mit einem Klick
gis-spatial-engineering
// Expert GIS tools for generating mathematically perfect marathon routes of exactly 26.2 miles using road network data and zone-sweep decomposition.
// Expert GIS tools for generating mathematically perfect marathon routes of exactly 26.2 miles using road network data and zone-sweep decomposition.
Specialized in working with Google Maps Grounding lite and MCP tools. Can provide information about specific locations like landmarks, businesses, and parks in a city. Also provide weather information for specific dates or historical weather information for locations.
Retrieve local rules and traffic information for a specific jurisdiction.
TODO - One line description of what this skill does.
Evaluates the plan against financial, community, and logistical goals.
Generates high-fidelity marathon routes using road network data (Dijkstra's algorithm) and outputting GeoJSON for visualization.
Step-by-step methodology for reviewing marathon plans for simulation readiness, covering route feasibility, logistics completeness, and safety clearance.
| name | gis-spatial-engineering |
| description | Expert GIS tools for generating mathematically perfect marathon routes of exactly 26.2 miles using road network data and zone-sweep decomposition. |
| metadata | {"adk_additional_tools":["plan_marathon_route","report_marathon_route","assess_traffic_impact"]} |
You use this skill to generate the physical path of the marathon.
You have access to a road network GeoJSON located at assets/network.json.
Key features available in this network include:
properties.name (e.g., Mandalay Bay,
Bellagio, Sphere, Las Vegas Sign, Allegiant Stadium, The Venetian,
Michelob Ultra Arena, etc.).
These landmarks are used automatically by plan_marathon_route() to build the route.properties.name (e.g.,
Las Vegas Boulevard, Las Vegas Freeway, Sahara Avenue, Flamingo Road,
Rainbow Boulevard, Paradise Road, Sunset Road, Tropicana Avenue,
Desert Inn Road, Eastern Avenue, Maryland Parkway, etc.).The default algorithm is zone-sweep: the route starts near a landmark, sweeps through city zones (neighborhoods) using non-crossing geometry, and finishes southbound on the Strip at the Las Vegas Sign. The algorithm handles all route geometry automatically — you do not need to select petals or manually sequence landmarks.
The legacy cloverleaf/petal algorithm is still available via the
petal_names parameter if explicitly requested.
plan_marathon_route() with no arguments produces a valid
26.2-mile zone-sweep route. Use start_landmark and seed for variety.plan_marathon_route(algorithm: str = "zone_sweep", start_landmark: Optional[str] = None, seed: Optional[int] = None, petal_names: Optional[list[str]] = None, geojson_data: Optional[str] = None):
Generate the exact 26.2-mile path.
algorithm: "zone_sweep" (default) or "cloverleaf".start_landmark: Name of a landmark to start near (e.g., "Michelob Ultra Arena"). Zone-sweep only.seed: Integer seed for route variety. Different seeds produce different routes. Zone-sweep only.petal_names: List of petal names. Cloverleaf algorithm only.add_water_stations(route_geojson: dict): Append water station features.add_medical_tents(route_geojson: dict): Append medical tent features.report_marathon_route(route_geojson: dict): Emit the final GeoJSON to the system registry.plan_marathon_route() with default arguments.seed to generate alternative routes when the user wants variety.start_landmark when the user specifies a preferred starting area.petal_names if the user explicitly asks for the cloverleaf/petal approach.