Skills for Real Engineers. Straight from my .agents directory.
39 skills
Full-empirical-analysis-skill
Agent skill from
Classical end-to-end empirical analysis workflow in the traditional Python econometric stack — pandas + numpy + scipy + statsmodels + linearmodels + pyfixest + rdrobust + econml + causalml + matplotlib/seaborn. **Defaults to economics empirical-paper style** (AER / QJE / AEJ) — every run produces a publication-ready output set with a multi-column regression table (M1→M6 progressive controls/FE) as the centerpiece, plus Table 1 (descriptives), mechanism / heterogeneity / robustness tables, and event-study + coefficient + trend figures. Covers the full 8-step pipeline an applied economist or quantitative social scientist runs on every paper — (1) data cleaning, (2) variable construction & transformation, (3) descriptive statistics & Table 1, (4) statistical diagnostic tests, (5) baseline empirical modeling, (6) robustness battery, (7) further analysis (mechanism, heterogeneity, mediation, moderation), (8) publication-ready tables & figures. **Also covers two parallel domain modes that sh
How to install Full-empirical-analysis-skill
install Full-empirical-analysis-skill
# install the Auto-Empirical-Research-Skills pack with the skills CLI
npx skills add brycewang-stanford/Auto-Empirical-Research-Skills# or add only this skill to Claude Code: copy the folder
skills/00.1-Full-empirical-analysis-skill_Python/
# into
~/.claude/skills/00.1-Full-empirical-analysis-skill_Python/ (all projects)
.claude/skills/00.1-Full-empirical-analysis-skill_Python/ (one project)
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