rowan
Rowan is a cloud-native molecular modeling and medicinal-chemistry workflow platform with a Python API. Use for pKa and macropKa prediction, conformer and tautomer ensembles, docking and analogue docking, protein-ligand cofolding, MSA generation, molecular dynamics, permeability, descriptor workflows, and related small-molecule or protein modeling tasks. Ideal for programmatic batch screening, multi-step chemistry pipelines, and workflows that would otherwise require maintaining local HPC/GPU infrastructure.
npx skills add K-Dense-AI/scientific-agent-skills --skill rowan --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Rowan: Cloud-Native Molecular-Modeling and Drug-Design Workflows ## Overview Rowan is a cloud-native workflow platform for molecular simulation, medicinal chemistry, and structure-based design. Its Python API exposes a unified interface for small-molecule modeling, property prediction, docking, molecular dynamics, and AI structure workflows. Use Rowan when you want to run medicinal-chemistry or molecular-design workflows programmatically without maintaining local HPC infrastructure, GPU provisioning, or a collection of separate modeling tools. Rowan handles all infrastructure, result management, and computation scaling. ## When to use Rowan **Rowan is a good fit for:** - Quantum chemistry, semiempirical methods, or neural network potentials - Batch property prediction (pKa, descriptors, permeability, solubility) - Conformer and tautomer ensemble generation - Docking workflows (single-ligand, analogue series, pose refinement) - Protein-ligand cofolding and MSA generation - Multi-step chemistry pipelines (e.g., tautomer search → docking → pose analysis) - Batch medicinal-chemistry campaigns where you need consistent, scalable infrastructure **Rowan is not the right fit for:** - Sim
- Overview
- When to use Rowan
- Quick start
- Installation
- User and webhook management
- Authentication
- Molecule input formats
- Core usage pattern
- result() vs. streamresult()
- Working with results
- Using typed properties and .data
- Cache invalidation
- Projects, folders, and organization
- Projects
uv pip install rowan-python export ROWAN_API_KEY="your_api_key_here"
What does the rowan skill do?
Rowan is a cloud-native molecular modeling and medicinal-chemistry workflow platform with a Python API. Use for pKa and macropKa prediction, conformer and tautomer ensembles, docking and analogue docking, protein-ligand cofolding, MSA generation, molecular dynamics, permeability, descriptor workflows, and related small-molecule or protein modeling tasks. Ideal for programmatic batch screening, multi-step chemistry pipelines, and workflows that would otherwise require maintaining local HPC/GPU infrastructure.
How do I install it?
Run `npx skills add K-Dense-AI/scientific-agent-skills --skill rowan --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From K-Dense-AI/scientific-agent-skills, a repository with 32,619 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.