# Review R

> Run the R code review protocol on R scripts. Checks code quality, reproducibility, domain correctness, and professional standards. Produces a report without editing files. Make sure to use this skill whenever the user wants their existing R code evaluated or audited — not when they want new analysis written. Triggers include: "review my R script", "check my R code", "is my code replication-ready", "audit this R file", "does this code follow conventions", "will this reproduce", "check my analysis script", "code review", "review-r", or when the user has an existing .R file and wants quality feedback rather than new code.

- Skill: `brycewang-stanford/review-r-2` (Agent Skill)
- Install (CLI): `npx skillmds@latest add brycewang-stanford/review-r-2`
- Raw SKILL.md: https://api.skillmd.com/api/skills/brycewang-stanford/review-r-2/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Security
- Author: brycewang-stanford (https://skillmd.com/u/brycewang-stanford)
- Updated: 2026-09-09
- Page: https://skillmd.com/skills/brycewang-stanford/review-r-2

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# Review R Scripts

Run the comprehensive R code review protocol.

## Steps

1. **Identify scripts to review:**
   - If `$ARGUMENTS` is a specific `.R` filename: review that file only
   - If `$ARGUMENTS` is a name pattern (e.g., `model_name`): glob for matching `.R` files. If multiple matches, use AskUserQuestion:
     - header: "Scripts"
     - question: "Multiple R scripts match that pattern. Which should I review?"
     - multiSelect: true
     - options: list up to 4 matched files (label: filename, description: path and last modified). User can select multiple.
   - If `$ARGUMENTS` is `all`: review all R scripts in `scripts/R/` and `Figures/*/`
   - If `$ARGUMENTS` is empty, glob for all `.R` files. If multiple found, use AskUserQuestion as above.

2. **For each script, launch the `r-reviewer` agent** with instructions to:
   - Follow the full protocol in the agent instructions
   - Read `rules/r-code-conventions.md` for current standards
   - Save report to `quality_reports/[script_name]_r_review.md`

3. **After all reviews complete**, present a summary:
   - Total issues found per script
   - Breakdown by severity (Critical / High / Medium / Low)
   - Top 3 most critical issues

4. **IMPORTANT: Do NOT edit any R source files.**
   Only produce reports. Fixes are applied after user review.