kilo-org/gcloud

gcloud CLI Skill for AI Agents

This document provides essential guidelines and best practices for AI agents interacting with the Google Cloud SDK (gcloud CLI). Following these rules is critical to avoid hallucinated commands, flags, flag values, and positional argument syntax, prevent destructive actions, and minimize context window usage.

Getting Started

1. Installation

If the gcloud executable is missing, refer to the official Google Cloud CLI Installation Guide to install it on your platform (Linux, macOS, Windows, etc.).

2. Authorization

Authenticate the CLI with Google Cloud. Choose the flow that matches your running environment:

• User Account (Interactive): Run gcloud auth login. Follow the browser prompts to sign in.
• User Account (Headless Flow): If operating on a terminal without a web browser (e.g. containers, remote SSH), append the --no-browser flag: gcloud auth login --no-browser. Copy the URL, sign in on another machine, and return the authentication code.
• Application Default Credentials (ADC): To authenticate code calls from local applications or SDK libraries, set up ADC via gcloud auth application-default login (append --no-browser for headless environments).
• Service Account (Best for Detached/Headless Automation): Authenticate directly using a JSON key file. Ideal for fully automated, background tasks and pipelines: gcloud auth activate-service-account --key-file=path/to/key.json. Note that some organizations may restrict access to JSON key files for security reasons.
• Service Account Impersonation (Preferred for Local Pair-Programming Agents): Leverage the human developer's existing user credentials to assume a service account identity. Best for local development assistants to avoid insecure private keys on human workstations: gcloud config set auth/impersonate_service_account SERVICE_ACCT_EMAIL

Separation of Privilege (Critical): Both service account approaches ensure the agent's permissions remain strictly distinct from the human user's wide access limits (enforcing least privilege), and ensure actions are properly audited under the agent's focused identity. (Impersonation requires roles/iam.serviceAccountTokenCreator).

For more detailed strategies and authentication types (such as Workload Identity Federation), see Authorizing the gcloud CLI.

Core Principles

1. Explicit Command Validation (Mandatory)

Your internal knowledge of gcloud may be stale or prone to hallucination (e.g., hallucinating commands, flags, flag values, or positional argument syntax). You are FORBIDDEN from executing commands until you have validated the exact syntax at the leaf level.

• Action: Always call gcloud help <command> for the exact command you intend to run (e.g., gcloud help compute instances create).
• Verify: Ensure the command, flags, flag values, and positional argument syntax are valid for that specific leaf command before attempting execution. Validation is not transitive from parent groups.

2. Data Reduction Strategies

To save context window space and reduce latency, always minimize the volume of data returned by gcloud.

• Projection: Use --format=json(key1, key2, ...) to select only the specific fields needed for your task. To understand the advanced projection and formatting syntax, refer to gcloud topic projections and gcloud topic formats.

• Limiting: Use --limit=N to cap the number of resources returned.

• Filtering: Use --filter to narrow down results server-side. Prioritize : for pattern matching and never quote the right side of the colon. Treat the entire filter flag as a singular string without quoting or escaping characters. To study the filter expression syntax, refer to gcloud topic filters.

• Schema Discovery: Unconstrained resource lists can quickly exhaust your context window with redundant data. To prevent this, discover a resource's schema before executing queries. If you are unsure of the JSON key path for projecting fields (--format) or filtering (--filter), run the targeted resource's list command (if supported) with a single-item limit:

  gcloud <GROUP> <RESOURCE> list --limit=1 --format=json
  

  Examine this single instance's JSON structure to safely identify the correct schema keys before requesting full or filtered datasets.

3. Execution Constraints

• Single Commands: Execute a single gcloud command at a time. No command chaining or sequencing.
• No Shell Operators: Do not use command substitution ($(...)), pipes (|), or redirection (>, >>, <). This is to increase command safety and ensure commands are more easily understandable and reviewable by users.
• No Interactivity: Do not run interactive commands or commands requiring a TTY (e.g., gcloud interactive). You must enforce non-interactive mode by appending --quiet (or -q) to your commands. This ensures that defaults are used or errors are raised if input is required.

4. Project and Location Scoping (Critical)

To ensure commands are deterministic, non-interactive, and target the correct environment, you must explicitly manage project and location scoping.

• Explicit Project Target: Do not rely on active configuration defaults. Always append --project=<PROJECT_ID> to all resource-manipulating and querying commands (unless running pure local config commands). This avoids accidental execution against the wrong project.

• Prevent Location Prompts: Many Google Cloud resources are regional or zonal. If you omit the location flag (e.g., --region, --zone, or --location), gcloud will trigger an interactive prompt to select a zone/region. This violates the No Interactivity rule. Always provide explicit location flags if the command requires them.

• Location Discovery: If you do not know the correct region, zone, or location for a service, run discovery commands first (remembering to limit results if there are many):

  • Compute Engine (VMs, Networks):

    • gcloud compute regions list --project=<PROJECT_ID>
    • gcloud compute zones list --project=<PROJECT_ID>

  • Other Services (Standard API Style): Many GCP services utilize a unified locations list command:

    • gcloud <GROUP> locations list --project=<PROJECT_ID>
    • Examples: gcloud artifacts locations list, gcloud kms locations list, gcloud secrets locations list.

Safety & Guardrails

[!CAUTION] Destructive actions (delete, update, remove) MUST be explicitly authorized by the user. Never invoke them autonomously unless explicitly instructed to do so in the context of a safe, pre-approved workflow.

Prohibited Operations (Denylist)

You are strictly prohibited from executing the following commands autonomously. These require explicit human-in-the-loop authorization:

• Any IAM policy, role, or binding modification (Security): Risk of privilege escalation, administrative lockout, service disruption, or unauthorized data exposure.
• No Proactive API Enabling: Assume necessary APIs are enabled. To prevent unexpected resource provisioning or billing charges, do not proactively try to enable APIs. User approval is required to enable any API.
• gcloud * delete (Destructive): Irreversible resource destruction (e.g., project deletion) or data wiping.
• gcloud billing * (Financial): Risk of service disruption or unbounded costs.
• gcloud organizations * (Governance): Org-level changes affect security posture for all users.
• gcloud kms * (Encryption): Risk of permanently locking data.
• gcloud infra-manager deployments apply (Destructive): Autonomous IaC execution can destroy managed resources.

Execution Guidelines

• Dry Run (Mandatory): You MUST invoke a command with --dry-run (or equivalent) first if it exists, before executing the actual command, to preview changes.

• Long Running Operations: For commands that support it, the --async flag is highly recommended for long-running operations to avoid blocking the agentic flow. Note that not every command has an --async flag. For commands that return an operation ID (whether via --async or by default), you are responsible for polling for completion if the operation status is needed for the next step.

Structured Workflows

Discovery Workflow

When asked to perform a task on a service you are not familiar with:

1. You MUST invoke help on a command (e.g., gcloud help <COMMAND>) before invoking it.
2. If you do not know the exact command, traverse the command tree by invoking help on a command group (e.g., gcloud help compute) to discover available subcommands and groups.
3. Schema Discovery: If you need to filter or project fields from a list command, but do not know the exact JSON keys, first run gcloud <GROUP> <RESOURCE> list --limit=1 --format=json to safely discover the schema. Never run a raw list command without scoping constraints (like --limit=1), as unconstrained results will pollute and exhaust your context window.
4. Execute with data reduction flags.

Quick Reference / Cheat Sheet

Task | Command Template ------------------ | ---------------------------------------------------------- Discover Schema | gcloud <GROUP> <RESOURCE> list --limit=1 --format=json Filtered List | gcloud <GROUP> <RESOURCE> list --filter="status:RUNNING" Specific Columns | gcloud <GROUP> <RESOURCE> list --format="json(name, id)" Learn Filters | gcloud topic filters Learn Formats | gcloud topic formats Learn Projections | gcloud topic projections Asynchronous Op | gcloud <COMMAND> --async Check Operation | gcloud operations describe <OPERATION_ID> Common commands | gcloud cheat-sheet List Regions (GCE) | gcloud compute regions list --project=<PROJECT_ID> List Zones (GCE) | gcloud compute zones list --project=<PROJECT_ID> List Locations | gcloud <GROUP> locations list --project=<PROJECT_ID>

Refer to the gcloud CLI Scripting Guide for guidance on using the gcloud CLI in automation.