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Found 25 Skills
Find nearest features efficiently using PostGIS KNN (<->) and distance ordering (with SRID/unit guidance).
Spaycial integration. Manage data, records, and automate workflows. Use when the user wants to interact with Spaycial data.
Builds geocoding workflows in CARTO that convert street addresses or place names into geographic coordinates. Triggers when the user mentions geocoding, address to coordinates, address resolution, geolocate addresses, "add geometry from addresses", lat/lon from address, place name to point, address matching, forward geocoding, converting addresses to points, or has tabular data with address columns but no spatial geometry column and needs to create one.
Convert JSON rows with latitude/longitude fields into a GeoJSON FeatureCollection using raw PostGIS SQL.
Spatial data processing for geological modelling with GemPy. Use when Claude needs to: (1) Prepare spatial data for GemPy models, (2) Extract interface points from geological maps, (3) Process orientations/dip measurements, (4) Sample DEMs along profiles or cross-sections, (5) Convert between GIS formats and GemPy inputs, (6) Clip/transform vector/raster data for modeling, (7) Create model extents from geospatial bounds.
Cross-application GIS skill — CRS reference, data formats, Blender/QGIS integration via digitalmodel.gis
Guides the user through spatial enrichment workflows — triggered by requests to enrich, add demographics, estimate population around locations, compute spatial features, sociodemographic analysis, "what's around" queries, buffer/isochrone + join patterns, or trade area enrichment.
Discover and subscribe to external spatial datasets via CARTO Data Observatory and partner catalogs.
GSLIB-inspired geostatistics library for variogram analysis, kriging, and simulation. Use when Claude needs to: (1) Calculate experimental variograms, (2) Fit variogram models, (3) Perform simple/ordinary kriging, (4) Run sequential Gaussian simulation (SGSIM), (5) Apply normal score transforms, (6) Decluster spatial data, (7) Generate multiple realizations for uncertainty.
Index points into a hexagonal grid
Use when "GeoPandas", "geospatial", "GIS", "shapefile", "GeoJSON", or asking about "spatial analysis", "coordinate transformation", "spatial join", "choropleth map", "buffer analysis", "geographic data", "map visualization"
Turn an address into a point, and a point into everything that contains it, instead of recalling coordinates that do not exist. Eleven services covering forward geocoding of a US street address to latitude and longitude, reverse geocoding a lat/lon back to a street address, the Census tract, block FIPS code and GEOID behind an address or a coordinate, up to ten addresses resolved in one request, every Census layer through a point at once — county, county subdivision, place, urban area, CBSA and CSA, congressional district and both state legislative chambers — USPS-style address standardization for deduplicating messy address lists, the nearest named street to a GPS fix, the nearest airports with IATA and ICAO codes, ground elevation from USGS 3DEP, and great-circle distance and bearing between two coordinates. Reach for it whenever an invented coordinate or an invented census tract is the way the task fails: both are strings of plausible digits that no reader can check by eye, and the address-to-tract mapping exists in no model's weights. Use it for asks like "geocode this address", "what census tract is this in", "which congressional district covers these coordinates", "standardize this address list", "what street is this GPS fix on", "nearest airport to this point", "how high is this point", "how far apart are these two coordinates". Geocoding is US-only and says so rather than guessing. Browsing and searching the catalog are free, and with no wallet configured a call prints its price and the exact request instead of paying; real calls cost $0.003 to $0.008, settled in USDC on Base.