Skill UI

This guide provides a comprehensive framework for building verifiable reproducibility evidence for academic manuscripts. It instructs authors on critical engineering disciplines, including freezing environment dependencies, controlling random seeds, versioning datasets and models, and creating anonymous, self-contained running materials that stand up to rigorous external peer review.

A comprehensive self-check tool for authors targeting Nature Water. It guides the framing, scope, methodological rigor, and structural requirements necessary for submitting high-impact research in water science, hydrology, and environmental engineering. Focuses on connecting technical findings to broad societal challenges and ensuring FAIR data compliance.

This skill guide teaches how to use a CLI tool to programmatically create, modify, and validate complex Excel (.xlsx) files. It covers everything from building robust financial models and dashboards to parsing raw data and ensuring the output adheres to professional standards, including zero formula errors and proper print layouts. Ideal for data engineering and business intelligence workflows.

This guide covers the mandatory Open Science appendix for high-level security research. It instructs authors on enumerating all artifacts (code, datasets, configurations), documenting data withholding decisions, and implementing engineering controls (like environment pinning and version tracking) to ensure that published results are independently and reliably reproducible.