Automates the entire scientific research lifecycle from data analysis and hypothesis generation to producing publication-ready LaTeX manuscripts.
Denario is a sophisticated multiagent AI system designed to streamline scientific workflows by orchestrating specialized agents for hypothesis generation, methodology development, and computational analysis. Built on the AG2 and LangGraph frameworks, it empowers researchers to transform raw datasets into structured findings and formatted papers for journals like APS. The skill offers both fully automated end-to-end pipelines and hybrid workflows that allow for human-in-the-loop customization at any stage of the research process.
Key Features
01Publication-ready LaTeX paper generation for journals
02Automated hypothesis generation from raw datasets
030 GitHub stars
04Structured methodology development and execution
05Multiagent orchestration using AG2 and LangGraph
06Interactive GUI for research workflow management
Use Cases
01Executing computational experiments and generating reproducible results
02Automating the creation of journal-formatted LaTeX manuscripts with figures
03Generating novel research ideas and hypotheses from complex datasets