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Agent skill

Sc Cytotrace

by TianGzlab in TianGzlab/OmicsClaw

Load when computing per-cell differentiation potency / stemness scores from gene-expression complexity on a scRNA AnnData via the CytoTRACE-simple method.

Apache-2.0Auto-check passedResearch & Science

Install Sc Cytotrace

skills CLI
$ npx skills add TianGzlab/OmicsClaw --skill sc-cytotrace -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install TianGzlab/OmicsClaw sc-cytotrace --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/TianGzlab/OmicsClaw.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/singlecell/scrna/sc-cytotrace .claude/skills/sc-cytotrace && rm -rf skills-src

Use ~/.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/

Facts

Skill name
sc-cytotrace
GitHub stars
161
Token cost
~1.1k tokens
SKILL.md length
394 words
Files
10 (incl. references)
Skills in repo
88
Repo updated
First seen
Licence
Apache-2.0

At a glance

Load when computing per-cell differentiation potency / stemness scores from gene-expression complexity on a scRNA AnnData via the CytoTRACE-simple method.

  • Tasks that involve Bioinformatics
  • SKILL.md covers Use from a step, API, Methods and parameters and Gotchas, plus 3 more sections
  • Runs Python scripts from its folder; calls python

What it does

Sc Cytotrace is an agent skill from TianGzlab/OmicsClaw. Load when computing per-cell differentiation potency / stemness scores from gene-expression complexity on a scRNA AnnData via the CytoTRACE-simple method. Skip when ordering cells along a trajectory (use sc-pseudotime); marker-based cell-type labelling (use sc-cell-annotation).

Its SKILL.md is about 1.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 12 other files, including reference files (for example `_api.py`, `examples/example_step.py` and `references/methodology.md`).

It sits in Research & Science, covering Bioinformatics. It works with AnnData. The repository describes itself as: Conversational & memory-enabled AI research partner for multi-omics analysis. CLI + Desktop App (installers in Releases). From biological idea to full research paper. The licence is Apache-2.0.

When your agent uses it

  • Tasks that involve Bioinformatics

Example prompts

  • “/sc-cytotrace”

Requirements

  • Python 3

What it can do on your machine

Read from SKILL.md and the folder at commit 90a3bec. 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

    Ships script files (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    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

Sc Cytotrace loads about 1.1k tokens when it runs, and up to ~2.3k if it reads all its reference files. Until then it costs about 73 tokens; SKILL.md has 394 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~73
When it runs · the whole SKILL.md, loaded when a task matches
~1.1k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~2.3k

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

The full file from TianGzlab/OmicsClaw at commit 90a3bec, republished under its Apache-2.0 licence (© TianGzlab). 394 words, ~1,062 tokens.

Download SKILL.mdSave it as .claude/skills/sc-cytotrace/SKILL.md (or your agent's skills folder). This skill also uses 9 other files; get the full folder from GitHub.
name
sc-cytotrace
description
Load when computing per-cell differentiation potency / stemness scores from gene-expression complexity on a scRNA AnnData via the CytoTRACE-simple method. Skip when ordering cells along a trajectory (use sc-pseudotime); marker-based cell-type labelling (use sc-cell-annotation).
tags
singlecell, scrna, cytotrace, potency, stemness, differentiation

sc-cytotrace

Use from a step

python
potency = load_skill("sc-cytotrace")
adata = potency.cytotrace(read_input("expression.h5ad"), layer="counts")
write_output(potency.potency_table(adata), "tables/potency.csv")
write_output(potency.potency_figure(adata), "figures/potency.png")
write_output(adata, "intermediate/adata_potency.h5ad")

The function annotates the input in place. The PBMC example in examples/example_step.py demonstrates the call, not biological differentiation.

API

<!-- api:begin generated from _api.py; regenerate with run.py api <skill dir> --write -->
cytotrace(adata, *, n_neighbors: int=30, layer: str | None=None)

Annotate a complexity-based potency proxy in place, preserving X.

This is CytoTRACE-simple, not the published CytoTRACE or CytoTRACE 2. It counts positive expression, smooths rank scores, ranks them again and bins them into six relative categories. Existing neighbors are reused.

:param adata: AnnData with expression and optionally PCA/neighbors. :param n_neighbors: Neighbors to construct when absent; default 30. :param layer: Expression layer for gene detection; None uses X. Use counts or unscaled log expression, not centered/scaled X. :returns: The same AnnData with cytotrace_score, cytotrace_gene_count and cytotrace_potency in obs; run_info returns diagnostics. :raises ValueError: The input is empty, a layer is missing, or neighbors < 1.

run_info(adata, *, keep: bool=True) -> dict

Read JSON potency diagnostics; keep=False removes them from uns.

potency_table(adata) -> pd.DataFrame

Return per-cell score, category and detected-gene count, indexed by cell.

potency_composition(adata) -> pd.DataFrame

Return counts for the six relative potency bins; they are not cell-type calls.

potency_figure(adata)

Return a matplotlib Figure showing the potency score distribution.

<!-- api:end -->

Methods and parameters

CytoTRACE-simple counts positive expression, rank-normalizes that complexity, smooths on a neighbor graph, ranks again and assigns six relative bins. It is not the published CytoTRACE or CytoTRACE 2 model.

n_neighbors=30 retains the CLI default and is used only if a neighbor graph must be built. layer=None uses X; specify a counts layer or unscaled log-normalized expression. Computation is deterministic for a fixed graph.

Show full SKILL.md (145 more words)Show less

Gotchas

  • The second rank transform makes the six cytotrace_potency bins approximately equal-sized when scores have no ties. Labels such as Totipotent are names of these bins, not evidence that those cells are biologically totipotent (_api.py:112).
  • Positive values in centered/scaled X do not count detected genes. Use layer="counts" or an unscaled matrix; inspect potency_table (_api.py:72).
  • Existing neighbors are reused regardless of n_neighbors. The CLI's processed PBMC demo has scaled X and is retained only for compatibility (_api.py:80).
  • run_info(adata)["degenerate"] marks at most one occupied category. It does not raise; the CLI mirrors this under result.json["summary"].

Inputs & Outputs

Input is AnnData with expression, optionally PCA and neighbors. The API adds cytotrace_score, cytotrace_potency and cytotrace_gene_count to obs and returns tables/Figures without writing files.

The CLI writes processed.h5ad, tables/cytotrace_scores.csv, report.md, result.json, figure_data/cytotrace_embedding.csv and potency/distribution plots under figures/. R-enhanced plots are optional.

Key CLI

bash
python skills/singlecell/scrna/sc-cytotrace/sc_cytotrace.py --demo --output /tmp/sc_cytotrace_demo
python skills/singlecell/scrna/sc-cytotrace/sc_cytotrace.py --input normalized.h5ad --n-neighbors 30 --output results/

Dependencies

anndata, matplotlib, numpy, pandas, scanpy, scipy

© TianGzlab, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 9 other files (references) in skills/singlecell/scrna/sc-cytotrace of TianGzlab/OmicsClaw.

  • SKILL.md
  • _api.py
  • examples/example_step.py
  • references/methodology.md
  • references/output_contract.md
  • references/parameters.md
  • references/r_visualization.md
  • sc_cytotrace.py
  • tests/test_cytotrace_api.py
  • tests/test_sc_cytotrace_methods.py

Open the folder on GitHubat commit 90a3bec

Compare with similar skills

Sc Cytotrace 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.

Sc Cytotrace compared with similar skills
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Sc Cytotrace this skillTianGzlab/OmicsClaw161—~1.1kAutomated safety check: PassApache-2.0
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ScgptJimLiu/science-skills2284 repos~1.3kAutomated safety check: PassApache-2.0
PyDESeq2 Differential Expressiondavila7/claude-code-templates33k11 repos~4kAutomated safety check: PassMIT
Anndatadavila7/claude-code-templates33k11 repos~2.5kAutomated safety check: PassMIT
Single-Cell Initial AnalysisLigphiDonk/Oh-my--paper7391 repos~1.4kAutomated safety check: PassMIT

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Works with

Categories

Questions about Sc Cytotrace

What does Sc Cytotrace do?

Load when computing per-cell differentiation potency / stemness scores from gene-expression complexity on a scRNA AnnData via the CytoTRACE-simple method. Sc Cytotrace is an agent skill from TianGzlab/OmicsClaw. Load when computing per-cell differentiation potency / stemness scores from gene-expression complexity on a scRNA AnnData via the CytoTRACE-simple method.

When should I use Sc Cytotrace?

Sc Cytotrace fits situations like: tasks that involve Bioinformatics.

How do I install Sc Cytotrace in Claude Code?

Run `npx skills add TianGzlab/OmicsClaw --skill sc-cytotrace -a claude-code`. Or copy the skill folder (skills/singlecell/scrna/sc-cytotrace in TianGzlab/OmicsClaw) into .claude/skills/sc-cytotrace in your project. Claude Code loads it when a task matches its description.

How do I install Sc Cytotrace in Codex?

Run `npx skills add TianGzlab/OmicsClaw --skill sc-cytotrace -a codex`. Or copy the skill folder (skills/singlecell/scrna/sc-cytotrace in TianGzlab/OmicsClaw) into .agents/skills/sc-cytotrace in your project. Codex loads it when a task matches its description.

Can I use Sc Cytotrace 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 TianGzlab/OmicsClaw --skill sc-cytotrace -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/sc-cytotrace, .gemini/skills/sc-cytotrace, .github/skills/sc-cytotrace and .opencode/skills/sc-cytotrace in your project.

What does Sc Cytotrace need to run?

Going by SKILL.md and its folder, Sc Cytotrace needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python 3.

Does Sc Cytotrace access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Sc Cytotrace 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 Sc Cytotrace use?

Sc Cytotrace is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Sc Cytotrace use?

About 1.1k tokens (SKILL.md is roughly 4.2k 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 1.3k tokens, read only when the agent opens those files.

What are the alternatives to Sc Cytotrace?

Skills that share tags, products or a category with Sc Cytotrace: Scanpy Single-Cell Analysis (davila7/claude-code-templates, 33k stars), Scgpt (JimLiu/science-skills, 228 stars), PyDESeq2 Differential Expression (davila7/claude-code-templates, 33k stars) and Anndata (davila7/claude-code-templates, 33k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Sc Cytotrace?

TianGzlab (a GitHub organization) maintains it in TianGzlab/OmicsClaw, which has 161 GitHub stars. The repository holds 88 skills in this directory. The repository was last updated on October 7, 2026.

Source: TianGzlab/OmicsClaw on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.