validator-expert
Validate production readiness of Vertex AI Agent Engine deployments across security, monitoring, performance, compliance, and best practices. Generates weighted scores (0-100%) with actionable recommendations. Use when asked to "validate deploymen...
When & Why to Use This Skill
This Claude skill serves as a comprehensive production readiness validator for Vertex AI Agent Engine deployments. It automates the complex process of auditing security, monitoring, performance, and compliance, providing weighted scores and actionable recommendations to ensure AI agents meet enterprise-grade standards before going live.
Use Cases
- Pre-deployment Security Audit: Automatically verify IAM roles, VPC Service Controls, and encryption settings to ensure a secure environment for AI agents.
- Operational Monitoring Setup: Validate that Cloud Monitoring dashboards, alerting policies, and token usage tracking are correctly configured for production visibility.
- Compliance and Governance Verification: Ensure deployments meet data residency, audit logging, and privacy requirements to satisfy regulatory standards.
- Performance Optimization: Review auto-scaling configurations, resource limits, and caching strategies to prevent latency issues and manage costs effectively.
| name | validator-expert |
|---|---|
| description | Validate production readiness of Vertex AI Agent Engine deployments across |
| allowed-tools | Read, Grep, Glob, Bash |
| license | MIT |
What This Skill Does
Production validator for Vertex AI deployments. Performs comprehensive checks on security, compliance, monitoring, performance, and best practices before approving production deployment.
When This Skill Activates
Triggers: "validate deployment", "production readiness", "security audit vertex ai", "check compliance", "validate adk agent"
Validation Checklist
Security Validation
- ✅ IAM roles follow least privilege
- ✅ VPC Service Controls enabled
- ✅ Encryption at rest configured
- ✅ No hardcoded secrets
- ✅ Service accounts properly configured
- ✅ Model Armor enabled (for ADK)
Monitoring Validation
- ✅ Cloud Monitoring dashboards configured
- ✅ Alerting policies set
- ✅ Token usage tracking enabled
- ✅ Error rate monitoring active
- ✅ Latency SLOs defined
Performance Validation
- ✅ Auto-scaling configured
- ✅ Resource limits appropriate
- ✅ Caching strategy implemented
- ✅ Code Execution sandbox TTL set
- ✅ Memory Bank retention configured
Compliance Validation
- ✅ Audit logging enabled
- ✅ Data residency requirements met
- ✅ Privacy policies implemented
- ✅ Backup/disaster recovery configured
Tool Permissions
Read, Grep, Glob, Bash - Read-only analysis for security
References
- Vertex AI Security: https://cloud.google.com/vertex-ai/docs/security