rowan

rowan is a skill for Claude Code, Codex from synthetic-sciences/openscience. It costs 115 tokens per session (3,069 once invoked), scanned A, original, Apache-2.0.

A Python API for running computational chemistry workflows in the cloud. It can calculate molecular properties, optimize molecular shapes, search conformers, dock proteins and ligands, and run protein cofolding models.

In plain words
What is it for?
Use it for pKa and solubility estimates, geometry optimization, conformer searches, docking, protein cofolding, and other supported molecular calculations.
Why use it?
It lets you automate chemistry simulations without maintaining a local compute cluster or learning several separate chemistry packages.

Skill for Claude CodeCodex

About the project

synthetic-sciences/openscience is an AI workbench that carries out scientific research by reading papers, forming hypotheses, writing and running code, conducting experiments, analyzing results, and preparing reports. Researchers use it for work in machine learning, biology, physics, and chemistry with remote or local models. Catalogue add-ons extend its scientific workflows through skills and instructions.

synthetic-sciences/openscience · 3,473 stars · on GitHub

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/synthetic-sciences/openscience/rowan
Any agent
npx skills add synthetic-sciences/openscience --skill rowan
Clone the repo
git clone --depth 1 https://github.com/synthetic-sciences/openscience

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for rowan

README.md
[![agentmods](https://agentmods.dev/badge/skills/synthetic-sciences/openscience/rowan.svg)](https://agentmods.dev/skills/synthetic-sciences/openscience/rowan)
Your own site
<a href="https://agentmods.dev/skills/synthetic-sciences/openscience/rowan"><img src="https://agentmods.dev/badge/skills/synthetic-sciences/openscience/rowan.svg" alt="Measured on agentmods" height="20"></a>
Per session 115 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,069 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00115 $0.03069
Opus 5 $0.00057 $0.01535
Sonnet 5 $0.00023 $0.00614
Haiku 4.5 $0.00012 $0.00307

Measured yesterday against content hash aca7a5236586, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

rowan scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

  • rowan — 92% identical, 8 lines differ
backend/cli/skills/coding/rowan/SKILL.md · 426 lines

How it starts

The opening of the file, as written. The whole thing — 426 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Rowan: Cloud-Based Quantum Chemistry Platform

Overview

Rowan is a cloud-based computational chemistry platform that provides programmatic access to quantum chemistry workflows through a Python API. It enables automation of complex molecular simulations without requiring local computational resources or expertise in multiple quantum chemistry packages.

Key Capabilities:

  • Molecular property prediction (pKa, redox potential, solubility, ADMET-Tox)
  • Geometry optimization and conformer searching
  • Protein-ligand docking with AutoDock Vina
  • AI-powered protein cofolding with Chai-1 and Boltz models
  • Access to DFT, semiempirical, and neural network potential methods
  • Cloud compute with automatic resource allocation

Why Rowan:

  • No local compute cluster required
  • Unified API for dozens of computational methods
  • Results viewable in web interface at labs.rowansci.com
  • Automatic resource scaling

Installation and Authentication

Installation

uv pip install rowan-python

Authentication

Generate an API key at labs.rowansci.com/account/api-keys.

Option 1: Direct assignment

import rowan
rowan.api_key = "your_api_key_here"

Option 2: Environment variable (recommended)

export ROWAN_API_KEY="your_api_key_here"

The API key is automatically read from ROWAN_API_KEY on module import.

Verify Setup

import rowan

# Check authentication
user = rowan.whoami()
print(f"Logged in as: {user.username}")
print(f"Credits available: {user.credits}")

Core Workflows

1. pKa Prediction

Calculate the acid dissociation constant for molecules:

import rowan
import stjames

# Create molecule from SMILES
mol = stjames.Molecule.from_smiles("c1ccccc1O")  # Phenol

# Submit pKa workflow
workflow = rowan.submit_pka_workflow(
    initial_molecule=mol,
    name="phenol pKa calculation"
)

# Wait for completion
workflow.wait_for_result()
workflow.fetch_latest(in_place=True)

# Access results
print(f"Strongest acid pKa: {workflow.data['strongest_acid']}")  # ~10.17

Read the full file on GitHub · 426 lines

Files

What ships with it

6 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. yesterday First seen · 426 lines · 115 tokens per session scan A aca7a5236586

Subscribe to this mod's changes

rowan is a skill published in the GitHub repository synthetic-sciences/openscience (3,473 stars, last pushed today), licensed Apache-2.0. It adds 115 tokens to every session and 3,069 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

Related

Other skills, from other repositories

meta-paper-write

Use this meta-skill instead of answering directly when the current user asks to draft or produce a new academic/research paper or LaTeX manuscript. It uses multi-skill orchestration for manuscript workflows that need source search, citation planning, experiment or figure/table placeholders, drafting, length checks…

opensquilla/opensquilla · 125 tokens

paper-revision-author

Revise independently drafted paper sections into one coherent LaTeX body before the abstract is written.

opensquilla/opensquilla · 24 tokens

paper-section-author

Write one publication-style research-paper section as a bounded, citation-grounded LaTeX fragment from a writing plan, outline, citation plan, and optional figure/table context.

opensquilla/opensquilla · 38 tokens

meta-arxiv-daily-digest-deck

Fetch the day's top arXiv submissions in a chosen category, write a structured per-paper digest, render the digest as a PPTX deck (one slide per paper), and persist the digest to long-term memory. Use for a daily 'arxiv morning briefing' — manual fire or cron-scheduled.

opensquilla/opensquilla · 71 tokens

paper-quality-gate

Deterministic pre-compile gate for meta-paper-write. Enforces length/citation verdicts and rejects unsupported empirical-result claims when no user evidence was supplied.

opensquilla/opensquilla · 37 tokens

paper-latex-sanitizer

Deterministically normalize safe LaTeX punctuation and replace unsupported forecast magnitudes with explicit placeholders before meta-paper-write publication gates run.

opensquilla/opensquilla · 33 tokens