Toolbelt Geo

Execute GPU-accelerated geospatial analytics end-to-end using Toolbelt MCP tools. Work through each phase in order. Extract all required inputs from task parameters or invocation context — do not prompt for user input. Progress through phases without confirmation. On unrecoverable error, emit a structured failure and halt.

When Not To Use

• For tabular data without lat/lon coordinates — use toolbelt-analyze instead.
• For unstructured text or documents — use toolbelt-entities instead.

Invocation Parameters

Extract these from the args string or conversation context before starting:

Default Sample Data

If no csv_content is provided, use this Tampa Bay area sensor dataset:

id,name,lat,lon
1,Sensor A,27.9506,-82.4572
2,Sensor B,27.9659,-82.4398
3,Sensor C,27.9881,-82.5014
4,Sensor D,27.9344,-82.5181
5,Sensor E,28.0080,-82.4271
6,Sensor F,27.9196,-82.3943
7,Sensor G,27.8772,-82.5236
8,Sensor H,28.0346,-82.4850
9,Sensor I,27.9712,-82.5489
10,Sensor J,27.9050,-82.4127

Default zone_wkt (downtown Tampa bounding polygon):

POLYGON((-82.4650 27.9400, -82.4350 27.9400, -82.4350 27.9700, -82.4650 27.9700, -82.4650 27.9400))

Phase 0: Verify Connection

Call toolbelt_list_namespaces (no arguments) immediately.

• If it succeeds: proceed to Phase 1 using the returned namespaces.
• If it fails: emit structured failure and halt.

FAILURE: Toolbelt MCP connection is not established.
The MCP server must be connected before invoking this skill.
See: https://toolbelt.ai/docs/mcp for setup instructions.

Phase 1: Resolve Namespace

Use the namespaces returned from Phase 0.

Resolution order:

1. If namespace_id was provided as a parameter, use it directly.
2. If only one namespace exists, use it.
3. If multiple exist and no namespace_id was specified, emit structured failure and halt.

FAILURE: Multiple namespaces found and none specified.
Available: [<list namespace display names and IDs>]
Re-invoke with namespace_id=<uuid>.

Store the resolved namespace_id — pass it to every subsequent tool call.

Phase 2: Upload Sensor Data

Upload the CSV as a document using toolbelt_save:

{
  "asset_type": "document",
  "namespace_id": "<namespace_id>",
  "name": "<asset_name or 'sensor-locations'>",
  "file_name": "sensor-locations.csv",
  "content": "<csv_content or default sample data above>",
  "content_encoding": "text",
  "data_format": "csv"
}

Poll for ingestion

Call toolbelt_jobs with { "namespace_id": "<namespace_id>" } every 10 seconds.

Wait for the ingest job to reach completed.

Typical duration: 15–60 seconds. Maximum wait: 3 minutes.

If the job reaches failed or the timeout elapses, emit structured failure and halt:

FAILURE: Sensor data ingestion did not complete.
Job status: <last observed status>

After completion, call toolbelt_context to retrieve the table name for the uploaded asset. Store it as sensor_table for use in Phase 3.

Phase 3: Run Geospatial Queries

Run all three queries using toolbelt_sql. Pass namespace_id and query for each call. Collect results.

Note: ST_DISTANCE, ST_CONTAINS, and ST_MAKELINE are Kinetica-native geospatial functions available through Toolbelt's GPU-accelerated query engine. They are not standard SQL and will not work against other databases.

Query 1 — Pairwise Distance

ST_DISTANCE(lat1, lon1, lat2, lon2) → meters between two WGS-84 points.

SELECT
  a.name AS sensor_a,
  b.name AS sensor_b,
  ROUND(ST_DISTANCE(a.lat, a.lon, b.lat, b.lon)) AS distance_m
FROM <sensor_table> a
JOIN <sensor_table> b ON a.id < b.id
ORDER BY distance_m ASC
LIMIT 10

Record: distance_query_rows (number of rows returned), closest_pair (sensor_a and sensor_b from the first row), min_distance_m.

Query 2 — Point-in-Polygon

ST_CONTAINS(wkt_polygon, lat, lon) → 1 if point is inside the polygon.

SELECT
  id,
  name,
  lat,
  lon,
  ST_CONTAINS('<zone_wkt>', lat, lon) AS in_zone
FROM <sensor_table>
WHERE ST_CONTAINS('<zone_wkt>', lat, lon) = 1

Substitute <zone_wkt> with the provided or default WKT string.

Record: in_zone_count (number of sensors inside the polygon), in_zone_sensors (list of names).

Query 3 — Track Line

ST_MAKELINE(lat, lon ORDER BY id) → linestring connecting all points in sequence.

SELECT
  ST_ASTEXT(ST_MAKELINE(lat, lon ORDER BY id ASC)) AS track_wkt,
  COUNT(*) AS point_count
FROM <sensor_table>

Record: track_point_count, track_wkt_excerpt (first 120 chars of the WKT).

Phase 4: Structured Output

After all queries complete, emit a single structured result:

RESULT:
  namespace_id: <uuid>
  sensor_table: <table name>
  phases_run: [0, 1, 2, 3]
  row_count: <total rows in sensor table>

  distance_query:
    rows_returned: <distance_query_rows>
    closest_pair: "<sensor_a> → <sensor_b>"
    min_distance_m: <min_distance_m>

  point_in_polygon:
    zone_wkt: "<zone_wkt used>"
    in_zone_count: <count>
    in_zone_sensors: [<names>]

  track:
    point_count: <track_point_count>
    track_wkt_excerpt: "<first 120 chars>"

If any query fails, include query_error: "<error>" under that query's section and continue with remaining queries. Only halt on Phase 0–2 failures.

Tool Reference