// Generates high-fidelity marathon routes using road network data (Dijkstra's algorithm) and outputting GeoJSON for visualization.
| name | route-planning |
| description | Generates high-fidelity marathon routes using road network data (Dijkstra's algorithm) and outputting GeoJSON for visualization. |
Goal: Design a mathematically perfect 42.195 km marathon route using real road network data, ensuring distance certification.
network.json) and Dijkstra's algorithm to calculate a certified 42.195 km route between specified landmarks.marathon_route_geojson event for real-time map visualization.network.json: Road network adjacency graph for Las Vegas.tools.py: Contains the core plan_marathon_route implementation.scripts/validate_route.py: Validates distance and waypoints.references/marathon_planning_guide.md: Consolidated guide for marathon standards, road width, traffic severity, and supported landmarks.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.
Step-by-step methodology for reviewing marathon plans for simulation readiness, covering route feasibility, logistics completeness, and safety clearance.
Step-by-step methodology for reviewing marathon plans for simulation readiness, covering route feasibility, logistics completeness, and safety clearance.