Claude Code Academic Workflow Guide
SkillAI & modelsClaude Code template for LaTeX, Beamer, and R research workflows
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What this skill tells your AI
The instructions your AI receives, as published by brycewang-stanford/auto-empirical-research-skills in skills/43-wentorai-research-plugins/skills/research/automation/claude-academic-workflow-guide/SKILL.md and read by ahel’s review.
Overview
A template and workflow guide for using Claude Code in academic research — managing LaTeX papers, Beamer presentations, R analysis scripts, and multi-agent peer review. Provides structured CLAUDE.md configurations, project templates, and automation patterns for common academic tasks. Designed for economists, social scientists, and quantitative researchers.
Project Structure
research-project/
├── CLAUDE.md # Claude Code instructions
├── paper/
│ ├── main.tex # Main LaTeX document
│ ├── references.bib # Bibliography
│ ├── sections/ # LaTeX sections
│ └── figures/ # Generated figures
├── slides/
│ ├── presentation.tex # Beamer slides
│ └── figures/
├── code/
│ ├── analysis.R # Main analysis
│ ├── data_clean.R # Data preparation
│ └── figures.R # Figure generation
├── data/
│ ├── raw/ # Original data
│ └── processed/ # Cleaned data
└── output/
├── tables/ # LaTeX tables
└── figures/ # PDF/PNG figures
CLAUDE.md Configuration
# Project: [Your Paper Title]
## Instructions
- This is an academic research project in economics
- LaTeX compiler: pdflatex (paper) or xelatex (if CJK)
- R version: 4.3+ with tidyverse, fixest, ggplot2
- Citation style: natbib, authoryear
- Always compile paper after LaTeX changes
- Run R scripts from project root
## Paper Conventions
- Use \input{sections/intro} for section includes
- Tables: booktabs package, generated from R
- Figures: PDF format, width=\textwidth
- Cross-refs: \label{sec:}, \label{tab:}, \label{fig:}
## R Conventions
- Style: tidyverse style guide
- Data: read from data/processed/
- Output: tables/ (LaTeX), figures/ (PDF)
- Reproducibility: set.seed(42) for all random ops
## Build Commands
- Paper: `cd paper && pdflatex main && bibtex main && pdflatex main && pdflatex main`
- Slides: `cd slides && pdflatex presentation`
- Analysis: `cd code && Rscript analysis.R`
LaTeX Paper Workflow
# Claude Code can manage the full LaTeX workflow:
# 1. Draft a section
# "Write the methodology section for our diff-in-diff analysis"
# 2. Generate tables from R output
# "Create a LaTeX table from the regression results in output/tables/"
# 3. Fix compilation errors
# "The paper won't compile — fix the LaTeX errors"
# 4. Update bibliography
# "Add the Callaway & Sant'Anna (2021) reference"
# 5. Format for submission
# "Format the paper for AER submission guidelines"
Beamer Presentations
% Template for academic presentations
\documentclass[aspectratio=169]{beamer}
\usetheme{metropolis}
\title{Your Presentation Title}
\subtitle{Conference/Seminar Name}
\author{Author Name}
\institute{University}
\date{\today}
\begin{document}
\maketitle
\begin{frame}{Motivation}
\begin{itemize}
\item Research question
\item Why it matters
\item What we do
\end{itemize}
\end{frame}
\begin{frame}{Data}
\input{figures/summary_stats_table}
\end{frame}
\begin{frame}{Results}
\centering
\includegraphics[width=0.8\textwidth]{figures/main_result.pdf}
\end{frame}
\end{document}
R Analysis Integration
# analysis.R — Main analysis script
library(tidyverse)
library(fixest)
library(modelsummary)
# Load cleaned data
df <- read_csv("data/processed/analysis_data.csv")
# Main regression
model1 <- feols(outcome ~ treatment | year + state, data = df)
model2 <- feols(outcome ~ treatment + controls | year + state,
data = df, cluster = ~state)
# Export table for LaTeX
modelsummary(
list("(1)" = model1, "(2)" = model2),
output = "output/tables/main_results.tex",
stars = c("*" = 0.1, "**" = 0.05, "***" = 0.01),
gof_map = c("nobs", "r.squared", "FE: year", "FE: state"),
)
# Export figure
ggplot(df, aes(x = year, y = outcome, color = treated)) +
geom_point(alpha = 0.3) +
geom_smooth(method = "loess") +
theme_minimal() +
labs(x = "Year", y = "Outcome", color = "Treatment Group")
ggsave("output/figures/treatment_trends.pdf", width = 8, height = 5)
Multi-Agent Review
### Self-Review Workflow
Use Claude Code to simulate peer review:
1. "Review this paper as a critical referee for AER"
2. "Check all mathematical derivations in section 3"
3. "Verify that all tables match the R code output"
4. "Check for consistency between text claims and results"
5. "List potential referee objections and how to address them"
Common Tasks
### Things to ask Claude Code:
- "Compile the paper and fix any errors"
- "Add robustness check using propensity score matching"
- "Create a Beamer slide summarizing Table 2"
- "Generate event study plot from the regression results"
- "Convert this Word draft to LaTeX format"
- "Check all cross-references are correct"
- "Format references in AEA style"
Use Cases
- Paper writing: LaTeX drafting and compilation workflow
- Data analysis: R script development and debugging
- Presentations: Beamer slide creation from paper content
- Self-review: Multi-agent review simulation
- Submission prep: Format conversion for journal submission
References
Signals
- GitHub stars
- 4k
- Forks
- 531
- Last commit
- Sep 2026
Advanced
- Item type
- skill
- Key
claude-academic-workflow-guide- Source
- github.com/brycewang-stanford/auto-empirical-research-skills
github.com/brycewang-stanford/auto-empirical-research-skills
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