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r-style-guide

Enforce R coding conventions for naming, formatting, and function design.

1|1|Updated May 5, 2026
Search Tags:#refactoring#error handling#code readability#naming conventions#function design#r style#tidyverse pipelines
One-click install
npx skills add https://github.com/cynkra/cynkra.ai.day --skill r-style-guide-cynkra
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: r-style-guide
Source: https://github.com/cynkra/cynkra.ai.day/tree/main/claude-code-r-skills/.claude/skills/r-style-guide
Command: npx skills add https://github.com/cynkra/cynkra.ai.day --skill r-style-guide-cynkra

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill prevents messy, inconsistent R code by providing concrete conventions for naming, spacing, structure, and function design that improve readability and maintainability.

Core Features & Use Cases

  • Function Writing Best Practices: Enforces clear structure, single responsibility, sensible return behavior, and readable defaults for common R workflows.
  • Naming and Argument Conventions: Standardizes snake_case naming, verb/noun roles, and rules for prefixed non-standard arguments.
  • Tidyverse-Friendly Layout: Guides pipe formatting, assignment style, indentation, and comment intent so code reviews are quicker and changes are safer.
  • Error Handling and User-Facing Messaging: Recommends structured user-facing abort patterns for clearer failure modes.
  • Use Case: Applying these rules while building data pipelines or helper functions in a small R project to keep behavior and style predictable across multiple collaborators.

Quick Start

Ask an AI to refactor your R function so it follows this R style guide’s naming, formatting, single-responsibility structure, and error handling conventions.

Frequently Asked Questions about r-style-guide

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

FAQPage Schema
How do I enforce consistent R naming and formatting conventions in my code?▼

To enforce consistent R naming and formatting, apply snake_case naming, specific spacing and layout rules, and standard indentation to improve code readability and maintainability across collaborative projects.

What is the best way to structure R functions for better readability?▼

The best way to structure R functions for readability is to enforce single responsibility, clear argument conventions, sensible return behavior, and readable defaults for common workflows.

How do I format tidyverse pipelines in R for collaborative data analysis?▼

To format tidyverse pipelines in R, apply specific pipe formatting, assignment styles, and indentation rules that make code reviews quicker and changes safer in collaborative projects.

How should I handle user-facing errors and abort patterns in R functions?▼

For error handling in R functions, use structured user-facing abort patterns to provide clearer failure modes and messaging when user-facing failures occur.

Can I use this R style guide to refactor existing code?▼

Yes, you can use this R style guide to refactor existing R functions by applying its rules for naming, formatting, single-responsibility structure, and error handling conventions.

When do I need to standardize R code conventions in a data pipeline project?▼

You need to standardize R code conventions when building data pipelines or helper functions in a project to keep behavior and style predictable across multiple collaborators.

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