Individual skill
vertex-engine-inspector
Inspect and validate Vertex AI Agent Engine deployments including Code Execution Sandbox, Memory Bank, A2A protocol compliance, and security posture. Generates production readiness scores. Use when asked to inspect, validate, or audit an Agent Engine deployment. Trigger with "inspect agent engine", "validate agent engine deployment", "check agent engine config", "audit agent engine security", "agent engine readiness check", "vertex engine health", or "reasoning engine status".
skills/.curated/vertex-engine-inspector/SKILL.md
Source commit 0500b275e963c027f6b410e8c49c0446945c574e
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- Last checked
- Nov 12, 2026
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- Repository stars (not skill ratings)
- 2,917
- Repository last updated
- Nov 12, 2026
- License
- MIT
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- ai Repository topic
- automation Repository topic
- claude-code Repository topic
- devops Repository topic
- mcp Repository topic
- ai-agents Repository topic
- anthropic Repository topic
- claude-code-plugins Repository topic
- developer-tools Repository topic
- llm Repository topic
- ai Declared skill tag
- deployment Declared skill tag
- security Declared skill tag
- compliance Declared skill tag
- security Derived category
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SKILL.mdcore · 6,820 bytesreferences/ARD.mddoc · 5,587 bytesreferences/PRD.mddoc · 4,621 bytesreferences/errors.mddoc · 6,158 bytesreferences/example-inspection-report.mddoc · 1,263 bytesreferences/examples.mddoc · 19,840 bytesreferences/inspection-categories.mddoc · 3,384 bytesreferences/inspection-workflow.mddoc · 1,171 bytesscripts/check-security.pyruns · 8,494 bytesscripts/inspect-agent.shruns · 6,144 bytes
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# Vertex Engine Inspector
## Overview
Inspect and validate Vertex AI Agent Engine deployments across seven categories: runtime configuration, Code Execution Sandbox, Memory Bank, A2A protocol compliance, security posture, performance metrics, and monitoring observability. This skill generates weighted production-readiness scores (0-100%) with actionable recommendations for each deployment.
## Prerequisites
- `google-cloud-aiplatform[agent_engines]>=1.120.0` Python SDK installed
- `gcloud` CLI authenticated (for IAM and monitoring queries — **not** for Agent Engine CRUD)
- IAM roles: `roles/aiplatform.user` and `roles/monitoring.viewer` granted on the target project
- Access to the target Google Cloud project hosting the Agent Engine deployment
- `curl` for A2A protocol endpoint testing (AgentCard, Task API, Status API)
- Cloud Monitoring API enabled for performance metrics retrieval
- Familiarity with Vertex AI Agent Engine concepts: Code Execution Sandbox, Memory Bank, Model Armor