denario

---
name: denario
description: Multiagent AI system for scientific research assistance that automates research workflows from data analysis to publication. This skill should be used when generating research ideas from datasets, developing research methodologies, executing computational experiments, performing literature searches, or generating publication-ready papers in LaTeX format. Supports end-to-end research pipelines with customizable agent orchestration.
---

# Denario

## Overview

Denario is a multiagent AI system designed to automate scientific research workflows from initial data analysis through publication-ready manuscripts. Built on AG2 and LangGraph frameworks, it orchestrates multiple specialized agents to handle hypothesis generation, methodology development, computational analysis, and paper writing.

## When to Use This Skill

Use this skill when:
- Analyzing datasets to generate novel research hypotheses
- Developing structured research methodologies
- Executing computational experiments and generating visualizations
- Conducting literature searches for research context
- Writing journal-formatted LaTeX papers from research results
- Automating the complete research pipeline from data to publication

## Installation

Install denario using uv (recommended):

```bash
uv init
uv add "denario[app]"
```

Or using pip:

```bash
uv pip install "denario[app]"
```

For Docker deployment or building from source, see `references/installation.md`.

## LLM API Configuration

Denario requires API keys from supported LLM providers. Supported providers include:
- Google Vertex AI
- OpenAI
- Other LLM services compatible with AG2/LangGraph

Store API keys securely using environment variables or `.env` files. For detailed configuration instructions including Vertex AI setup, see `references/llm_configuration.md`.

## Core Research Workflow

Denario follows a structured four-stage research pipeline:

### 1. Data Description

Define the research context by specifying available data and tools:

```python
from denario import Denario

den = Denario(project_dir="./my_research")
den.set_data_description("""
Available datasets: time-series data on X and Y
Tools: pandas, sklearn, matplotlib
Research domain: [specify domain]
""")
```

### 2. Idea Generation

Generate research hypotheses from the data description:

```python
den.get_idea()
```

This produces a research question or hypothesis based on the described data. Alternatively, provide a custom idea:

```python
den.set_idea("Custom research hypothesis")
```

### 3. Methodology Development

Develop the rese

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