AI policy drafting
Describe a rule, review catalog matches and tests, and install the result yourself.
On this page
Create a draft
Open the policy editor’s AI drafting flow and describe the action, surface, environment, and desired outcome. The job runs asynchronously. Keep the job visible while it reports progress, completion, or failure; do not treat an accepted job as an installed policy.
The current drafter can use the workspace’s MCP catalog and installed surfaces. It presents test results and matching-tool notes based on the available examples and tool names.
Review the result
Check the rule’s effect, conditions, trigger, environment, and identity assumptions. Confirm a known matching action and a close non-match. Test actual workflow cases beyond the generated examples. Install only after a human reviews the resulting policy.
API job contract
The customer API provides administrator-gated job routes:
| Operation | Start route | Poll route |
|---|---|---|
| Draft rule | POST /api/v1/policies/draft-rule/jobs | GET /api/v1/policies/draft-rule/jobs/{id} |
| Summarize change | POST /api/v1/policies/draft-change-summary/jobs | GET /api/v1/policies/draft-change-summary/jobs/{id} |
| Narrow a flagged rule | POST /api/v1/decisions/{decisionID}/suggest-policy-fix/jobs | GET /api/v1/decisions/{decisionID}/suggest-policy-fix/jobs/{id} |
Use a user session and the required AI-rule entitlement. The draft-rule body contains a non-empty description. Read the job status and its nested result; preserve unknown result fields in clients.
Deprecations and limits
Older synchronous drafting routes remain mounted for compatibility but are deprecated and bounded by a request timeout. New integrations should use jobs. Drafting requires the server’s model service to be configured. A failed job should remain a visible failure, not a success with an empty draft.
Review scope and drafting failures
Current hosted drafting can propose shared coding-agent rules from supported history, and can draft native PII/secret content controls. Historical source is evidence origin, not proof that the resulting policy should apply only to that agent. Review the proposed target surfaces and real tool schemas. Native Cursor file-edit events remain audit-only.
If drafting fails, retain the request and inspect the visible error before retrying. A generated explanation or passing generated examples does not prove detector accuracy: independently test the sensitive case, a benign near-match and the actual target integration. Conversational multi-step policy Builder improvements are still in review and are not an available hosted feature in this guide.