/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
$ npx -y skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill review-r --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/review-r
Context preview
The summary Claude sees to decide when to auto-load this skill.
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
SKILL.md
review-r.SKILL.mdname: review-r
description: >-
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.
argument-hint: "[filename, 'all', or analysis name pattern]"
allowed-tools: ["Read", "Grep", "Glob", "Write", "Task", "AskUserQuestion"]
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.
Read more
name: review-r description: >- 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. argument-hint: "[filename, 'all', or analysis name pattern]" allowed-tools: ["Read", "Grep", "Glob", "Write", "Task", "AskUserQuestion"]
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.
📌 文档结构(2026-07-22 起): 本文件是中文默认入口 —— banner + badges + 信任面 + 9 阶段流水线速览 + 76 行合集总表。 每个合集的完整描述、按用途分组、精确数字、验证方法在 docs/CONTENT_ZH.md(扩展正文,总表行内的 → 直接跳转到对应锚点)。 English version: README-en.md · 中文扩展正文:docs/CONTENT_ZH.md · README-zh-CN.md 已弃用(重定向占位) 🌐 语言: English |
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