Python bindings for H3, a hierarchical hexagonal geospatial indexing system
84
Pending
Does it follow best practices?
Impact
84%
0.95xAverage score across 10 eval scenarios
Pending
The risk profile of this skill
{
"context": "Evaluates how well the solution relies on the h3 Python bindings to convert lat/lng coordinates into H3 cell identifiers, recover cell centers, and extract boundary polygons. Scoring emphasizes correct use of the library's conversion and boundary helpers rather than manual geometry or formatting.",
"type": "weighted_checklist",
"checklist": [
{
"name": "Known encoding",
"description": "Uses `h3.latlng_to_cell` with resolution 9 to map (37.7749, -122.4194) to `89283082e6bffff` instead of constructing the identifier manually.",
"max_score": 30
},
{
"name": "Resolution handling",
"description": "Varies the resolution argument in `latlng_to_cell` (e.g., res 7 vs 9) and asserts distinct valid outputs, demonstrating reliance on the package's resolution-aware encoding.",
"max_score": 20
},
{
"name": "Center round-trip",
"description": "Uses `h3.cell_to_latlng` to get the center of `89283082e6bffff` and re-encodes it with `latlng_to_cell` to confirm the identifier is unchanged.",
"max_score": 25
},
{
"name": "Boundary retrieval",
"description": "Retrieves vertices via `h3.cell_to_boundary`, checks for six counterclockwise points containing the source coordinate, and avoids hand-built polygons.",
"max_score": 25
}
]
}docs
evals
scenario-1
scenario-2
scenario-3
scenario-4
scenario-5
scenario-6
scenario-7
scenario-8
scenario-9
scenario-10