How do I install the Denario skill?

You can install Denario using the uv package manager with the command 'uv add denario[app]' or via pip.

What frameworks does Denario use for orchestration?

Denario is built on the AG2 and LangGraph frameworks to coordinate multiple specialized agents for tasks like hypothesis generation and data analysis.

Can Denario generate papers for specific journals?

Yes, it supports specific journal formatting styles such as APS (American Physical Society) and produces complete LaTeX source files.

Does Denario handle data visualization?

Yes, during the results generation stage, Denario can execute Python code to perform computations and create research visualizations.

What LLM providers are supported by Denario?

Denario supports Google Vertex AI, OpenAI, and other LLM services compatible with the AG2 and LangGraph ecosystems.

Denario Scientific Research Automation

Name: Denario Scientific Research Automation
Author: Microck

byMicrock

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데이터 과학 및 ML

Automates the end-to-end scientific research lifecycle from data analysis and hypothesis generation to publication-ready LaTeX manuscripts.

소개

Denario is a multiagent AI system designed to streamline scientific discovery by orchestrating specialized agents for complex research tasks. Built on the AG2 and LangGraph frameworks, it guides users through a structured four-stage pipeline: data description, hypothesis generation, methodology development, and computational analysis. The skill culminates in the production of journal-formatted LaTeX papers, making it an essential tool for researchers looking to accelerate their experimental workflows and automate the tedious aspects of academic documentation and formatting.

주요 기능

Journal-specific LaTeX paper generation with integrated figures
81 GitHub stars
Multiagent orchestration using AG2 and LangGraph frameworks
Automated hypothesis generation from raw datasets
Execution of computational experiments and data visualization
Structured research methodology development and planning

사용 사례

Developing and executing reproducible computational research pipelines from scratch
Generating novel research hypotheses from complex time-series or experimental datasets
Automating the creation of formatted scientific manuscripts for peer-reviewed journals

소개

주요 기능

Journal-specific LaTeX paper generation with integrated figures
81 GitHub stars
Multiagent orchestration using AG2 and LangGraph frameworks
Automated hypothesis generation from raw datasets
Execution of computational experiments and data visualization
Structured research methodology development and planning

사용 사례

Developing and executing reproducible computational research pipelines from scratch
Generating novel research hypotheses from complex time-series or experimental datasets
Automating the creation of formatted scientific manuscripts for peer-reviewed journals