physical-science
Handle remote sensing/GIS, astronomy FITS, quantum or physical simulation, and engineering optimization beyond writing-centric workflows.
Before you start
Choose your system and agent, then run the command in your terminal. After installation, send the prompts below to your agent.
curl -sSL https://paperskills.com/scripts/paperskills-install.sh | bash -s -- \
--tool codex \
--skills sa.geomaster,sa.geopandas,sa.astropy,sa.fluidsim,sa.pymoo \
--registry https://paperskills.com/api/registryStep 1 · sa.geomaster
Task for your agent
Use geomaster/geopandas to read spatial data, check CRS, clip the study area, generate a quality report, and create the first exploratory map.Expected outputs
Step 2 · sa.astropy
Task for your agent
If the data is FITS or astronomy observations, use astropy for units, coordinates, WCS, tables, and time systems, then output a reproducible notebook outline.Expected outputs
Step 3 · sa.pymoo
Task for your agent
If the task involves engineering design or parameter optimization, use pymoo to define objectives, constraints, Pareto fronts, and an interpretation template.Expected outputs
Comprehensive geospatial science skill covering remote sensing, GIS, spatial analysis, machine learning for earth observation, and 30+ scientific domains. Supports satellite imagery processing (Sentinel, Landsat, MODIS, SAR, hyperspectral), vector and raster data operations, spatial statistics, point cloud processing, network analysis, cloud-native workflows (STAC, COG, Planetary Computer), and 8 programming languages (Python, R, Julia, JavaScript, C++, Java, Go, Rust) with 500+ code examples. Use for remote sensing workflows, GIS analysis, spatial ML, Earth observation data processing, terrain analysis, hydrological modeling, marine spatial analysis, atmospheric science, and any geospatial computation task.
View skillPython library for working with geospatial vector data including shapefiles, GeoJSON, and GeoPackage files. Use when working with geographic data for spatial analysis, geometric operations, coordinate transformations, spatial joins, overlay operations, choropleth mapping, or any task involving reading/writing/analyzing vector geographic data. Supports PostGIS databases, interactive maps, and integration with matplotlib/folium/cartopy. Use for tasks like buffer analysis, spatial joins between datasets, dissolving boundaries, clipping data, calculating areas/distances, reprojecting coordinate systems, creating maps, or converting between spatial file formats.
View skillCore Python library for astronomy and astrophysics workflows that need Astropy APIs, including units/quantities, coordinates, FITS I/O, tables, time systems, WCS, and cosmology. Use when implementing or debugging astronomical data analysis code with Astropy.
View skillFramework for computational fluid dynamics simulations using Python. Use when running fluid dynamics simulations including Navier-Stokes equations (2D/3D), shallow water equations, stratified flows, or when analyzing turbulence, vortex dynamics, or geophysical flows. Provides pseudospectral methods with FFT, HPC support, and comprehensive output analysis.
View skillMulti-objective optimization framework. NSGA-II, NSGA-III, MOEA/D, Pareto fronts, constraint handling, benchmarks (ZDT, DTLZ), for engineering design and optimization problems.
View skill