data-skill

Generate R and Python scripts for data analysis workflows in Quarto QMD projects.

1|1|Updated Feb 10, 2026
One-click install
npx skills add https://github.com/jason-jj-li/skills --skill data-skill-jason-jj-li
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: data-skill
Source: https://github.com/jason-jj-li/skills/tree/main/data-skill
Command: npx skills add https://github.com/jason-jj-li/skills --skill data-skill-jason-jj-li

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) and assets (resource) components.

What problem does it solve?

AI-driven hybrid data analysis workflow across R (tidyverse and ggplot2) and Python (pandas and seaborn) that reduces repetitive tasks by providing templates for common steps and AI-generated code, speeding up cleaning, processing, visualization, and reporting, including Quarto qmd integration.

Core Features & Use Cases

  • Hybrid templates for standard patterns (explore_variable, clean_data, process_data, plot_scatter, plot_bar, plot_box, statistical_test, plot_dag, tte_cloning) in R and their Python equivalents.
  • AI-assisted code generation for custom data needs when templates do not fit.
  • Built-in MCP Context7 guidance and QMD integration practices to streamline reproducible reporting.
  • Renders ready-to-run scripts and supports lifecycle phases: Understand, Prepare, Analyze, Visualize, and Report.

Quick Start

Describe your data task and let the templates or AI generate runnable code you can execute to start analysis.

Frequently Asked Questions about data-skill

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

FAQPage Schema
How do I automate data cleaning and visualization workflows in Python and R?▼

Automate data cleaning and visualization workflows by using pre-built R tidyverse and Python pandas templates that generate runnable code for standard data processing and plotting patterns.

What is the best way to generate reproducible Quarto reports from data analysis scripts?▼

Generate reproducible Quarto reports by integrating QMD project practices with AI-assisted code generation, streamlining the transformation of analysis scripts into formatted reporting outputs.

Can I use Python pandas and seaborn templates alongside R ggplot2 in the same project?▼

Use Python pandas and seaborn templates alongside R ggplot2 within a hybrid workflow, applying equivalent standard patterns for data exploration and plotting across both languages.

How do I create custom data transformation code when standard templates do not fit my dataset?▼

Create custom data transformation code by leveraging AI-assisted code generation to produce tailored scripts when standard templates for data processing and exploration do not fit.

Does this data analysis template support statistical testing and survival analysis tasks?▼

Data analysis templates support statistical testing and survival analysis tasks by providing standard patterns like statistical_test and tte_cloning for both R and Python environments.

How to handle end-to-end data exploration and reporting without writing repetitive boilerplate code?▼

Handle end-to-end data exploration and reporting by applying templates across lifecycle phases to understand, prepare, analyze, visualize, and report data, eliminating repetitive boilerplate.