Okareo · Schema
EvaluatorSpecRequest
CompanyArtificial IntelligenceSynthetic DataVoice AgentsTesting
Properties
| Name | Type | Description |
|---|---|---|
| name | object | Name of the evaluator |
| user_input | object | Primary user instruction for generation. When set, used instead of description for the LLM prompt. |
| description | object | Description for the evaluator. When this request is sent to generate an evaluator, this field will be used to generate it (or user_input if set). |
| requires_scenario_input | boolean | Whether the evaluator requires scenario input |
| requires_scenario_result | boolean | Whether the evaluator requires scenario expected result |
| output_data_type | object | Evaluator output data type (i.e., bool, int, float) |
| project_id | object | ID for the project |
| check_type | object | model or code based check |
| prior_code | object | Existing code to refine (code branch). When set, LLM is asked to modify/improve it. |
| prior_prompt | object | Existing prompt to refine (model branch). When set, LLM is asked to revise it. |
JSON Schema
{
"$schema": "https://json-schema.org/draft/2020-12/schema",
"$id": "https://artifacts.apis.io/okareo/json-schema/okareo-evaluator-spec-request-schema.json",
"title": "EvaluatorSpecRequest",
"x-generated": "2026-11-10",
"x-method": "derived",
"x-generator": "derive-json-schema.py",
"x-source": "openapi/okareo-checks-api-openapi.yml#/components/schemas/EvaluatorSpecRequest",
"properties": {
"name": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"title": "Name",
"description": "Name of the evaluator"
},
"user_input": {
"anyOf": [
{
"type": "string",
"maxLength": 50000
},
{
"type": "null"
}
],
"title": "User Input",
"description": "Primary user instruction for generation. When set, used instead of description for the LLM prompt."
},
"description": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"title": "Description",
"description": "Description for the evaluator.\n When this request is sent to generate an evaluator, this field will be used to generate it (or user_input if set)."
},
"requires_scenario_input": {
"type": "boolean",
"title": "Requires Scenario Input",
"description": "Whether the evaluator requires scenario input",
"default": false
},
"requires_scenario_result": {
"type": "boolean",
"title": "Requires Scenario Result",
"description": "Whether the evaluator requires scenario expected result",
"default": false
},
"output_data_type": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"title": "Output Data Type",
"description": "Evaluator output data type (i.e., bool, int, float)"
},
"project_id": {
"anyOf": [
{
"type": "string",
"format": "uuid"
},
{
"type": "null"
}
],
"title": "Project Id",
"description": "ID for the project"
},
"check_type": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"title": "Check Type",
"description": "model or code based check",
"default": "code"
},
"prior_code": {
"anyOf": [
{
"type": "string",
"maxLength": 50000
},
{
"type": "null"
}
],
"title": "Prior Code",
"description": "Existing code to refine (code branch). When set, LLM is asked to modify/improve it."
},
"prior_prompt": {
"anyOf": [
{
"type": "string",
"maxLength": 50000
},
{
"type": "null"
}
],
"title": "Prior Prompt",
"description": "Existing prompt to refine (model branch). When set, LLM is asked to revise it."
}
},
"type": "object"
}
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