch-geometric/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "torch-geometric", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/BioTender-max/awesome-bio-agent-skills/tree/main/skills/kdense/torch-geometricType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add BioTender-max/awesome-bio-agent-skills --skill torch-geometric -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install BioTender-max/awesome-bio-agent-skills torch-geometric --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/BioTender-max/awesome-bio-agent-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/kdense/torch-geometric .agents/skills/torch-geometric && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "torch-geometric" agent skill from https://github.com/BioTender-max/awesome-bio-agent-skills/tree/main/skills/kdense/torch-geometric into .agents/skills/torch-geometric/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "torch-geometric", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add BioTender-max/awesome-bio-agent-skills --skill torch-geometric -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install BioTender-max/awesome-bio-agent-skills torch-geometric --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/BioTender-max/awesome-bio-agent-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/kdense/torch-geometric .cursor/skills/torch-geometric && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "torch-geometric" agent skill from https://github.com/BioTender-max/awesome-bio-agent-skills/tree/main/skills/kdense/torch-geometric into .cursor/skills/torch-geometric/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "torch-geometric", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/BioTender-max/awesome-bio-agent-skills.git --path skills/kdense/torch-geometric--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add BioTender-max/awesome-bio-agent-skills --skill torch-geometric -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install BioTender-max/awesome-bio-agent-skills torch-geometric --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/BioTender-max/awesome-bio-agent-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/kdense/torch-geometric .gemini/skills/torch-geometric && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "torch-geometric" agent skill from https://github.com/BioTender-max/awesome-bio-agent-skills/tree/main/skills/kdense/torch-geometric into .gemini/skills/torch-geometric/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "torch-geometric", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install BioTender-max/awesome-bio-agent-skills torch-geometricInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add BioTender-max/awesome-bio-agent-skills --skill torch-geometric -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/BioTender-max/awesome-bio-agent-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/kdense/torch-geometric .github/skills/torch-geometric && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "torch-geometric" agent skill from https://github.com/BioTender-max/awesome-bio-agent-skills/tree/main/skills/kdense/torch-geometric into .github/skills/torch-geometric/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "torch-geometric", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add BioTender-max/awesome-bio-agent-skills --skill torch-geometric -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install BioTender-max/awesome-bio-agent-skills torch-geometric --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/BioTender-max/awesome-bio-agent-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/kdense/torch-geometric .opencode/skills/torch-geometric && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "torch-geometric" agent skill from https://github.com/BioTender-max/awesome-bio-agent-skills/tree/main/skills/kdense/torch-geometric into .opencode/skills/torch-geometric/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "torch-geometric", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
torch-geometric- GitHub stars
- 199
- Token cost
- ~4.3k tokens
- SKILL.md length
- 1,032 words
- Files
- 7 (incl. references)
- Skills in repo
- 23
- Repo updated
- First seen
- Licence
- Custom licence
At a glance
Guide for building Graph Neural Networks with PyTorch Geometric (PyG).
- Works in 4 steps: propagate() orchestrates the message… → message() defines what info flows along… → aggregate() combines messages at each… → …
- The user asks about graph neural networks
- SKILL.md covers Core Concepts, Building GNN Models, Task-Specific Patterns and Scaling to Large Graphs, plus 4 more sections
- Calls uv
What it does
Torch Geometric is an agent skill from BioTender-max/awesome-bio-agent-skills. Guide for building Graph Neural Networks with PyTorch Geometric (PyG). Use this skill whenever the user asks about graph neural networks, GNNs, node classification, link prediction, graph classification, message passing networks, heterogeneous graphs, neighbor sampling, or any task involving torchgeometric / PyG. Also trigger when you see imports from torchgeometric, or the user mentions graph convolutions (GCN, GAT, GraphSAGE, GIN), graph data structures, or working with relational/network data. Even if the user…
Its SKILL.md is about 4.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 7 other files, including reference files (for example `references/custom_datasets.md`, `references/explainability.md` and `references/heterogeneous.md`).
It sits in AI & LLM Engineering, covering Deep learning. It works with PyTorch. The repository describes itself as: A curated collection of AI agent skills for biomedical research, covering genomics, proteomics, single-cell analysis, clinical AI, and protein design.
When your agent uses it
- The user asks about graph neural networks
- Node classification
- Link prediction
- Graph classification
Example prompts
- “graph learning”
- “geometric deep learning”
- “/torch-geometric”
Requirements
- Python 3
Workflow steps
4 steps, taken from the first numbered list in SKILL.md.
- propagate() orchestrates the message passing
- message() defines what info flows along each edge (the phi function)
- aggregate() combines messages at each node (sum/mean/max)
- update() transforms the aggregated result (the gamma function)
What it can do on your machine
Read from SKILL.md and the folder at commit 8cbdd18. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Shell commands in SKILL.md call:
uv
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md. Its commands use uv, which can reach the network depending on how they are called.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Torch Geometric loads about 4.3k tokens when it runs, and up to ~15k if it reads all its reference files. Until then it costs about 152 tokens; SKILL.md has 1,032 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
Its licence (Custom licence) doesn't allow us to republish the file, so here is its outline and opening line. It has 1,032 words (~4,258 tokens).
“PyG is the standard library for Graph Neural Networks built on PyTorch. It provides data structures for graphs, 60+ GNN layer implementations, scalable mini-batch training, and support for heterogeneous graphs.”
- name
- torch-geometric
Files
SKILL.md and 6 other files (references) in skills/kdense/torch-geometric of BioTender-max/awesome-bio-agent-skills.
- SKILL.md
- references/custom_datasets.md
- references/explainability.md
- references/heterogeneous.md
- references/link_prediction.md
- references/message_passing.md
- references/scaling.md
Open the folder on GitHubat commit 8cbdd18
Compare with similar skills
Torch Geometric next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Torch Geometric this skillBioTender-max/awesome-bio-agent-skills | 199 | — | ~4.3k | Automated safety check: Pass | Custom licence | |
| Add Uint Supportpytorch/pytorch | 104k | 2 repos | ~2.3k | Automated safety check: Pass | Custom licence | |
| CLIP Image-Text MatchingOrchestra-Research/AI-Research-SKILLs | 13k | 7 repos | ~1.7k | Automated safety check: Pass | MIT | |
| Add Torch Shapes Examplefacebook/pyrefly | 7.1k | — | ~1.3k | Automated safety check: Pass | MIT | |
| MUSA GPU Training Optimizeropen-infra-skills/infra-skills | 141 | — | ~1.7k | Automated safety check: Pass | Apache-2.0 | |
| Ghstack CIpytorch/pytorch | 104k | — | ~1.4k | Automated safety check: Pass | Custom licence |
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Questions about Torch Geometric
What does Torch Geometric do?
Guide for building Graph Neural Networks with PyTorch Geometric (PyG). Torch Geometric is an agent skill from BioTender-max/awesome-bio-agent-skills. Guide for building Graph Neural Networks with PyTorch Geometric (PyG).
When should I use Torch Geometric?
Torch Geometric fits situations like: the user asks about graph neural networks; Node classification; link prediction; graph classification.
How do I install Torch Geometric in Claude Code?
Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill torch-geometric -a claude-code`. Or copy the skill folder (skills/kdense/torch-geometric in BioTender-max/awesome-bio-agent-skills) into .claude/skills/torch-geometric in your project. Claude Code loads it when a task matches its description.
How do I install Torch Geometric in Codex?
Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill torch-geometric -a codex`. Or copy the skill folder (skills/kdense/torch-geometric in BioTender-max/awesome-bio-agent-skills) into .agents/skills/torch-geometric in your project. Codex loads it when a task matches its description.
Can I use Torch Geometric in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add BioTender-max/awesome-bio-agent-skills --skill torch-geometric -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/torch-geometric, .gemini/skills/torch-geometric, .github/skills/torch-geometric and .opencode/skills/torch-geometric in your project.
What does Torch Geometric need to run?
Going by SKILL.md and its folder, Torch Geometric needs the command-line tools its instructions call (uv). Our summary lists: Python 3.
Does Torch Geometric access the network?
SKILL.md contains no URLs. Its commands use uv, which can reach the network depending on how they are called. This is read from the text; nothing was executed.
Is Torch Geometric safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Torch Geometric use?
Torch Geometric has a licence file (the repository's licence) that doesn't match a standard licence. Read it on GitHub before reusing the skill.
How many tokens does Torch Geometric use?
About 4.3k tokens (SKILL.md is roughly 17k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 11k tokens, read only when the agent opens those files.
What are the alternatives to Torch Geometric?
Skills that share tags, products or a category with Torch Geometric: Add Uint Support (pytorch/pytorch, 104k stars), CLIP Image-Text Matching (Orchestra-Research/AI-Research-SKILLs, 13k stars), Add Torch Shapes Example (facebook/pyrefly, 7.1k stars) and MUSA GPU Training Optimizer (open-infra-skills/infra-skills, 141 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Torch Geometric?
BioTender-max (a GitHub user) maintains it in BioTender-max/awesome-bio-agent-skills, which has 199 GitHub stars. The repository holds 23 skills in this directory. The repository was last updated on July 1, 2026.
Source: BioTender-max/awesome-bio-agent-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.