r-code-conventions

Enforce repository-local R coding standards for here() and data.table pipelines.

Updated Feb 21, 2026
One-click install
npx skills add https://github.com/choi-jaehyun/jaehyun-claude-workflow --skill r-code-conventions
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: r-code-conventions
Source: https://github.com/choi-jaehyun/jaehyun-claude-workflow/tree/main/.agents/skills/r-code-conventions
Command: npx skills add https://github.com/choi-jaehyun/jaehyun-claude-workflow --skill r-code-conventions

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

The R coding standards in this repository provide a unified, repeatable approach to writing, refactoring, and reviewing R code, reducing style drift and improving reproducibility across the project.

Core Features & Use Cases

  • Repo-local guidelines for using here(), data.table-first workflows, naming conventions, and transparent logging.
  • Guidance for script organization, pipeline structure, and reproducible workflows within the code/ directory.
  • Use cases include code reviews, collaborative development, and educational demonstrations requiring consistent R coding practices.

Quick Start

Review and apply these standards before editing or reviewing R scripts in the code/ directory.

Frequently Asked Questions about r-code-conventions

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

FAQPage Schema
How do I enforce R coding standards for reproducible data.table pipelines?

To enforce R coding standards for reproducible pipelines, this Skill provides repo-local guidelines for using here() for path resolution and structuring data.table-first workflows consistently across scripts.

What should I include in R code review guidelines for a collaborative project?

R code review guidelines should cover naming conventions, script organization within the code/ directory, pipeline structure, transparent logging, and here() path usage to ensure reproducibility and reduce style drift.

Can I use these R coding standards for refactoring scripts that don't use data.table?

These R coding standards are specifically designed for projects using data.table-based pipelines and here() for paths. While the general naming conventions apply, the core workflow guidance targets data.table-first environments.

Why does my R script fail reproducibility checks when using relative file paths?

R scripts fail reproducibility checks because relative paths break when working directories change. This Skill mandates using here() to construct robust, project-root-relative paths that remain consistent across different execution contexts.

What is the best way to organize R scripts in a reproducible data analysis project?

The best way to organize R scripts is placing them in a dedicated code/ directory and following structured pipeline conventions. This Skill defines script organization standards that promote transparent logging and reproducible workflows.