marimo

Create, edit, and debug reactive marimo notebooks with UI elements.

2|1|Updated Nov 30, 2025
One-click install
npx skills add https://github.com/nibzard/skills-kit --skill marimo
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: marimo
Source: https://github.com/nibzard/skills-kit/tree/main/skills/marimo
Command: npx skills add https://github.com/nibzard/skills-kit --skill marimo

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Automates the creation, debugging, and interactive enhancement of reactive Python notebooks using the marimo framework, enabling consistent patterns and best practices.

Core Features & Use Cases

  • Create new marimo notebooks with a clear, documented structure.
  • Debug reactive execution, manage dependencies, and optimize performance.
  • Add interactive UI elements and patterns to build dashboards, reports, or ML workflows.
  • Reuse code patterns and utilities to accelerate project setup and maintainability.
  • Convert traditional notebooks to marimo format for progressive migration.

Quick Start

Install marimo in your project and follow the patterns to scaffold a new notebook, add cells with @app.cell decorators, and run the app to interactively explore data.

Frequently Asked Questions about marimo

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

FAQPage Schema
How do I create reactive Python notebooks for dynamic dashboards?▼

You can create reactive Python notebooks for dynamic dashboards by using marimo to scaffold a documented structure with @app.cell decorators, adding interactive UI elements, and running the app to explore data.

What is the best way to convert traditional notebooks to reactive marimo format?▼

Converting traditional notebooks to reactive marimo format enables progressive migration by applying structured guidance and reusable code patterns to transform standard cells into a clean, UI-enabled data workflow.

How do I debug reactive execution and manage dependencies in marimo notebooks?▼

Debugging reactive execution in marimo notebooks involves using provided error-handling recommendations to manage dependencies, optimize performance, and enforce consistent best-practice patterns across your data workflow.

Do I need external dependencies to build interactive ML workflows with marimo?▼

Building interactive ML workflows with marimo requires no external dependencies beyond the marimo framework itself and common data science libraries already present in your environment.

Can I add UI elements directly inside Python notebooks for data analysis?▼

You can add interactive UI elements directly inside Python notebooks using marimo patterns to build reports and data analysis dashboards without needing separate frontend tools.

Why should I use reactive notebooks instead of traditional Python notebooks for data workflows?▼

Reactive notebooks enforce a clean, UI-enabled data workflow by automating dependency management and execution order, overcoming the hidden-state and out-of-order execution issues common in traditional Python notebooks.