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review-r

Review R scripts in code/ and generate per-script quality reports.

Updated Feb 21, 2026
Search Tags:#reports#r#static-analysis#quality-assurance#lint#code-review#reproducibility
One-click install
npx skills add https://github.com/choi-jaehyun/jaehyun-claude-workflow --skill review-r-choi-jaehyun
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: review-r
Source: https://github.com/choi-jaehyun/jaehyun-claude-workflow/tree/main/.agents/skills/review-r
Command: npx skills add https://github.com/choi-jaehyun/jaehyun-claude-workflow --skill review-r-choi-jaehyun

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Automates the quality review of R scripts to identify defects, consistency issues, and reproducibility gaps.

Core Features & Use Cases

  • Batch code-review: run standardized checks on multiple R scripts in code/ to surface issues from style to correctness.
  • Per-script reporting: produce individual reports saved to quality_reports/[script_name]_r_review.md.
  • Use Case: In a data science project with dozens of R scripts, obtain consistent feedback without editing the source.

Quick Start

Review all R scripts in code/ to generate per-script quality reports.

Frequently Asked Questions about review-r

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

FAQPage Schema
How do I automate code review for multiple R scripts in a data science project?▼

Automate R script code review by running standardized checks across all scripts in the code/ directory, identifying defects and consistency issues while generating per-script quality reports without editing source files.

What is static analysis for reproducibility gaps in R scripts?▼

Static analysis for R scripts identifies reproducibility gaps by scanning code for defects and consistency issues, ensuring data science workflows meet quality assurance standards before generating reports.

Can I review a single R file instead of batching all scripts in the code directory?▼

Yes, the R code review process can target a single file or process all scripts located in code/, excluding code/temp/ and code/archive/ directories, producing individual reports for each.

Do I need any local dependencies to run automated R script quality checks?▼

Yes, running automated R script quality checks requires the local $r-reviewer and $r-code-conventions stacks to evaluate defects, consistency issues, and reproducibility gaps.

Where are the generated R code review reports saved?▼

R code review reports are saved as Markdown files to the quality_reports/ directory, formatted as quality_reports/[script_name]_r_review.md for each evaluated script.

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