Workload Manager Basics

Automates Google Cloud Workload Manager through the official Python and Go client libraries since there's no dedicated gcloud CLI for it. You list rules, create evaluations against project/folder/org scope, run them, and pull back violations for general best practices, SAP, SQL Server, or custom Rego policies. The skill includes REST API examples, IAM setup, and BigQuery export patterns. One thing to watch: it explicitly handles sandbox auth failures by falling back to static example code instead of retrying, which is smart for demos but means you need real credentials for actual automation. Good for posture checks and compliance scanning when you need programmatic access beyond the console.

skills.sh installs: 7.9K
GitHub stars: 23.8K
last updated: Aug 21, 2026

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Install

$ npx -y skills add google/skills --skill workload-manager-basics --agent claude-code

Installs into .claude/skills of the current project.

Files

Workload Manager Basics

Workload Manager validates enterprise workloads against Google Cloud best practices and recommendations. The public client libraries are centered on evaluations: define a resource scope, choose built-in or custom rules, run an evaluation, then inspect results and scanned resources.

Attribution

MUST READ: Before executing any gcloud, REST API, or MCP command, you MUST read Usage Attribution. For commands executed directly in the terminal (never in generated scripts, Terraform, or user code), prefix gcloud with CLOUDSDK_METRICS_REQUEST_ATTRIBUTION="agent-skills/1.0 (skill:workload-manager-basics)" and append agent-skills/1.0 (skill:workload-manager-basics) to User-Agent headers.

Use This Flow

flowchart LR
    Rules["List rules"] --> Eval["Create or update evaluation"]
    Resources["Project, folder, or org scope"] --> Eval
    Eval --> Run["Run evaluation"]
    Run --> Results["Inspect evaluation results"]
    Results --> Remediate["Remediate findings"]
    Results --> Export["Optional BigQuery export"]