Arboreto

Infer gene regulatory networks from expression data with GRNBoost2/GENIE3, scaled via Dask.

Tested · Works

Test report

Verdict
Tested · Works
Score
8.8/10
Tested
Jul 14, 2026
Environment
Claude Code 2.x (agent harness)
Upstream re-checked
Aug 10, 2026 · b837e2d

The Quick Start marks the `if __name__ == '__main__':` Dask guard as 'Critical' and repeats it in Troubleshooting; a baseline script assembled from general arboreto knowledge dropped that guard, which is a genuine hang/crash bug on macOS and Windows spawn-based multiprocessing.

Scored on four weighted criteria — install, triggering, output vs. baseline, docs. How scoring works

  • Installs cleanly 5/5
  • Triggers reliably 5/5
  • Output vs. baseline 7/10
  • Docs & honesty 5/5

What Arboreto does

Guides GRN inference from bulk or single-cell RNA-seq expression data using arboreto's GRNBoost2 and GENIE3 algorithms, including TF filtering, local/cluster Dask scaling, and pySCENIC integration. Triggers when analyzing transcriptomics data to find transcription-factor-to-target-gene regulatory relationships.

How to install Arboreto

git clone https://github.com/K-Dense-AI/scientific-agent-skills
cd scientific-agent-skills
mkdir -p ~/.claude/skills
cp -r skills/arboreto ~/.claude/skills/arboreto

Skills live in ~/.claude/skills/ (global) or .claude/skills/ (per-project). Restart Claude Code after installing.

Commands — how to trigger Arboreto

  • /arboreto Infer gene regulatory networks from expression data with GRNBoost2/GENIE3, scaled via Dask.

It also activates on plain-language prompts like these:

  • Infer a gene regulatory network with GRNBoost2
  • Run GENIE3 GRN inference on my expression matrix
  • Build a GRN from single-cell data using arboreto

Frequently asked questions

Is the Arboreto skill free?
Yes. The skill itself is free from K-Dense-AI/scientific-agent-skills. SkillProof publishes the install command and an independent test verdict at no cost.
Does Arboreto work with Claude Code?
We tested it with Claude Code 2.x (agent harness) on Jul 14, 2026. Verdict: Tested · Works. The Quick Start marks the `if __name__ == '__main__':` Dask guard as 'Critical' and repeats it in Troubleshooting; a baseline script assembled from general arboreto knowledge dropped that guard, which is a genuine hang/crash bug on macOS and Windows spawn-based multiprocessing.
What is the Arboreto SkillProof Score?
8.8/10 — installs cleanly 5/5, triggers reliably 5/5, output vs. baseline 7/10, docs & honesty 5/5.
How do I install Arboreto?
Copy the install command from this page, run it in your terminal, and restart Claude Code. Skills live in ~/.claude/skills/ (global) or .claude/skills/ inside a project.
Can I use Arboreto with Cursor, Copilot, Gemini CLI, Codex or other AI tools?
The SKILL.md format is native to Claude (Claude Code, Desktop, claude.ai). The instructions inside adapt to other assistants: Cursor rules, GitHub Copilot instructions, Windsurf rules, Custom GPTs, AGENTS.md for OpenAI Codex, and GEMINI.md for Google Gemini CLI — our conversion guides cover each, and the free converter on the tools page does the wrapping for you.