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The Notebook Debugger skill provides a robust framework for diagnosing runtime errors in executed notebooks across various formats including marimo, jupytext, and standard Jupyter. It implements a strict 'Iron Law' verification process that prevents false success claims by mandating execution-to-ipynb, cell-level output inspection, and automated traceback detection using tools like jq. This skill is essential for data scientists and developers who need to ensure their notebook-based workflows are fully functional, sequential, and error-free before final delivery.
