Install
$ agentstack add skill-danielrosehill-claude-data-wrangler-plugin-geodata-formatter ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ 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.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
Geodata Formatter
Convert CSV / tabular geodata to GeoJSON.
When to invoke
- User has a flat file with location columns and needs GeoJSON for Leaflet / Mapbox / QGIS / ArcGIS / Kepler.gl / geopandas / PostGIS.
- User asks "convert to GeoJSON", "make this mappable", "export as geojson".
Supported inputs
- Lat/lon columns — pair of numeric columns (
lat/lng,latitude/longitude,y/x). Most common. - WKT / WKB geometry column — a string column containing
POINT(...),LINESTRING(...),POLYGON(...)etc. (or hex-encoded WKB). - H3 / S2 / geohash — spatial index strings that decode to polygons/cells.
- Address / place name columns — requires geocoding; ask user explicitly before using a third-party service and respect rate limits.
Output formats
- GeoJSON FeatureCollection (
.geojson) — single document, good for small/medium datasets. - GeoJSON Sequence / NDGeoJSON (
.geojsonlor.geojsons) — newline-delimited, good for streaming and >100k features. - Optional: TopoJSON via
topojson/pytopojsonfor compactness. - Optional: GeoParquet (recommended for big data; a different skill, but link).
Procedure
- Identify geometry source columns — lat/lon pair, WKT, geohash, H3, or address. Ask if ambiguous.
- Confirm CRS:
- Default: EPSG:4326 (WGS84) — required by the GeoJSON spec (RFC 7946).
- If the source is in a different CRS (e.g. British National Grid EPSG:27700, Web Mercator EPSG:3857, Israeli ITM EPSG:2039), reproject via
pyprojbefore writing GeoJSON.
- Validate coordinate sanity:
- Lat in [-90, 90], lon in [-180, 180].
- Flag rows outside these bounds — often indicates swapped lat/lon. Ask user.
- NaN / null geometries → emit as
{"geometry": null, ...}Features (valid per spec) or drop; ask user.
- Pick feature properties — which columns become
propertiesin each Feature. Default all non-geometry columns. Exclude PII-flagged columns by default. - Build Features:
- Point:
{"type":"Point","coordinates":[lon,lat]}— note the lon-first ordering (GeoJSON spec), not lat-first. - From WKT: parse with
shapely.wkt.loads→shapely.geometry.mapping(...). - From H3: decode to cell polygon via
h3.cells_to_geo([cell]). - From address: geocode via
geopywith a user-selected provider (Nominatim, Google, Mapbox, LocationIQ). Confirm ToS/rate limits; cache results; never batch against Nominatim above 1 req/sec.
- Write output:
- Small files:
json.dump({"type":"FeatureCollection","features":[...]}). - Large files: stream per-feature to
.geojsonlor chunk writes to avoid memory bloat. - Add a top-level
bboxfor the FeatureCollection if helpful.
- Validate — optional lint via
geojson/geojson-pydantic; report any invalid features. - Report — feature count, geometry-type breakdown, rows skipped/flagged, output path, CRS written (always EPSG:4326 for GeoJSON).
- Update the data dictionary — record geometry source columns, CRS, geocoding provider if used.
Dependencies
pip install pandas shapely pyproj
# optional
pip install geopandas fiona # richer read/write of geo formats
pip install h3 # H3 cells
pip install geopy # geocoding
pip install geojson-pydantic # validation
Edge cases
- Lat/lon swap — the most common bug. Detect when "lat" values exceed ±90 or "lon" names correspond to y-axis. Ask, don't silently swap.
- Antimeridian crossing — polygons crossing the 180° line need splitting for most renderers. Flag and offer to split via
shapely. - Very large polygons — simplify via
shapely.simplify(tolerance)if downstream tools choke; record the tolerance. - Mixed geometry types in one collection — valid GeoJSON but some tools reject. Offer to split per-type.
- Addresses — refuse to geocode at scale without explicit user consent and a chosen provider; geocoding is often billable and rate-limited.
Safety
Follow the backup policy in CONVENTIONS.md before any in-place rewrite. This skill by default writes a new .geojson or .geojsonl file alongside the source.
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: danielrosehill
- Source: danielrosehill/Claude-Data-Wrangler-plugin
- License: MIT
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.