Mapbox Search Patterns

# Mapbox Search Patterns Skill

Expert guidance for AI assistants on using Mapbox search tools effectively. Covers tool selection, parameter optimization, and best practices for geocoding, POI search, and location discovery.

## Available Search Tools

### 1. search_and_geocode_tool

**Best for:** Specific places, addresses, brands, named locations

**Use when query contains:**

- Specific names: "Starbucks on 5th Avenue", "Empire State Building"
- Brand names: "McDonald's", "Whole Foods"
- Addresses: "123 Main Street, Seattle", "1 Times Square"
- Chain stores: "Target"
- Cities/places: "San Francisco", "Portland"

**Don't use for:** Generic categories ("coffee shops", "museums")

### 2. category_search_tool

**Best for:** Generic place types, categories, plural queries

**Use when query contains:**

- Generic types: "coffee shops", "restaurants", "gas stations"
- Plural forms: "museums", "hotels", "parks"
- Is-a phrases: "any coffee shop", "all restaurants", "nearby pharmacies"
- Industry terms: "electric vehicle chargers", "ATMs"

**Don't use for:** Specific names or brands

### 3. reverse_geocode_tool

**Best for:** Converting coordinates to addresses, cities, towns, postcodes

**Use when:**

- Have GPS coordinates, need human-readable address
- Need to identify what's at a specific location
- Converting user location to address

## Tool Selection Decision Matrix

| User Query                      | Tool                    | Reasoning                |
| ------------------------------- | ----------------------- | ------------------------ |
| "Find Starbucks on Main Street" | search_and_geocode_tool | Specific brand name      |
| "Find coffee shops nearby"      | category_search_tool    | Generic category, plural |
| "What's at 37.7749, -122.4194?" | reverse_geocode_tool    | Coordinates to address   |
| "Empire State Building"         | search_and_geocode_tool | Specific named POI       |
| "hotels in downtown Seattle"    | category_search_tool    | Generic type + location  |
| "Target store locations"        | search_and_geocode_tool | Brand name (even plural) |
| "any restaurant near me"        | category_search_tool    | Generic + "any" phrase   |
| "123 Main St, Boston, MA"       | search_and_geocode_tool | Specific address         |
| "electric vehicle chargers"     | category_search_tool    | Industry category        |
| "McDonald's"                    | search_and_geocode_tool | Brand name               |

## Parameter Guidance

### Proximity vs Bbox vs Country

**Three ways to spatially constrain search results:**

#### 1. proximity (STRONGLY RECOMMENDED)

**What it does:** Biases results toward a location, but doesn't exclude distant matches

**Use when:**

- User says "near me", "nearby", "close to"
- Have a reference point but want some flexibility
- Want results sorted by relevance to a point

**Example:**

```json
{
  "q": "pizza",
  "proximity": {
    "longitude": -122.4194,
    "latitude": 37.7749
  }
}
```

**Why this works:** API returns SF pizza places first, but might include famous NYC pizzerias if highly relevant

**Critical:** Always set proximity when you have a reference location! Without it, results are IP-based or global.

#### 2. bbox (Bounding Box)

**What it does:** Hard constraint - ONLY returns results within the box

**Use when:**

- User specifies an area: "in downtown", "within this neighborhood"
- Have a defined service area
- Need to guarantee results are within bounds

**Example:**

```json
{
  "q": "hotel",
  "bbox": [-122.51, 37.7, -122.35, 37.83] // [minLon, minLat, maxLon, maxLat]
}
```

**Why this works:** Guarantees all hotels are within SF's downtown area

**Watch out:** Too small = no results; too large = irrelevant results

#### 3. country

**What it does:** Limits results to specific countries

**Use when:**