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home / skills / jeremylongshore / claude-code-plugins-plus-skills / vertex-engine-inspector

vertex-engine-inspector skill

/plugins/ai-ml/jeremy-vertex-engine/skills/vertex-engine-inspector

This skill helps you inspect and validate Vertex AI Agent Engine deployments, generating production readiness scores and actionable security posture insights.

npx playbooks add skill jeremylongshore/claude-code-plugins-plus-skills --skill vertex-engine-inspector

Review the files below or copy the command above to add this skill to your agents.

Files (8)
SKILL.md
1.2 KB
---
name: vertex-engine-inspector
description: |
  Execute 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 agent engine" or "validate depl... Trigger with relevant phrases based on skill purpose.
allowed-tools: Read, Grep, Glob, Bash(cmd:*)
version: 1.0.0
author: Jeremy Longshore <[email protected]>
license: MIT
---

# Vertex Engine Inspector

## Overview


This skill provides automated assistance for vertex engine inspector tasks.
This skill provides automated assistance for the described functionality.

## Prerequisites

- Appropriate file access permissions
- Required dependencies installed

## Instructions

1. Invoke this skill when the trigger conditions are met
2. Provide necessary context and parameters
3. Review the generated output
4. Apply modifications as needed

## Output

The skill produces structured output relevant to the task.

## Error Handling

See `{baseDir}/references/errors.md` for comprehensive error handling.

## Examples

See `{baseDir}/references/examples.md` for detailed examples.

## Resources

- Project documentation
- Related skills and commands

Overview

This skill inspects and validates Vertex AI Agent Engine deployments, producing a production readiness score and remediation guidance. It covers Code Execution Sandbox, Memory Bank consistency, A2A protocol compliance, and security posture checks. Use it to automate engineering reviews and surface actionable findings for deployments.

How this skill works

The skill runs a sequence of automated checks against a deployed Vertex AI Agent Engine: sandbox configuration, memory bank integrity, inter-agent A2A protocol behavior, and security controls. It aggregates findings into a structured report with severity levels and a summarized production readiness score. The output includes concrete remediation steps, evidence artifacts, and recommendations for configuration changes.

When to use it

  • Before promoting an agent engine to production
  • During security or compliance audits of agent deployments
  • When validating a new code execution sandbox or memory bank implementation
  • After updates to inter-agent communication protocols (A2A)
  • When troubleshooting unexpected agent behavior or performance regressions

Best practices

  • Provide deployment context and access credentials with least-privilege roles
  • Run inspections in a staging environment before production scans
  • Correlate findings with runtime logs and telemetry for root cause analysis
  • Act on high and critical severity recommendations first, then address medium/low items
  • Regularly re-run inspections after configuration or dependency changes

Example use cases

  • Validate that the Code Execution Sandbox enforces resource limits and isolation before go-live
  • Verify Memory Bank integrity and data lifecycle policies for agent state persistence
  • Check A2A protocol conformance across agent clusters to prevent message misrouting or deadlocks
  • Scan security posture for exposed endpoints, inadequate IAM roles, or missing encryption at rest/in transit
  • Generate a production readiness report for stakeholder review and change approvals

FAQ

What outputs does the inspector produce?

Structured report with findings, severity levels, evidence artifacts, remediation steps, and an overall production readiness score.

What permissions are required to run inspections?

Least-privilege access to deployment metadata, logs, and configuration; specific permissions depend on Vertex AI resources being inspected.