How does it assist with R package creation?

It provides comprehensive guidance on API design, managing dependencies, writing unit tests, and documenting functions to meet professional CRAN-like standards.

Can it help me migrate from the magrittr pipe?

Absolutely. The skill emphasizes the use of the native R pipe ( |> ) over the magrittr pipe ( %>% ) and provides clear patterns for updating legacy code.

Does it include performance optimization tools?

Yes, it integrates best practices for profiling code using profvis and benchmarking different approaches with the bench package to ensure maximum efficiency.

Does this skill support the latest tidyverse features?

Yes, it specifically prioritizes modern patterns introduced in dplyr 1.1.0 and later, including the .by grouping argument and join_by() syntax.

Modern R Development

Name: Modern R Development
Author: CodingKaiser

byCodingKaiser

0•

Data Science & ML

Implements modern R programming practices, tidyverse patterns, and performance optimizations for data science workflows.

This skill equips Claude with the latest R programming standards, focusing on the tidyverse ecosystem (dplyr 1.1+), native pipe operations, and efficient data-masking techniques with rlang. It provides a comprehensive framework for writing clean, performant R code, developing professional-grade packages, and optimizing existing scripts through rigorous profiling and benchmarking. Whether you are migrating legacy code or building complex data pipelines, this skill ensures your R projects adhere to current industry best practices and maintainable design patterns.

Key Features

01Modern tidyverse implementation including dplyr 1.1+ and native pipe syntax

02Performance profiling and benchmarking with profvis and bench

03Automated migration patterns from legacy base R to modern tidyverse

04Advanced data-masking and metaprogramming patterns using rlang

05Standardized R package development and API design guidance

060 GitHub stars

Use Cases

01Optimizing data processing bottlenecks in omics or large-scale analytics

02Refactoring legacy R scripts to use modern, readable tidyverse syntax

03Building and documenting professional R packages with robust testing

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add codingkaiser/claude-kaiser-skills r-development

For use in Claude.ai and ChatGPT

Key Features

01Modern tidyverse implementation including dplyr 1.1+ and native pipe syntax

02Performance profiling and benchmarking with profvis and bench

03Automated migration patterns from legacy base R to modern tidyverse

04Advanced data-masking and metaprogramming patterns using rlang

05Standardized R package development and API design guidance

060 GitHub stars

Use Cases

01Optimizing data processing bottlenecks in omics or large-scale analytics

02Refactoring legacy R scripts to use modern, readable tidyverse syntax

03Building and documenting professional R packages with robust testing

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add codingkaiser/claude-kaiser-skills r-development

For use in Claude.ai and ChatGPT