Create Quality Policy
create_quality_policyCreate a project-specific quality policy that defines required checks, metric thresholds, and validation protocols to enforce model quality gates before runs.
Instructions
Save project-specific checks. Built-in checks have metric (r_hat_max, mae, rmse, wape, prediction_mae, prediction_rmse, prediction_wape), maximum and required. Custom numeric checks use metric custom:, name, units, operator (lte/gte/between), applicable minimum/maximum and required. Boolean checks use kind=boolean, operator=equals and expected=true/false. Manual checks use kind=manual, equals, expected=true; agents can define these but cannot submit manual sign-off. Custom bounds may be negative. WAPE is a fraction. Prediction-window checks require saved finite actuals/predictions at unique dates after the saved training window; this does not certify untouched holdout provenance. No default thresholds are assumed. Declare at least one required check, use each metric once, and set maximum R-hat at least 1. Optional validation_protocol declares a temporal holdout split, configured sampling minima, R-hat and prediction WAPE limits before both runs launch under this policy. The backend validates policy rules.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | ||
| checks | Yes | ||
| study_id | Yes | ||
| rationale | Yes | ||
| validation_protocol | No |
Output Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||