Generate publication-ready regression tables as LaTeX fragments and CSVs.
npx skills add https://github.com/zhouziyue233/great-econometrics --skill table-zhouziyue233
Please help me install this Agent Skill. Skill: table Source: https://github.com/zhouziyue233/great-econometrics/tree/main/skills/table Command: npx skills add https://github.com/zhouziyue233/great-econometrics --skill table-zhouziyue233
This skill generates publication-quality regression tables, descriptive statistics tables, and multi-panel layouts for economics journals. It consolidates outputs from major table tools across Python, R, and Stata to streamline paper-ready results.
Call this skill after you have regression outputs to format them into publication-ready tables.
High-intent search queries and answers about installing and using this skill.
To generate publication-ready regression tables, you provide your model outputs along with the table type, strategy, and software context. The system processes these inputs to produce a body LaTeX fragment and a CSV file containing the raw numbers.
Yes, you can create descriptive statistics and balance tables for economics journals. The system supports formatting main results, descriptive stats, and multi-panel layouts suitable for top journal publication standards.
Yes, this table generation approach works across Python, R, and Stata workflows. It consolidates outputs from major table tools like pyfixest, modelsummary, fixest, stargazer, and esttab to streamline paper-ready results.
The best way to export LaTeX regression tables with verifiable raw numbers is to use a tool that outputs two files per table: a body-only LaTeX fragment for insertion and an accompanying CSV for verification and reproducibility.
To format your regression results into a multi-panel layout, you need to provide your model outputs and specify the table type, strategy, and software context. This ensures the generated LaTeX and CSV files meet your formatting requirements.
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