validator-expert

# Validator Expert ## Current State !`gcloud config get-value project 2>/dev/null || echo 'no active project'` !`gcloud auth list --filter=status:ACTIVE --format="value(account)" 2>/dev/null || echo 'not authenticated'` ## Overview Validate production readiness of Vertex AI Agent Engine deployments by executing weighted checks across five categories: security (30 points), monitoring (20 points), performance (25 points), compliance (15 points), and best practices (10 points). This skill produces a 0-100% composite score with pass/fail per check and prioritized remediation recommendations. ## Prerequisites - `gcloud` CLI authenticated with `roles/aiplatform.viewer`, `roles/iam.securityReviewer`, and `roles/monitoring.viewer` - Access to the target Google Cloud project and Vertex AI Agent Engine deployment - Cloud Monitoring API and Cloud Logging API enabled in the project - Knowledge of the deployment's expected SLOs (latency targets, error rate thresholds) - Read-only access to IAM policies, VPC-SC configurations, and service account bindings ## Instructions 1. Retrieve the deployment configuration using the Python SDK (`vertexai.Client().agent_engines.get(name)`) or REST API (`GET https://{LOCATION}-aiplatform.googleapis.com/v1/projects/{PROJECT}/locations/{LOCATION}/reasoningEngines/{ID}`) and parse model, scaling, and feature settings 2. Run the security validation suite (see [security checklist](references/security-checklist.md)): - Check if Agent Identity is ena...