rowan

rowan is a skill for Claude Code, Codex from foryourhealth111-pixel/Vibe-Skills. It costs 115 tokens per session (3,153 once invoked), scanned A, a copy of rowan, Apache-2.0.

A cloud platform with a Python API for computational chemistry, meaning computer-based simulations and calculations about molecules and proteins. It provides workflows for molecular properties, geometry, conformations, docking, and protein cofolding.

In plain words
What is it for?
Use it for pKa, redox, solubility, and toxicity-related predictions, geometry optimisation, conformer searches, protein-ligand docking, and protein cofolding.
Why use it?
It lets developers run these chemistry workloads through an API without managing local computing resources or several separate chemistry programs.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it for pKa, redox, solubility, and toxicity-related predictions, geometry optimisation, conformer searches, protein-ligand docking, and protein cofolding.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/foryourhealth111-pixel/vibe-skills/rowan
About the project

Vibe-Skills is a collection and routing system that helps AI agents discover, select, and coordinate specialized skills for completing tasks. It is intended for agents that need to organize workflows across many installed capabilities. The catalogue entries are skills and an agent belonging to this system.

foryourhealth111-pixel/Vibe-Skills · 3,252 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.

Any agent
npx skills add foryourhealth111-pixel/Vibe-Skills --skill rowan
Clone the repo
git clone --depth 1 https://github.com/foryourhealth111-pixel/Vibe-Skills

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/foryourhealth111-pixel/vibe-skills/rowan/github.svg)](https://agentmods.dev/skills/foryourhealth111-pixel/vibe-skills/rowan)
Your own site
<a href="https://agentmods.dev/skills/foryourhealth111-pixel/vibe-skills/rowan"><img src="https://agentmods.dev/badge/skills/foryourhealth111-pixel/vibe-skills/rowan/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for rowan

Your own site · 80×15
<a href="https://agentmods.dev/skills/foryourhealth111-pixel/vibe-skills/rowan"><img src="https://agentmods.dev/badge/skills/foryourhealth111-pixel/vibe-skills/rowan.svg" alt="Reviewed on agentmods" width="80" 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 3,153 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 92% copy Near-identical to another mod 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 5.1 $0.00115 $0.03153
Opus 5 $0.00057 $0.01577
Sonnet 5 $0.00023 $0.00631
Haiku 4.5 $0.00012 $0.00315

Measured 9d ago against content hash f94890062df7, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, 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 9d ago.

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

This is a copy

92% identical to rowan — 8 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

bundled/skills/rowan/SKILL.md · 428 lines

How it starts

The opening of the file, as written. The whole thing — 428 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Rowan: Cloud-Based Quantum Chemistry Platform

Routing Boundary

Use this skill only for explicit Rowan context, including Rowan, rowan-python, labs.rowansci.com, the Rowan API, or a Rowan-specific chemistry workflow. Do not use it for generic chemistry, RDKit, PubChem, ChEMBL, docking, pKa, conformer search, quantum chemistry, molecular machine learning, Boltz, or Chai-1 unless explicit Rowan context is present.

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

Read the full file on GitHub · 428 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. 9d ago First seen · 428 lines · 115 tokens per session scan A f94890062df7

Subscribe to this mod's changes

rowan is a skill published in the GitHub repository foryourhealth111-pixel/Vibe-Skills (3,252 stars, last pushed 12d ago), licensed Apache-2.0. It adds 115 tokens to every session and 3,153 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. It is 92% identical to rowan, differing in 8 lines, and is treated as a copy.

Related

Other skills, from other repositories

astropy

Core Python library for astronomy and astrophysics workflows that need Astropy APIs, including units/quantities, coordinates, FITS I/O, tables, time systems, WCS, and cosmology. Use when implementing or debugging astronomical data analysis code with Astropy.

K-Dense-AI/scientific-agent-skills · 56 tokens

cobrapy

Constraint-based metabolic modeling (COBRA). FBA, FVA, gene knockouts, flux sampling, SBML models, for systems biology and metabolic engineering analysis.

K-Dense-AI/scientific-agent-skills · 38 tokens

matlab

Build, review, migrate, and safely plan MATLAB or GNU Octave numerical workflows, including arrays, tabular/time data, tests, projects, graphics, MAT files, and explicit Python interoperability.

K-Dense-AI/scientific-agent-skills · 42 tokens

bioservices

Unified Python interface to 40+ bioinformatics services. Use when querying multiple databases (UniProt, KEGG, ChEMBL, Reactome) in a single workflow with consistent API. Best for cross-database analysis, ID mapping across services. For quick single-database lookups use gget; for sequence/file manipulation use…

K-Dense-AI/scientific-agent-skills · 73 tokens

pennylane

Hardware-agnostic quantum ML framework with automatic differentiation. Use when training quantum circuits via gradients, building hybrid quantum-classical models, or needing device portability across IBM/Google/Rigetti/IonQ. Best for variational algorithms (VQE, QAOA), quantum neural networks, and integration with…

K-Dense-AI/scientific-agent-skills · 98 tokens

nanoresearch-experiment

Generate a Python code skeleton from an experiment blueprint.

OpenRaiser/NanoResearch · 15 tokens