scGPT

SkillProductivity

Runs scGPT-style single-cell analysis like cell annotation, embeddings, and perturbation prediction on gene datasets.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the scGPT skill

About this capability

Use scGPT-style single-cell foundation model workflows. Use when a task asks for single-cell embeddings, perturbation prediction, cell annotation, batch transfer, or gene-program analysis.

What this skill tells your AI

The instructions your AI receives, as published by companion-inc/feynman in skills/scgpt/SKILL.md and read by ahel’s review.

Use this skill for single-cell foundation model analysis.

Workflow:

  1. Record dataset source, organism, modality, preprocessing, gene identifiers, cell labels, and perturbation design.
  2. Verify model/checkpoint/package availability before running.
  3. Save AnnData or matrix manifests, preprocessing code, model version, embeddings, predictions, plots, and logs.
  4. Compare labels or predictions against source metadata, marker genes, perturbation controls, and literature.
  5. Preserve batch, donor, disease, and assay provenance in every summary table.

Do not present cell-state labels without marker or metadata support.

Signals

GitHub stars
9k
Forks
1k
Last commit
Sep 2026
Advanced
Catalog kind
skill
Gateway key
scgpt
Source
github.com/companion-inc/feynman