Denario is a multiagent AI system for Claude Code that automates the scientific research lifecycle, including data analysis, experiment execution, and manuscript writing.

How does Denario handle data analysis?

It uses specialized agents to interpret data descriptions, write analysis code (using tools like pandas and sklearn), and generate visual results.

Which journal formats does Denario support?

It currently supports American Physical Society (APS) formatting, with a modular structure that allows for additional journal styles and custom LaTeX templates.

Can I provide my own research hypotheses to Denario?

Absolutely. While Denario can generate ideas from data, you can also manually set your own research ideas and methodologies for the agents to process.

Does Denario require specific local dependencies?

Yes, Denario requires Python 3.12 or higher. For LaTeX compilation, it is recommended to have a TeX distribution installed or use the provided Docker container.

Denario Scientific Research Assistant

Name: Denario Scientific Research Assistant
Author: Activer007

byActiver007

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Data Science & ML

Automates end-to-end scientific research workflows from initial data analysis to publication-ready LaTeX manuscripts.

Denario is a powerful multiagent AI system designed to streamline the entire scientific research process within Claude Code. By orchestrating specialized agents through frameworks like AG2 and LangGraph, it assists researchers in generating novel hypotheses, developing structured methodologies, executing computational experiments, and producing journal-formatted papers in LaTeX. Whether you are starting with a raw dataset or a specific research question, Denario provides a modular and reproducible pipeline to accelerate scientific discovery and simplify the path to academic publication.

Key Features

01Execution of computational experiments and data visualizations

02Journal-formatted LaTeX paper generation (e.g., APS style)

03Structured research methodology development and documentation

04Literature search integration for research context

050 GitHub stars

06Automated hypothesis generation from raw datasets

Use Cases

01Building reproducible research pipelines using multiagent orchestration

02Generating novel research ideas and hypotheses from experimental data

03Automating the creation of publication-ready manuscripts for academic journals

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add activer007/ordinary-claude-skills denario

For use in Claude.ai and ChatGPT

Download Skill