r-skills
A curated collection of Claude Code configurations for modern R use. These skills, rules, commands, and agents help Claude Code understand R best practices and generate idiomatic, high-quality R code.

A curated collection of Claude Code configurations for modern R use. These skills, rules, commands, and agents help Claude Code understand R best practices and generate idiomatic, high-quality R code.
Patterns for Bayesian inference in R using brms, including multilevel models, DAG validation, and marginal effects. Use when…
R object-oriented programming guide for S7, S3, S4, and vctrs. Use when designing R classes or choosing an OOP system.
R package development guide covering dependencies, API design, testing, and documentation. Use when developing R packages.
R performance best practices including profiling, benchmarking, vctrs, and optimization strategies. Use when optimizing R code.
R style guide covering naming conventions, spacing, layout, and function design best practices. Use when writing R code.
rlang metaprogramming patterns for data-masking, injection operators, and dynamic dots. Use when writing functions that use tidy…
Test-driven development workflow for R using testthat. Use when writing new features, fixing bugs, or refactoring code. Enforces…
Modern tidyverse patterns for R including pipes, joins, grouping, purrr, and stringr. Use when writing tidyverse R code.
Senior R code review specialist. Use after writing code to review for security, quality, and best practices before committing.
Expert planning specialist for R projects. Use for feature implementation, architectural changes, or complex refactoring.…
Test-driven development specialist for R. Enforces test-first development with testthat. Use when writing new features, fixing…
Review code for security, quality, and best practices. Use after writing code and before committing.
Create an implementation plan before writing code. Use for new features, architectural changes, or complex refactoring.
Test-driven development workflow for R. Write tests first, then implement. Use for new features, bug fixes, and refactoring.
Run full R verification loop before committing. Checks build, lint, style, test coverage, and code quality.
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