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ml-denario

Automate scientific research workflows from data analysis to LaTeX publication.

Updated Mar 13, 2026
Search Tags:#data analysis#research automation#latex#scientific writing#hypothesis generation#multiagent ai#computational experiments
One-click install
npx skills add https://github.com/biomaps-infra/blender-opencode --skill ml-denario
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: ml-denario
Source: https://github.com/biomaps-infra/blender-opencode/tree/main/.opencode/skills/ml-denario
Command: npx skills add https://github.com/biomaps-infra/blender-opencode --skill ml-denario

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill automates complex, end-to-end scientific research workflows, from generating novel hypotheses and designing methodologies to executing computational experiments and drafting publication-ready papers.

Core Features & Use Cases

  • End-to-End Research Automation: Manages the entire research pipeline, including data analysis, hypothesis generation, methodology development, computational experiments, and LaTeX paper writing.
  • Multiagent Orchestration: Leverages specialized AI agents coordinated by AG2 and LangGraph for robust and adaptable research processes.
  • Use Case: A researcher can input a dataset and research domain, and the skill will generate a novel hypothesis, outline a methodology, perform the necessary computations, and produce a draft of a LaTeX paper for submission.

Quick Start

Use the ml-denario skill to automate a full research pipeline starting with a data description.

Frequently Asked Questions about ml-denario

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

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

Multiagent AI research automation orchestrates specialized agents to generate hypotheses, execute computational experiments, and draft publication-ready LaTeX papers from a given dataset end-to-end.

What is multiagent orchestration for computational experiments and how does it work?▼

Multiagent orchestration coordinates specialized AI agents using frameworks like AG2 and LangGraph to manage adaptable research processes, from methodology development to computational execution and literature search.

Can I generate research ideas and hypotheses directly from raw datasets?▼

Yes, research automation workflows can ingest a dataset description to automatically generate novel hypotheses, outline appropriate research methodologies, and plan the necessary computational experiments.

How do I draft publication-ready scientific papers in LaTeX using AI?▼

AI-driven scientific writing automates the generation of publication-ready LaTeX documents by structuring computational experiment results, literature searches, and generated methodologies into a cohesive draft.

Does multiagent research automation require specific dependencies or framework installations?▼

No external dependencies are required to run the Skill itself, but it internally leverages multiagent frameworks like AG2 and LangGraph to coordinate the specialized AI agents for research tasks.

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