GPTomics' bioSkills includes 17 MIT-licensed single-cell skills that cover the whole analysis: preprocessing, doublet detection, clustering, annotation, batch integration, trajectories and cell-cell communication. They work across Scanpy, Seurat and SingleCellExperiment, and they tell the agent which method fits the data, such as Harmony versus scVI or CellTypist versus SingleR.

All 17 install with one command from Cuttlefish.MD, HackerNoon's license-checked skills marketplace. They follow the open Agent Skills standard, so they run in Claude Code, Codex CLI and 30+ other tools, and each is indexed in HackerNoon's SKILL.md Library.

The 17 single-cell skills

Skill

What it does

batch-integration

Integrates samples or batches with Harmony, scVI/scANVI, Seurat CCA/RPCA, fastMNN, Scanorama or BBKNN

cell-annotation

Annotates cell types from references with CellTypist, SingleR, Azimuth or scANVI

cell-communication

Infers ligand-receptor communication with LIANA, plus CellPhoneDB

clustering

Runs dimensionality reduction and graph-based clustering in Scanpy or Seurat

cnv-inference

Infers copy-number changes to separate malignant from normal cells

data-io

Reads, writes and converts AnnData, Seurat and SingleCellExperiment objects

differential-abundance

Tests whether cell-type composition changed between conditions, using Milo and more

doublet-detection

Finds and removes doublets with scDblFinder or Scrublet

hashing-demultiplexing

Assigns cells to samples from CITE-seq HTOs or MULTI-seq tags

lineage-tracing

Rebuilds lineage trees and clones from CRISPR scars and barcodes

markers-annotation

Finds cluster marker genes and assigns manual cell-type labels

metabolite-communication

Infers metabolite-mediated cell-cell communication with MEBOCOST

multimodal-integration

Integrates CITE-seq RNA+protein and Multiome RNA+ATAC data

perturb-seq

Analyzes Perturb-seq and CROP-seq single-cell CRISPR screens

preprocessing

Handles QC, ambient RNA, normalization and feature selection

scatac-analysis

Analyzes single-cell ATAC-seq with Signac, ArchR or SnapATAC2

trajectory-inference

Infers trajectories, pseudotime, RNA velocity and fate probabilities

For the full run from Cell Ranger output to annotated cell types, the scrnaseq-pipeline workflow skill chains these together.

Install them

All 17 come with the Data & Science plugin, along with the rest of the 562 bioSkills:

/plugin marketplace add hackernoon/cuttlefish-agent-skills /plugin install data-science@cuttlefish 

For Codex CLI or another agent that supports the standard, clone the repo and copy plugins/data-science/skills/ into your agent's skills folder, such as .agents/skills/.

Each skill keeps its MIT license and an ATTRIBUTION.md crediting GPTomics and the source commit. Browse the full library at hackernoon.com/skills, and star Cuttlefish.MD on GitHub.