Awesome-Agent-Skills-for-Empirical-Research 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.

install

source · Clone the upstream repo

git clone https://github.com/brycewang-stanford/Awesome-Agent-Skills-for-Empirical-Research

Claude Code · Install into ~/.claude/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/brycewang-stanford/Awesome-Agent-Skills-for-Empirical-Research "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/15-Felpix-Studios-social-science-research/skills/review-r" ~/.claude/skills/brycewang-stanford-awesome-agent-skills-for-empirical-research-review-r-aa3d9a && rm -rf "$T"

manifest: skills/15-Felpix-Studios-social-science-research/skills/review-r/SKILL.md

source content

Review R Scripts

Run the comprehensive R code review protocol.

Steps

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.
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
```
After all reviews complete, present a summary:
- Total issues found per script
- Breakdown by severity (Critical / High / Medium / Low)
- Top 3 most critical issues
IMPORTANT: Do NOT edit any R source files. Only produce reports. Fixes are applied after user review.