latex-table
LaTeX回归表格生成Skill。辅助生成符合AER/QJE等顶刊格式的三线表,包括标准误聚类标注、显著性星标、固定效应标注。触发词:LaTeX表格/回归表/三线表/table制作/latex table
Install / Use
npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill latex-tableInstalls into whichever agent you are using.
SKILL.md
Installable skill definition
Quality Score
Category
Development & EngineeringSupported Platforms
Our assessment of latex-table
latex-table scores 88/100 on our quality scale, 783rd of 2,569 Development & Engineering skills we index (top 31%).
Its SKILL.md is 5.6 KB long, well organised into 21 sections with 10 code examples: a solid amount of guidance for an agent.
With 4,360 GitHub stars, it is one of the more widely adopted skills in the catalogue.
Maintenance, license and trust
- The repository was last updated 3 days ago, so latex-table is actively maintained.
- No license is declared. By default that means all rights are reserved: you can read it, but reusing or redistributing it is not clearly permitted. Ask the author before building on it commercially.
- Its trust signals score 88/100, with 1 caution from licensing, adoption, age or documentation. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
latex-table compared with similar skills
All 4 of these similar skills score higher than latex-table; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| latex-table (this skill)by brycewang-stanford | 88 | 4.4k | 3d ago | SKILL.md |
| Agent-Reachby Panniantong | 100 | 85.6k | 11d ago | CLAUDE.md |
| headroomby headroomlabs-ai | 100 | 73.9k | today | CLAUDE.md |
| ai-job-searchby MadsLorentzen | 100 | 44.0k | 6d ago | CLAUDE.md |
| claude-howtoby luongnv89 | 100 | 41.7k | today | CLAUDE.md |
Frequently asked questions
- How do I install latex-table?
- Run
npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill latex-table. The install tabs above show the steps for each supported agent. - Which AI agents does latex-table work with?
- It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
- Is latex-table safe to use?
- It declares no license and scores 88/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is latex-table still maintained?
- The repository was last updated 3 days ago, so latex-table is actively maintained.
Skill content
View source on GitHubname: latex-table description: LaTeX回归表格生成Skill。辅助生成符合AER/QJE等顶刊格式的三线表,包括标准误聚类标注、显著性星标、固定效应标注。触发词:LaTeX表格/回归表/三线表/table制作/latex table version: "1.0" metadata: openclaw: emoji: "📋" homepage: "https://github.com/SiyaoZheng/ai4ss-skills"
latex-table — LaTeX 回归表格生成Skill
本 Skill 辅助生成符合**经济学顶刊(AER, QJE, Econometrica, JPE)**格式规范的 LaTeX 回归表格。涵盖:标准三线表、面板数据固定效应表、工具变量表、事件研究表。
适用场景
- 论文写作中需要插入规范的回归结果表
- 将 Stata/Python/R 输出转换为 LaTeX 代码
- 按期刊要求排版三线表
- 生成主子表(Main Table)+ 在线附录表(Online Appendix Table)
核心理念
顶刊表格的核心要素:
- 清晰的信息层级——表头、分组、变量名层层递进
- 完整的统计信息——样本量、标准误、聚类层级、R²、F统计量
- 规范的显著性标注——星标统一(†///)
- 可复现——表格代码必须与回归代码对应
标准三线表格式规范
顶刊表格结构
┌─────────────────────────────────────────────┐
│ 表头(表标题 + 注释信息) │
├─────────────────────────────────────────────┤
│ 列标签(列1 列2 列3) │
│ ────────────────────────────────────────── │ ← 第一道线(顶部)
│ 变量行(因变量、自变量、控制变量) │
│ ────────────────────────────────────────── │ ← 第二道线(列分隔)
│ 统计量行(N、R²、F、聚类标准误) │
├─────────────────────────────────────────────┤
│ 表底注释(显著性标注、数据来源、稳健性说明) │
└─────────────────────────────────────────────┘
显著性星标标准
| 符号 | p值 | 说明 | |------|-----|------| | *** | p < 0.001 | 1% 显著性 | | ** | p < 0.01 | 5% 显著性 | | * | p < 0.05 | 10% 显著性 | | † | p < 0.10 | 15% 显著性(部分期刊)|
⚠️ 注意:不同期刊对星标的数量和阈值要求不同,投稿前需确认目标期刊格式。
常用表格 LaTeX 模板
模板 1:标准 OLS 回归表
\begin{table}[htbp]
\centering
\caption{基准回归结果}
\label{tab:baseline}
\begin{threeparttable}
\begin{tabular}{l*{3}{c}}
\toprule
& \multicolumn{3}{c}{因变量: log(GDP per capita)} \\
\cmidrule(l){2-4}
& (1) & (2) & (3) \\
\midrule
互联网普及率 & 0.023*** & 0.018** & 0.015* \\
& (0.007) & (0.008) & (0.008) \\
控制变量 & 否 & 是 & 是 \\
固定效应 & 否 & 否 & 年份+国家\\
\midrule
观测值 & 1,240 & 1,240 & 1,240 \\
R² & 0.041 & 0.315 & 0.682 \\
\bottomrule
\end{tabular}
\begin{tablenotes}
\item \textit{注:} ***, **, * 分别表示1\%, 5\%, 10\%的显著性水平。括号内为聚类标准误(聚类在国家层面)。控制变量包括:教育年限、人口增长率、贸易开放度。
\end{tablenotes}
\end{threeparttable}
\end{table}
模板 2:面板数据固定效应表
\begin{table}[htbp]
\centering
\caption{固定效应模型估计结果}
\label{tab:fe}
\begin{threeparttable}
\begin{tabular}{l*{4}{c}}
\toprule
& \multicolumn{2}{c}{OLS} & \multicolumn{2}{c}{固定效应} \\
\cmidrule(l){2-3} \cmidrule(l){4-5}
& (1) & (2) & (3) & (4) \\
\midrule
技术扩散指数 & 0.035*** & 0.028** & 0.021* & 0.018* \\
& (0.009) & (0.010) & (0.011) & (0.010) \\
\midrule
国家固定效应 & \checkmark & \checkmark & \checkmark & \checkmark \\
年份固定效应 & & \checkmark & & \checkmark \\
\midrule
观测值 & 1,240 & 1,240 & 1,240 & 1,240 \\
R² & 0.31 & 0.45 & 0.72 & 0.78 \\
\bottomrule
\end{tabular}
\begin{tablenotes}
\item \textit{注:} 同上。固定效应模型使用双向聚类标准误(国家+年份)。
\end{tablenotes}
\end{threeparttable}
\end{table}
模板 3:工具变量法表
\begin{table}[htbp]
\centering
\caption{工具变量估计结果}
\label{tab:iv}
\begin{threeparttable}
\begin{tabular}{l*{3}{c}}
\toprule
& OLS & \multicolumn{2}{c}{2SLS} \\
\cmidrule(l){2-2} \cmidrule(l){3-4}
& (1) & (2) & (3) \\
\midrule
技术扩散指数 & 0.023*** & 0.041*** & 0.038*** \\
& (0.007) & (0.013) & (0.012) \\
\midrule
KP F统计量 & & 24.6 & 28.3 \\
弱工具变量检验 & & & \\
\midrule
观测值 & 1,240 & 1,240 & 1,240 \\
\bottomrule
\end{tabular}
\begin{tablenotes}
\item \textit{注:} 列(2)-(3)使用技术扩散的滞后值作为工具变量。KP F统计量>10通过弱工具变量检验。
\end{tablenotes}
\end{threeparttable}
\end{table}
从 Stata/Python/R 到 LaTeX 的转换工具
Stata → LaTeX
// 安装 estout 套件
ssc install estout, replace
// 保存回归结果
eststo clear
eststo: reg ln_gdp internet i.year, vce(cluster country)
eststo: reg ln_gdp internet cov1 cov2 i.year, vce(cluster country)
// 导出 LaTeX
esttab using "tables/table1.tex", replace ///
title("基准回归结果") ///
label ///
booktabs ///
nonumbers ///
mtitles("OLS" "OLS") ///
star(* 0.05 ** 0.01 *** 0.001) ///
se ///
r2 ///
addn("控制变量包括教育年限、人口增长率、贸易开放度。")
Python (statsmodels) → LaTeX
import pandas as pd
from scipy.stats import ttest_ind
# 使用 statsmodels 输出的 LaTeX 转换
from statsmodels.iolib.summary import summary_table
# 回归后
result = model.fit()
print(result.summary_latex())
三线表排版规范(顶刊要求)
| 要求 | 说明 |
|------|------|
| Threeparttable | 使用 \begin{threeparttable} 环境 |
| booktabs | 使用 \toprule, \midrule, \bottomrule |
| 字体 | 通常10pt,表的注释可9pt |
| 列宽 | 使用 p{3cm} 控制列宽,或 tabularx 自动调整 |
| 数字对齐 | 数字右对齐,变量名列左对齐 |
| 缺失值 | 表格中用空白表示缺失,不写"NA" |
输出规范
## 表格输出规范
**输出路径**:tables/table{N}.tex
**主子表规范**:
- 主表(Main):表格1-3,放入正文
- 附录表(Appendix):表格A1-A10,放入Online Appendix
**文件名规范**:
tables/table1_baseline.tex # 基准回归 tables/table2_heterogeneity.tex # 异质性分析 tables/tableA1_robustness_iv.tex # 附录:IV稳健性
**LaTeX 代码规范**:
- 表格必须可编译(无缺失 `}` 或 `{`)
- 所有特殊字符(%, &, #)需转义
调用接口
在 Claude Code 对话窗口输入:
/latex-table
或完整 Prompt:
按LaTeX表格Skill生成符合AER顶刊格式的三线表回归结果,包括:基准回归表(表1)、固定效应表(表2)、工具变量表(表3)。使用booktabs环境,包含标准误聚类标注、显著性星标、固定效应标注。
与其他 Skill 的配合
did-reviewer→ DID 回归结果使用事件研究表格式R-optimizer→ R 输出表格时的优化codebook-pass→ 清洗后数据直接用于表格生成
重要声明
- 表格必须可复现——LaTeX 表格代码对应的回归必须可通过 Makefile 重新运行
- 投稿前必须按目标期刊格式调整星标阈值和表格大小
- 主子表分离——主表放核心结果,稳健性和异质性放入附录
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From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.
