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skillboardThis skill covers causal machine learning methods in applied economics and quantitative social science. Use when implementing or choosing between modern ML-based causal estimators — including double machine learning, DML, partially linear models, interactive regression models, cross-fitting, Neyman orthogonality, debiased ML, causal forests, generalized random forest, GRF, honest causal trees, AIPW with machine learning, doubly robust with machine learning, DR-Learner, T-Learner, S-Learner, X-Learner, meta-learners, heterogeneous treatment effects, conditional average treatment effect, CATE, HTE, high-dimensional controls, LASSO controls, post-LASSO, post-double selection, Belloni-Chernozhukov-Hansen, Riesz representer, Chernozhukov, sample splitting, econml, DoubleML package, or any combination of machine learning and causal inference.
Causal Machine Learning Reference for semiparametric ML estimators: DML with cross fitting, generalized random forests, debiased regularization, and nuisance function approximation. Covers Neyman orthogonal moment conditions, sample splitting, plug in bias correction, and heterogeneous treatment effects. When to Use This Skill Use when the user is: Estimating treatment effects with high dimensional controls (p large relative to n) Interested in heterogeneous treatment effects (CATE) as a…
Full body not shown for this license – view the source on GitHub →Copy a source-pinned command for your client. You run it yourself.
Destination: .claude/skills/causal-ml · pinned to the source commit
# Run from your project root
git clone https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills.git .skillboard-tmp
git -C .skillboard-tmp checkout 692e9fa3fea40bbdf614584d461851f8fb968ac2
mkdir -p ".claude/skills"
cp -r ".skillboard-tmp/skills/11-James-Traina-compound-science/skills/causal-ml" ".claude/skills/"
rm -rf .skillboard-tmpReview the source before running. This copies files into your project; it is not a one-click install and does not verify runtime safety.
sudo apt update && sudo apt install -y gitnpm install -g @anthropic-ai/claude-code# Run from your project root
git clone https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills.git .skillboard-tmp
git -C .skillboard-tmp checkout 692e9fa3fea40bbdf614584d461851f8fb968ac2
mkdir -p ".claude/skills"
cp -r ".skillboard-tmp/skills/11-James-Traina-compound-science/skills/causal-ml" ".claude/skills/"
rm -rf .skillboard-tmpDestination: .claude/skills/causal-ml
Scanner static-checks@0.1.0 · commit 692e9fa3fea4. Static checks cannot prove runtime safety – review the source and the exact diff before installing. How checks work.
No static rules matched. This is not a safety guarantee.