geo-infer-place
Place-based analysis with H3 hexagonal indexing. Use when performing place identification, catchment area analysis, county/region geometry loading, or H3-based place-shedding and geographic boundary operations.
Best use case
geo-infer-place is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Place-based analysis with H3 hexagonal indexing. Use when performing place identification, catchment area analysis, county/region geometry loading, or H3-based place-shedding and geographic boundary operations.
Teams using geo-infer-place should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/GEO-INFER-PLACE/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How geo-infer-place Compares
| Feature / Agent | geo-infer-place | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Place-based analysis with H3 hexagonal indexing. Use when performing place identification, catchment area analysis, county/region geometry loading, or H3-based place-shedding and geographic boundary operations.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# GEO-INFER-PLACE
## Instructions
### Core Capabilities
- **Place identification**: Named place resolution and geocoding
- **Catchment analysis**: Service area and accessibility modeling
- **H3 place-shedding**: Hexagonal tessellation of administrative boundaries
- **Boundary operations**: County/region geometry loading and manipulation
- **Unified backend**: Multi-source geographic data integration
### Key Imports
```python
from geo_infer_place.core.unified_backend import UnifiedPlaceBackend
from geo_infer_place.core.catchment import CatchmentAnalyzer
from geo_infer_place.core.geocoding import PlaceGeocoder
```
## Examples
```python
from geo_infer_place.core.unified_backend import UnifiedPlaceBackend
backend = UnifiedPlaceBackend()
place = backend.resolve("Portland, OR")
print(f"Resolved: {place.name}, Center: ({place.lat}, {place.lng})")
boundary = backend.get_boundary(place.id)
print(f"Boundary: {boundary.area_km2:.1f} km²")
```
```python
from geo_infer_place.core.catchment import CatchmentAnalyzer
analyzer = CatchmentAnalyzer(mode="drive_time")
catchment = analyzer.compute(
facility_location=(45.5, -122.6),
max_time_minutes=15
)
print(f"15-min catchment: {catchment.area_km2:.1f} km²")
print(f"Population covered: {catchment.population:,}")
```
## Guidelines
- Uses H3 v4 API exclusively
- Fallback placeholder geometries used when county data is unavailable (graceful degradation)
- Test: `uv run python -m pytest GEO-INFER-PLACE/tests/ -v`
### Integrations
- **SPACE** → H3 tessellation of place boundaries
- **DATA** → Boundary geometry data sources
- **CIV** → Community place identification
- **HEALTH** → Health district boundary resolution
- **TRANSPORT** → Accessible catchment areas