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review-r

Review R scripts for quality, reproducibility, and academic standards.

6|14|Updated May 7, 2019
Search Tags:#quality assurance#code review#academic research#reproducibility#R#script analysis
One-click install
npx skills add https://github.com/irudik/repo-template --skill review-r-irudik
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: review-r
Source: https://github.com/irudik/repo-template/tree/main/.agents/skills/review-r
Command: npx skills add https://github.com/irudik/repo-template --skill review-r-irudik

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill addresses the critical need for high-quality, reproducible R code in academic research by automating a rigorous code review process.

Core Features & Use Cases

  • Comprehensive Code Auditing: Checks R scripts against a detailed protocol covering structure, reproducibility, domain correctness, and professional standards.
  • Automated Reporting: Generates detailed reports identifying issues without modifying source files.
  • Use Case: After writing an R script for a new simulation, use this Skill to ensure it adheres to project coding standards, uses correct formulas, and is set up for seamless reproduction by collaborators.

Quick Start

Run the review-r skill to review all R scripts in the code directory.

Frequently Asked Questions about review-r

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

FAQPage Schema
How do I review R scripts to ensure academic research reproducibility?▼

To review R scripts for reproducibility, analyze script structure, console output hygiene, function design, and RDS data patterns. This process generates detailed markdown reports identifying issues against academic research standards without modifying source files.

Can I audit R code quality without modifying the original source files?▼

Yes, you can audit R code quality without modifying source files by conducting a thorough script analysis. The review process checks structure, domain correctness, and figure quality, outputting results entirely in separate markdown reports.

What does a comprehensive R code review cover for simulation scripts?▼

A comprehensive R code review for simulation scripts covers script structure, reproducibility measures, function design, domain correctness, formula validation, figure quality, comment quality, error handling, and professional polish.

How do I check if my R script adheres to project coding standards?▼

You check R script adherence to project coding standards by running an automated code auditing protocol. This analyzes console output hygiene, error handling, and professional polish, generating a detailed report on compliance gaps.

Does automated R script analysis work for preparing code for collaborator reproduction?▼

Automated R script analysis works for collaborator reproduction by verifying reproducibility measures, RDS data patterns, and script structure. It ensures your code is set up correctly for seamless reproduction by generating a detailed markdown report.

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