Skill UI

A meta-skill designed for planning educational and creative ventures for children (e.g., science fair entries, DIY kits). It assesses project feasibility based on the child's age, generates age-appropriate step-by-step plans, suggests materials with budget alternatives, and provides critical safety notes and parent-facing learning objectives for effective supervision.

A comprehensive guide for structuring and presenting rigorous, high-impact experimental chapters suitable for top-tier computer science journals. Learn to design experiments driven by Research Questions (RQ), select fair baselines, conduct statistical significance testing, and implement ablation/sensitivity analyses. Ensures evidence is reproducible and perfectly aligns with abstract claims.

This skill guides authors on submitting original, high-quality, and reusable Earth System datasets (observations, reanalysis, model outputs) as primary publications. It assesses whether the work fits the criteria of a 'data paper,' requiring open deposition in a FAIR repository with a persistent DOI, detailed provenance documentation, and rigorous quality control. It serves as a venue-selection and manuscript re-framing tool.

This guide provides best practices for ensuring scientific reproducibility in Earth and Planetary Science Letters (EPSL) manuscripts. It details how to structure supplementary materials, data tables, and analytical code to comply with modern research data policies (FAIR principles). It directs authors on depositing data into recognized community repositories (e.g., PANGAEA, Zenodo, EarthChem), ensuring that the paper's findings can be independently validated by any reader.

A comprehensive guide to designing rigorous, reproducible, and fair experimental protocols for computational science research, particularly for top-tier academic journals. It covers critical elements such as selecting standard benchmark instances, establishing strong baselines, ensuring fair parameter tuning, reporting hardware constraints, and performing robust statistical validation, helping researchers avoid common pitfalls and maximize the scientific validity of their claims.

This comprehensive guide is designed for authors submitting full-length manuscripts to Journal of Geophysical Research: Atmospheres (JGR-Atmospheres). It helps assess the fit, required depth, and methodological rigor of atmospheric science studies. The skill covers essential topics like aerosol interaction, cloud physics, atmospheric dynamics, data requirements (FAIR), and the specific structural expectations (e.g., Plain Language Summary) needed to meet the journal's high standard for quantitative, definitive scientific advances.

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 provides comprehensive guidance for submitting research to npj Computational Materials. It defines the journal's scope, requiring rigorous computational methods (DFT, MD, ML, high-throughput screening) that yield generalizable materials insights or predictive capabilities. It educates authors on the required standards, including methodological rigor, reproducibility, and adherence to FAIR data principles, helping authors re-frame their work for a high-impact venue.

A comprehensive guide for authors submitting to high-impact scientific journals. It outlines the essential principles for structuring experiments and presenting evidence, emphasizing claims-evidence matching, fair benchmarking, differentiating result sources (simulation, hardware, theory), and ensuring statistical rigor. Covers best practices across computer science, control, communication, and microelectronics.