denario

Name: denario
Availability: InStock
Author: robinbarvaag

Automate scientific research workflows from data analysis to LaTeX paper creation.

Updated Jan 10, 2026

Search Tags:#research #data analysis #latex #scientific writing #hypothesis generation #multiagent

Ready to run

npx skills add https://github.com/robinbarvaag/poynt --skill denario-robinbarvaag

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: denario
Source: https://github.com/robinbarvaag/poynt/tree/main/.github/skills/denario
Command: npx skills add https://github.com/robinbarvaag/poynt --skill denario-robinbarvaag

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill automates the entire scientific research pipeline, from generating novel hypotheses and developing methodologies to executing computational experiments and producing publication-ready papers.

Core Features & Use Cases

Automated Research Workflow: Manages hypothesis generation, methodology design, data analysis, and manuscript writing.
Multiagent Orchestration: Leverages specialized AI agents for different research tasks.
Publication Generation: Creates LaTeX papers formatted for specific journals.
Use Case: A researcher can input a dataset and research domain, and Denario will propose hypotheses, outline an experimental design, perform the analysis, and draft a scientific paper.

Quick Start

Use the denario skill to generate a research paper from a dataset description.

Frequently Asked Questions about denario

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I automate scientific research workflows from data analysis to LaTeX publication?▼

Automating scientific research workflows involves using a multiagent AI system to handle hypothesis generation, data analysis, and LaTeX paper creation. Denario orchestrates this entire pipeline end-to-end, from initial dataset input to publication-ready manuscript.

Can I generate research hypotheses and experimental designs automatically from a dataset?▼

Generating research hypotheses and experimental designs automatically from a dataset is supported by Denario. It uses specialized AI agents to analyze your specified research domain, propose testable hypotheses, and outline a matching experimental methodology.

Does this multiagent research assistant work with AG2 and LangGraph frameworks?▼

This multiagent research assistant integrates directly with AG2 and LangGraph frameworks. These integrations enable the orchestration of specialized agents that manage different stages of the computational research and publication pipeline.

What is the best way to create LaTeX papers formatted for specific journals using AI?▼

Creating LaTeX papers formatted for specific journals using AI is best handled by automating the manuscript writing stage. Denario processes your computational experiment results and generates publication-ready LaTeX documents tailored to target journal requirements.

Do I need prior multiagent system knowledge to use this automated research pipeline?▼

Prior multiagent system knowledge is not required to use this automated research pipeline. You can input a dataset description and research domain, and the system autonomously manages the specialized agents for methodology, analysis, and writing.

What are the limitations of using multiagent AI for scientific writing and computational experiments?▼

Limitations of using multiagent AI for scientific writing include the need for human oversight to verify generated hypotheses and computational experiment accuracy. The system automates the research pipeline but requires expert review to validate scientific conclusions.