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review-r

Audit R scripts for quality, reproducibility, and coding standards.

8|2|Updated Apr 2, 2026
Search Tags:#research#audit#quality#r#scripts#code-review#reproducibility
One-click install
npx skills add https://github.com/Felpix-Studios/social-science-research --skill review-r-felpix-studios
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: review-r
Source: https://github.com/Felpix-Studios/social-science-research/tree/main/skills/review-r
Command: npx skills add https://github.com/Felpix-Studios/social-science-research --skill review-r-felpix-studios

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Audit R scripts for quality, reproducibility, and adherence to coding standards without altering source code.

Core Features & Use Cases

  • Automated review protocol: Runs a comprehensive R code review against your scripts, producing a report per script.
  • Non-destructive: Does not modify your R files; outputs are placed in quality_reports for review.
  • Use Case: When you need an independent assessment of an existing R project to prepare for publication or collaboration.

Quick Start

Run a review on your target R scripts to generate a detailed quality report.

Frequently Asked Questions about review-r

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

FAQPage Schema
How do I audit R scripts for quality and reproducibility without modifying the source code?▼

You can audit R scripts for reproducibility by running an automated review protocol that evaluates code against predefined standards and outputs a report to a quality_reports directory, leaving the original source files completely unaltered.

What is an automated R code review and how does it check coding standards?▼

An automated R code review is a non-destructive assessment that checks scripts against reference conventions, such as rules/r-code-conventions.md, generating a detailed markdown report that highlights reproducibility issues and standard violations per script.

How do I prepare an R project for publication or collaboration assessment?▼

To prepare an R project for publication, run an impartial automated review on the scripts in your scripts/ directory to identify quality issues and generate a comprehensive quality report without editing the actual codebase.

Do I need a specific directory structure to review R code reproducibility?▼

Yes, this review protocol applies to projects containing R code within a scripts/ directory and requires access to a standard protocol and reference standards file to evaluate adherence to coding conventions.

Can I integrate automated R script quality reports into existing project workflows?▼

The review process integrates into project workflows by saving the generated assessment reports directly into a quality_reports folder, allowing you to review identified issues independently before making manual code adjustments.

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