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$ agentstack add skill-cxcscmu-skilllearnbench-plate-tectonics-geospatial ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
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- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
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Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
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Plate Tectonics Geospatial Analysis
Overview
The PB2002 (Plate Boundaries 2002) dataset provides comprehensive data on tectonic plate boundaries and plate definitions. This skill covers loading, processing, and spatial analysis of plate data.
PB2002 Dataset Structure
Boundary Data (PB2002_boundaries.json)
{
"type": "FeatureCollection",
"features": [
{
"type": "Feature",
"geometry": {
"type": "LineString",
"coordinates": [[lon1, lat1], [lon2, lat2], ...]
},
"properties": {
"PLATE1": "Pacific",
"PLATE2": "North American",
"TYPE": "subduction zone", // or "transform", "spreading", etc.
"STEPOVER": ""
}
}
]
}
Plate Data (PB2002_plates.json)
{
"type": "FeatureCollection",
"features": [
{
"type": "Feature",
"geometry": {
"type": "MultiPolygon", // or Polygon
"coordinates": [...]
},
"properties": {
"PlateName": "Pacific",
"PlateID": 101
}
}
]
}
Loading and Processing
Load Plate Boundaries
import geopandas as gpd
import json
with open('/root/PB2002_boundaries.json', 'r') as f:
boundaries_geojson = json.load(f)
boundaries_gdf = gpd.GeoDataFrame.from_features(
boundaries_geojson['features'],
crs='EPSG:4326'
)
# Filter for specific plate boundary
pacific_boundaries = boundaries_gdf[
(boundaries_gdf['PLATE1'] == 'Pacific') |
(boundaries_gdf['PLATE2'] == 'Pacific')
]
Load Plate Polygons
with open('/root/PB2002_plates.json', 'r') as f:
plates_geojson = json.load(f)
plates_gdf = gpd.GeoDataFrame.from_features(
plates_geojson['features'],
crs='EPSG:4326'
)
# Get Pacific plate polygon
pacific_plate = plates_gdf[plates_gdf['PlateName'] == 'Pacific']
Spatial Operations
Identify Points Within Plate
# Use spatial join to find earthquakes within Pacific plate
earthquakes_in_pacific = gpd.sjoin(
earthquakes_gdf,
pacific_plate,
how='inner',
predicate='within'
)
Calculate Distance to Boundary
# For each earthquake, calculate minimum distance to boundary
def min_distance_to_boundary(point, boundary_lines_gdf):
"""Calculate minimum distance from point to any boundary line"""
min_dist = float('inf')
for idx, boundary in boundary_lines_gdf.iterrows():
dist = point.distance(boundary['geometry'])
if dist < min_dist:
min_dist = dist
return min_dist
# Apply to all earthquakes in the plate
# First, project to projected CRS for accurate distance in km
earthquakes_projected = earthquakes_in_pacific.to_crs('EPSG:3857')
boundaries_projected = pacific_boundaries.to_crs('EPSG:3857')
earthquakes_projected['distance_to_boundary'] = earthquakes_projected.geometry.apply(
lambda point: min_distance_to_boundary(point, boundaries_projected)
)
# Convert from meters to kilometers
earthquakes_projected['distance_km'] = earthquakes_projected['distance_to_boundary'] / 1000
Find Maximum Distance
# Find earthquake furthest from boundary
furthest_idx = earthquakes_projected['distance_km'].idxmax()
furthest_earthquake = earthquakes_projected.loc[furthest_idx]
Important Considerations
Polygon Validation
# Ensure polygons are valid before spatial operations
if not plates_gdf.geometry.is_valid.all():
plates_gdf['geometry'] = plates_gdf.geometry.buffer(0)
if not boundaries_gdf.geometry.is_valid.all():
boundaries_gdf['geometry'] = boundaries_gdf.geometry.buffer(0)
Handling MultiPolygons
# If a plate is represented as MultiPolygon, create a union
pacific_plate_union = pacific_plate.unary_union
Projection for Accurate Distances
# Use Web Mercator (EPSG:3857) for global distances in meters
# Then convert to kilometers
# For regional analysis, consider UTM zones
# EPSG:32633 = UTM Zone 33N
# EPSG:32733 = UTM Zone 33S
Common Pitfalls
- Not projecting before distance calculations - Distances in geographic CRS are meaningless
- Invalid geometries - Use
.buffer(0)to fix self-intersecting polygons - Antimeridian issues - Points near ±180° longitude may have wrapping issues
- MultiPolygon confusion - Remember that a plate may consist of multiple disconnected polygons
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: cxcscmu
- Source: cxcscmu/SkillLearnBench
- License: MIT
- Homepage: https://cxcscmu.github.io/SkillLearnBench
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.