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Most Sixtyfour intelligence endpoints accept a struct field that defines exactly what data you want returned in structured_data. This guide explains how struct works and how the API resolves and casts types.

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How struct works

Each key in struct becomes a field in the response’s structured_data, and its value tells the agent what to find. You can pass either a plain-English description or an object with description and type: 
{
  "struct": {
    "email": "The individual's email address",
    "num_employees": {"description": "Approximate employee count", "type": "int"}
  }
}
The agent uses these descriptions to guide its research. Be specific — "company's primary Instagram handle" returns better results than "social".
For endpoints that support struct (e.g., Company Intelligence, People Intelligence, QA Agent), only fields specified in struct appear in structured_data.

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Type casting

The API automatically handles type casting with intelligent type preservation.

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Resolution priority

Type resolution follows this priority:
  1. Explicit type definitions in struct (highest)
  2. Original input types from the request body (e.g., target_company, lead_info, data)
  3. Inferred types from example values in struct
  4. String (default)

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Supported types

TypeExample values
"str" or "string""Pacific View Studios"
"int" or "integer"50, 1000
"float"95.5, 3.14
"bool" or "boolean"true, false
"list"["item1", "item2"]
"list[str]"["item1", "item2"]
"list[int]"[1, 2, 3]
"list[float]"[1.5, 2.7, 3.14]
"list[bool]" or "list[boolean]"[true, false]
"dict""{\"key\": \"value\"}" (stringified JSON)
The "dict" type returns a stringified JSON value, not a nested typed object. Parse it client-side with json.loads() (Python) or JSON.parse() (JavaScript).

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Examples

Type override — explicit type in struct overrides the original input type: 
{
  "lead_info": {"age": 30, "is_active": true},
  "struct": {
    "age": {"type": "str"},
    "location": "Current location"
  }
}
// Output: {"age": "30", "is_active": true, "location": "New York"}
Explicit type definition — useful when you want predictable shapes: 
{
  "struct": {
    "age": {"description": "Person's age", "type": "int"},
    "is_verified": {"description": "Status", "type": "bool"}
  }
}
// Output: {"age": 30, "is_verified": true}
Type inference from values — types are inferred from the example values you pass: 
{
  "struct": {
    "score": 95.5,
    "active": false,
    "count": 42
  }
}