Optimization Combining

// GOOD
1. User enters "Seattle"
2. Geocode "Seattle" → (lng, lat)
3. Use those coordinates for multiple category searches
4. Cache coordinates for session

// BAD
1. Geocode "Seattle" for coffee search
2. Geocode "Seattle" again for restaurant search
3. Geocode "Seattle" again for hotel search

1. category_search_tool → Get POIs
2. distance_tool (offline) → Calculate distances
3. bearing_tool (offline) → Get directions

1. category_search_tool({category: "hospital", proximity: user_location})
   → Returns 10 hospitals with coordinates
2. distance_tool(user_location, each_hospital)
   → Calculate exact distances offline
3. Sort by distance

1. search_and_geocode_tool({q: "Space Needle"})
   → Get destination coordinates
2. directions_tool({from: user_location, to: space_needle_coords})
   → Get turn-by-turn directions

1. search_and_geocode_tool({q: "warehouse"})
   → Get warehouse coordinates
2. isochrone_tool({coordinates: warehouse, time: 30, profile: "driving"})
   → Get 30-minute delivery zone polygon
3. point_in_polygon_tool(customer_address, delivery_zone)
   → Check if customer is in delivery zone

1. category_search_tool({category: "restaurant", limit: 10})
   → Get restaurant coordinates
2. static_map_image_tool({
     markers: restaurant_coordinates,
     auto_fit: true
   })
   → Create map image showing all restaurants

1. category_search_tool({category: "taco"}) → No results
2. Check: Is "taco" a valid category?
   → Use category_list_tool → See "mexican_restaurant" is valid
3. Retry: category_search_tool({category: "mexican_restaurant"}) → Success

resource_reader_tool({uri: "mapbox://categories"})