Agent skill · Data & Analytics

denario

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.

majiayu000github.com/majiayu000GitHub ↗
claude-codeMIT
Install
npx skills add majiayu000/claude-skill-registry --skill denario-aiskillstore-marketplace-2 --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 2
SKILL.md size: 7 KB
Bundled scripts: none
Path: skills/analysis/denario-aiskillstore-marketplace-2/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 534
Language: HTML

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# 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 ke

What's inside
Steps it walks through
  1. Overview
  2. When to Use This Skill
  3. Installation
  4. LLM API Configuration
  5. Core Research Workflow
  6. 1. Data Description
  7. 2. Idea Generation
  8. 3. Methodology Development
  9. 4. Results Generation
  10. 5. Paper Generation
  11. Available Journals
  12. Launching the GUI
  13. Common Workflows
  14. End-to-End Research Pipeline
Ships with 1 file
  • metadata.json
Commands it runs
uv init
uv add "denario[app]"
uv pip install "denario[app]"
denario run
More from claude-skill-registry
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About this skill
What does the denario skill do?

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.

How do I install it?

Run `npx skills add majiayu000/claude-skill-registry --skill denario-aiskillstore-marketplace-2 --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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