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This skill equips Claude with specialized templates and checklists designed to bring rigor to technical tasks in software engineering and data science. By providing systematic scaffolds for TDD, exploratory data analysis (EDA), and machine learning pipelines, it ensures that developers and data scientists follow best practices—such as writing tests before code or validating data quality—before proceeding to execution. This systematic approach helps prevent common pitfalls, ensures comprehensive test coverage, and improves the reliability of statistical insights and predictive models.
