{
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    "title": "Google Maps Reviewer Geo Profile API",
    "description": "Infer a Google Maps reviewer's home region from their review history. Clusters review coordinates into a standardized home-region guess (city/state/country + ISO codes), a confidence score, and a local-vs-travel footprint. One row per reviewer, for reviewer vetting and fraud research. MCP-ready.",
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        "properties": {
          "contributorId": {
            "title": "Contributor ID",
            "type": "string",
            "description": "Enter a single Google Maps contributor ID (the long numeric ID from a reviewer's profile, e.g. '107022004965696773221'). Provide this, `contributorIds`, or both. You can read a contributor ID from any place review's reviewer."
          },
          "contributorIds": {
            "title": "Contributor IDs",
            "type": "array",
            "description": "Provide a list of Google Maps contributor IDs to profile in one run. Merged with `contributorId` and de-duplicated. One derived row is returned per reviewer.",
            "items": {
              "type": "string"
            }
          },
          "regionGranularity": {
            "title": "Region Granularity",
            "enum": [
              "city",
              "admin1",
              "country"
            ],
            "type": "string",
            "description": "Level the home-region guess and confidence are computed at: 'city' (e.g. Chicago, IL), 'admin1' (state or province), or 'country'. The row always includes the full standardized breakdown (city, admin, country, ISO codes) regardless. Default 'city'.",
            "default": "city"
          },
          "minCityPopulation": {
            "title": "Minimum City Population",
            "minimum": 0,
            "type": "integer",
            "description": "Snap each review to the nearest city with at least this population, so big-metro neighborhoods (e.g. 'Chicago Loop') group under the principal city ('Chicago'). Default 100000. Lower it (e.g. 1000) to keep smaller towns distinct, at the cost of large metros fragmenting across neighborhoods.",
            "default": 100000
          },
          "hl": {
            "title": "Language Code",
            "type": "string",
            "description": "Set the two-letter interface language code (e.g. 'en', 'es', 'de'). Affects the source review text; the region output is standardized independently of this. Defaults to 'en'.",
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          },
          "maxResultsPerContributor": {
            "title": "Maximum Reviews Per Contributor",
            "minimum": 1,
            "maximum": 200,
            "type": "integer",
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          }
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