Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add naity/FM4Life --skill scgptgit clone --depth 1 https://github.com/naity/FM4LifeWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/naity/fm4life/scgpt)<a href="https://agentmods.dev/skills/naity/fm4life/scgpt"><img src="https://agentmods.dev/badge/skills/naity/fm4life/scgpt.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00103 | $0.01967 |
| Opus 5 | $0.00051 | $0.00983 |
| Sonnet 5 | $0.00021 | $0.00393 |
| Haiku 4.5 | $0.00010 | $0.00197 |
Grade A, and why
scgpt scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 222 lines — stays where its author put it; the contents beside it link to each section on GitHub.
scGPT: Foundation Model for Single-Cell Biology
Overview
scGPT is a generative pretrained transformer trained on 33 million human single cells. It learns a universal representation of gene expression that transfers across tissues, diseases, and experimental batches.
Core tasks:
- Cell type annotation — classify cell types by fine-tuning on labeled data
- Cell embedding — zero-shot or fine-tuned cell representations for clustering/UMAP
- Perturbation prediction — predict gene expression changes after knockouts/overexpression
- Multi-batch integration — harmonize data across studies and technologies
- Reference mapping — map query cells onto a large reference atlas
- Gene regulatory network (GRN) — infer gene-gene relationships from learned embeddings
- Multi-omics — integrate RNA + protein (CITE-seq) or RNA + ATAC
Input: AnnData objects with raw or normalized count matrices (adata.X, genes × cells).
Output: Cell embeddings (stored in adata.obsm['X_scGPT']), cell type predictions, perturbation forecasts.
Installation
pip install scgpt "flash-attn<1.0.5"
Requirements: Python ≥ 3.7.12, PyTorch ≥ 1.13, CUDA 11.7 recommended.
Key dependencies installed automatically: scanpy, scvi-tools, numba, umap-learn, leidenalg.
Pretrained Checkpoints
Download from the scGPT Google Drive. Each checkpoint contains vocab.json, best_model.pt, and args.json.
| Model | Training data | Best for |
|---|---|---|
scGPT_human (whole-human) |
33M normal human cells | General-purpose default |
scGPT_CP (continual-pretrained) |
Refined on Tabula Sapiens | Zero-shot embedding, cell typing |
scGPT_brain |
13.2M human brain cells | Brain tissue analysis |
scGPT_blood |
10.3M hematopoietic cells | Blood / immune studies |
scGPT_heart |
1.8M cardiac cells | Heart tissue |
scGPT_lung |
2.1M lung cells | Lung tissue |
scGPT_kidney |
814K kidney cells | Kidney tissue |
scGPT_panCancer |
5.7M cancer cells | Cancer type classification |
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 7d ago First seen · 222 lines · 103 tokens per session scan A 5729c7cd425b
scgpt is a skill published in the GitHub repository naity/FM4Life (2 stars, last pushed 5mo ago), licensed MIT. It adds 103 tokens to every session and 1,967 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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