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Example prompts

The model decides when to call cluster_points based on what you ask. These prompts reliably trigger a tool call and get a useful explanation back.

Good prompts

Specific about the input shape

Here's a GeoJSON FeatureCollection of recent rhino sightings in Kruger. Use cluster_points with eps = 3000 and minPts = 4 to find sighting clusters, then summarise each cluster in plain English.

Asks for analysis on top of the tool output

Cluster these delivery drop-points and tell me which cluster is likely to need a second driver — that's the one with more than 20 stops within a 2 km radius.

Lets the model pick parameters

Cluster these GPS pings into camps. Pick reasonable DBSCAN parameters for "human-scale walking distance", run cluster_points, and explain your parameter choice.

Prompts that go sideways

Vague geometry

"Cluster this CSV." — the tool needs GeoJSON. Convert first, or ask the model to do the conversion.

Too-loose eps

"Cluster with eps = 100000." — at 100 km you'll get one giant cluster. Start small (1 km) and widen until the output stops merging.

Trying to cluster polygons

cluster_points only consumes Point features. Centroid your polygons first if you must — or open an issue asking for cluster_polygons.

Tips for getting the most out of the model

  • Tell the model why you're clustering. "Find delivery routes" leads to different eps/minPts choices than "find rare-species hotspots".
  • Ask it to render the output. "Now produce a Leaflet snippet that shows these polygons on top of an OSM basemap."
  • Stack tools. Once we add convex_hull or buffer you can chain them: cluster, then hull, then buffer.

Want to ship a prompt with your team?

Drop it in the /users/prompts/ folder of our examples repo (PRs welcome) so others can reuse it.