Back to prompt library
Build a Wildfire Exposure Boundary Metadata Auditor — implementation
Linked challenge: Build a Wildfire Exposure Boundary Metadata Auditor
Prompt source
implementation61 lines11 sectionsNo variables1 code block
## Build
Evaluate commercial real estate exposure locations by compiling intersecting STAC metadata records. Identify available high-resolution multispectral imagery links for defensive vegetation buffer audits using an LLM-assisted metadata retrieval workflow.
## User
Commercial Property Risk Surveyor
## Workflow
1. Load commercial facility polygon geometries and perimeter buffer specifications.
2. Discover recent high-resolution STAC Items covering the extended perimeter zones.
3. Extract valid spatial asset links representing optical imagery bands from the STAC records.
4. Generate a structured metadata retrieval report for downstream vegetation analysis by human reviewers.
## Interface
Web inspection terminal presenting property boundary overlays and retrieved STAC metadata links.
## Data
Query open STAC Catalog collections for Sentinel-2 or NAIP metadata, or utilize bundled local STAC GeoJSON files.
Starter examples below are synthetic. They are not downloaded records.
## Source
[STAC specification](https://raw.githubusercontent.com/radiantearth/stac-spec/master/README.md)
Traverses STAC Collections and Item metadata to parse asset bounding boxes and multispectral imagery links.
## Tools
anthropic-claude, pystac, shapely.
Claude parses complex STAC JSON schemas to extract valid optical imagery links and formats structured retrieval summaries.
Hosted Claude API for contextual JSON parsing and metadata audit reporting.
## Deliverables
Submit runnable source, pinned dependencies, setup commands, a working interface, example outputs, and a recorded end-to-end demo. Include tests and an action log.
## Acceptance
- Queries STAC catalogs to find items intersecting property polygons.
- Successfully filters items containing optical imagery asset links.
- Emits human-readable metadata retrieval summaries for property inspection teams.
## Starter Examples
```json
[
{
"input": {
"facility_id": "FAC-WUI-01",
"buffer_clearance_m": 12.5,
"stac_collection": "naip"
},
"expected_output": {
"facility_id": "FAC-WUI-01",
"imagery_links_found": 2,
"metadata_status": "READY_FOR_REVIEW",
"record_type": "simplified synthetic app record"
}
},
{
"input": {
"facility_id": "FAC-WUI-02",
"buffer_clearance_m": 45,
"stac_collection": "naip"
},
"expected_output": {
"facility_id": "FAC-WUI-02",
"imagery_links_found": 0,
"metadata_status": "NO_IMAGERY_FOUND",
"record_type": "simplified synthetic app record"
}
}
]
```
## Safety
Provides preliminary metadata screening; does not execute physical site audits or replace qualified municipal fire marshals.
Use mock external writes. Require human review before any real deployment.