Use for structured/tabular data prediction: churn, fraud, credit/risk scoring, price/demand regression, conversion, recommendation features, any CSV/database ML. Picks gradient boosting vs deep tabular, robust feature engineering, correct CV, calibration, and imbalance handling. Triggers on 'predict churn/fraud/price/risk', 'classify this CSV/table', 'tabular', 'XGBoost/LightGBM', 'feature engineering'.
How to install domain-tabular?
mxslr/mlcraft/domain-tabular
$npx -y skills add mxslr/mlcraft --skill domain-tabularInstalls into the current project.
›Prefer a prompt? Paste this to your agent
Run `npx skills use "https://github.com/mxslr/mlcraft" --skill "mxslr/mlcraft/domain-tabular"` and follow the generated skill instructions now. Read its complete output, redirecting it to a temporary file first if necessary. Resolve relative paths from the supporting-files directory it provides.
Use the skills in "https://github.com/mxslr/mlcraft" that are relevant to the current task. Run `npx skills add "https://github.com/mxslr/mlcraft"` and select the relevant skills, then follow their instructions.
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