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GET
/
api
/
automl
/
feature-engineering
/
jobs
/
{job_id}
Get a feature engineering proposal
curl --request GET \
  --url https://api.example.com/api/automl/feature-engineering/jobs/{job_id} \
  --header 'Authorization: Bearer <token>'
{
  "job_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
  "target_table_name": "<string>",
  "domain": "<string>",
  "owner": "<string>",
  "created_at": "2023-11-07T05:31:56Z",
  "updated_at": "2023-11-07T05:31:56Z",
  "recipe": {
    "target_table": "<string>",
    "entity_grain": [
      "<string>"
    ],
    "label": {
      "name": "label",
      "type": "binary",
      "column": "<string>",
      "derivation": "<string>",
      "positive_class_value": "<unknown>"
    },
    "features": [
      {
        "name": "<string>",
        "expression": "<string>",
        "source_table": "<string>",
        "description": "<string>",
        "data_type": "<string>"
      }
    ],
    "notes": "<string>"
  },
  "sql": "<string>",
  "validation": {
    "estimated_row_count": 123,
    "label_distribution": {},
    "high_null_columns": {},
    "warnings": [
      "<string>"
    ]
  },
  "error": "<string>"
}

Authorizations

​
Authorization
string
header
required

The access token received from the authorization server in the OAuth 2.0 flow.

Path Parameters

​
job_id
string<uuid>
required

Feature engineering job ID.

Response

Successful Response

The crew's proposal returned to the user for review.

​
job_id
string<uuid>
required
​
status
enum<string>
required

Lifecycle of an AutoML feature engineering job.

Available options:
running,
pending_approval,
failed,
approved,
materializing,
complete
​
target_table_name
string
required
​
domain
string
required
​
owner
string
required
​
created_at
string<date-time>
required
​
updated_at
string<date-time>
required
​
recipe
FeatureRecipe · object | null

Structured recipe describing the training table the crew designed.

​
sql
string | null

The CREATE TABLE AS SELECT query the crew produced.

​
validation
ValidationSummary · object | null

Result of running the CTAS query with a row limit during validation.

Kept intentionally lean. Large agents produce more than 10 KB of JSON when this grows with per-column null rates and sample rows. That often exceeds output-token limits. Run the SQL directly to inspect rows. Only persist what's cheap and structurally useful.

​
error
string | null