rowan

Compute quantum chemistry workflows and molecular property predictions via the Rowan Python API.

1|Updated Mar 11, 2026
One-click install
npx skills add https://github.com/SciMate-AI/scicli --skill rowan-scimate-ai
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: rowan
Source: https://github.com/SciMate-AI/scicli/tree/main/internal/skills/bundled/claude-scientific-skills/skills/rowan
Command: npx skills add https://github.com/SciMate-AI/scicli --skill rowan-scimate-ai

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Rowan provides a cloud-based platform to run quantum chemistry workflows and molecular-property calculations without requiring local compute resources.

Core Features & Use Cases

  • Cloud compute access for pKa predictions, geometry optimization, conformer searches, docking, and AI protein cofolding.
  • Unified Python API to submit, monitor, and retrieve results; integrates with stjames.Molecule and RDKit inputs.
  • Real-world use cases include high-throughput screening, automated computational pipelines, and research-scale workflows.

Quick Start

Submit a pKa workflow for a molecule using Rowan's Python API.

Frequently Asked Questions about rowan

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I run quantum chemistry workflows without local compute resources?▼

You can run cloud-based quantum chemistry workflows by submitting molecular property predictions through a Python API. This approach offloads pKa predictions, geometry optimizations, and conformer searches to remote cloud compute infrastructure.

Can I use RDKit inputs for molecular docking and AI protein cofolding?▼

Yes, RDKit inputs are supported for molecular docking and AI protein cofolding. The Python API accepts RDKit objects to submit and monitor cloud-based quantum chemistry workflows for both small molecules and proteins.

What is needed to submit a pKa prediction workflow via Python?▼

To submit a pKa prediction workflow via Python, you need a Rowan API key and cloud compute access. You use the Python API to submit stjames.Molecule or RDKit inputs, then monitor and retrieve the calculation results.

Does this approach support high-throughput screening for automated computational pipelines?▼

Yes, the cloud-based quantum chemistry platform supports high-throughput screening and automated computational pipelines. You can programmatically submit, monitor, and retrieve large batches of molecular property predictions using the Python API.

How do I retrieve results from a geometry optimization or conformer search?▼

You retrieve geometry optimization and conformer search results by using the Python API to monitor submitted workflows and fetch outcomes. The API manages the full lifecycle of cloud-based quantum chemistry calculations and returns the computed molecular properties.