denario

Automate scientific research workflows from hypothesis generation to LaTeX paper writing.

Updated Mar 10, 2026

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

Ready to run

npx skills add https://github.com/felixboehm/biochem-allergy --skill denario-felixboehm

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: denario
Source: https://github.com/felixboehm/biochem-allergy/tree/main/.claude/skills/denario
Command: npx skills add https://github.com/felixboehm/biochem-allergy --skill denario-felixboehm

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill automates complex, multi-stage scientific research workflows, from generating hypotheses and developing methodologies to executing computational experiments and writing publication-ready papers.

Core Features & Use Cases

End-to-End Research Automation: Manages the entire research pipeline.
Hypothesis Generation: Creates research ideas from data descriptions.
Methodology Development: Designs structured research plans.
Computational Execution: Runs experiments and generates results.
Publication Writing: Produces LaTeX papers formatted for scientific journals.
Use Case: A researcher can input their dataset description and research goals, and Denario will generate a hypothesis, outline a methodology, perform the analysis, and draft a LaTeX paper for submission.

Quick Start

Use the denario skill to automate a full research pipeline from data description to paper generation.

Frequently Asked Questions about denario

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

FAQPage Schema

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

Automate scientific research workflows using a multiagent system that orchestrates hypothesis generation, methodology development, computational experiments, and LaTeX publication writing to produce end-to-end research pipelines.

What is the best way to generate a research hypothesis from a dataset description?▼

Generate research hypotheses from data descriptions by using an automated multiagent system that analyzes your input and creates structured research ideas for your scientific writing pipeline.

Can I use pandas and sklearn for computational experiments in an automated research pipeline?▼

Use pandas and sklearn for computational experiments within an automated research pipeline that executes analysis and generates results for your scientific publication.

Does this research automation approach support generating LaTeX papers formatted for scientific journals?▼

Research automation supports LaTeX paper generation formatted for scientific journals, producing publication-ready drafts after completing computational experiments.

How do I develop a structured research methodology for computational experiments?▼

Develop a structured research methodology by inputting your dataset description and research goals into an automated system that designs a research plan and executes computational experiments.

What are the limitations of automating the entire research pipeline from data to publication?▼

Automating the research pipeline handles hypothesis generation, experiments, and LaTeX writing, but requires clear data descriptions and research goals to produce meaningful publication-ready results.