Skill UI

GeoMaster is a comprehensive geospatial science skill that guides remote sensing, GIS, spatial analysis, and machine learning workflows for Earth observation and planetary data projects, covering satellite imagery, vector/raster math, point clouds, terrain, hydrology, and cloud-native data stacks.

A powerful skill covering geospatial science, including GIS, remote sensing, spatial statistics, and machine learning for Earth observation. It supports processing of various data types (raster, vector, point cloud) from sources like Sentinel and Landsat, and integrates modern cloud-native workflows (STAC, COG). Ideal for environmental monitoring, urban planning, and advanced spatial modeling tasks.

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 detailed reporting norms for reducing and analyzing complex Earth and Planetary Science Letters (EPSL) data, specifically focusing on isotope geochemistry and geochronology. It mandates full uncertainty budgeting, proper statistical interpretation (e.g., MSWD, weighted means), and thorough model diagnostics to ensure results are scientifically defensible and reproducible.

This guide provides rigorous standards for developing figures and tables in Earth and Planetary Science Letters (EPSL). It emphasizes making complex scientific arguments legible to a cross-disciplinary audience by mandating visible uncertainty (error ellipses, error bars), providing spatial context, and adhering to strict sub-field conventions (e.g., MSWD, depth scales). It teaches how to structure exhibits so that figures carry the argument, while detailed data resides in the supplementary material.

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 for planning rigorous scientific studies in Earth and Planetary Sciences, covering sampling, analytical campaigns, experimental runs, and modeling. It ensures that research designs are robust, addressing critical elements like sample context, traceability to reference materials, replication levels, and falsifiability before data collection begins. Essential for high-impact scientific publishing.

This skill helps assess whether a manuscript in solid-earth, ocean, atmospheric, or planetary sciences meets the high conceptual and systemic standards required for top-tier geoscience journals like Nature Geoscience. It guides authors to re-frame local findings into global, Earth-system processes, focusing on cross-disciplinary coupling, mechanistic advances, and robust data documentation. It is a conceptual fit tool, not a submission guide.

A comprehensive guide for authors designing figures and tables for Nature Geoscience manuscripts. It outlines strict rules for adhering to a limited figure budget (4-6 display items), ensuring the lead figure immediately conveys the core Earth-system advance and its uncertainty, and maintaining high standards of cartography and data visualization for non-specialist readership.