Geosql: A Claude/Codex skill for geospatial data

It's not % it's number of evals. Here is how I did evaluation https://dekart.xyz/blog/how-to-evaluate-claude-skill-output-...

LOVE the fact that LiDAR is OpenData!

I am currently working on a website https://hillsha.de that makes it easy to download LiDAR las/laz files for almost every place in europe, the US and some other regions. I also made an iOS app for the same use-case, which can render the LiDAR data in 3D and 2D without PDAL and GDAL. It uses a vibe-coded library instead that combines both in native Swift. The iOS app is still in testing but works great.

Implementing France was a lot more comfortable than almost every other country, very well structured metadata and naming conventions. So thanks for that

(i work at the german mapping agency but this is a private project since i just love working with LiDAR hillshades)

Thanks for sharing, and thanks for making the video you shared. A couple thoughts. Is PostGIS king in this area? I've been liking duckDB as it does not require a server. Is there a good alternative to PostGIS in the duckDB world? Maybe just plain GeoParquet files read in through duckDB?

In the example in your video are any special GEOMETRY functions being used in the underlying SQL? Or, could your data just have been in plain postgres?

A similar product GeoSQL is Malloy which puts a semantic layer on top of your data for better LLM understanding. Malloyyo gives you an MCP server for precise and auditable interaction with your data.

This can be very useful for urban planning. you could have an agent investigate the optimal spot for a new datacenter, examine solar power installations, and so on.

20 year GIS dev here. Looks pretty useful for data exploration. I'd say one of the more compelling GeoAI things I've seen.

The problem is there's really a lot of data out there and it's a lot of work to move it around, e.g. between S3 buckets. There's also a ton of GIS SAAS vendors who are pure rent-seekers: I'm looking at a newer offering charging $23 per month for 10GB storage. This has more utility than their offering in my opinion.

The good thing here is that it could keep data provenance because it's SQL over known datasets.

I wonder if this would be useful in OSINT stuff.

I work with maps everyday. I'm cheap and my employer is cheap with me, but we've got to produce a lot of maps for compliance & business intelligence. The work is is mostly cleaning & standardization, with some user experience toward a particular audit purpose.

There are some much more lucrative niches, that have to do with chain-of-title, rights of way, resource rights, and so on, and I can imagine why anyone would pay to save, say, 20 hours a week.

Power interconnects for datacenter siting would be a hot example.

Map snapshot PNG. Apparently, LLM is quite competent when reading map images. It can say, “Oh, that's not all London coverage.” “ “Oh, this and this street is a problem (without having street data).”

Skills provide guidance; they augment and narrow the search space. Even intelligent humans benefit from guidance.

Exactly, this platform has fallen down so incredibly low. Every other post is worthless garbage about LLMs, without a single ounce of actual science being showcased, created, or even talked about. But a whole post about a markdown file is a new low imo. How does anyone who's actually competent at all in their domain think that this is worth sharing?

If you check into the docs, skill is the entry point for the map harness for Claude. You need to install the skill and run the Docker image.

That said, some of the skill frameworks like gstack created 10x productivity gain for me. IMO, worth sharing here.