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Gcloud CLI Skill

Free

Enhance gcloud CLI command safety and validation.

by google17.6k stars on google/skills
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Updated Aug 10, 2026
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Free · Opens the source repo

What Gcloud CLI Skill does

The Gcloud CLI Skill provides essential guidelines for safely interacting with the Google Cloud SDK (gcloud CLI). It emphasizes the importance of explicit command validation to prevent errors and potential destructive actions when executing commands across Google Cloud Platform (GCP) services. This skill is particularly useful for developers and engineers who frequently work with the gcloud CLI, ensuring that they adhere to best practices while executing commands.

By integrating this skill into your workflow, you will benefit from a structured approach to command execution. The skill mandates that all commands undergo strict syntax validation through gcloud help <command> before any execution or command proposal. This prevents the common pitfalls of command hallucinations and ensures that all flags and parameters are accurate and appropriate for the specific command being used.

Additionally, the skill provides a clear framework for planning and executing gcloud commands, which includes a mandatory four-step plan template. This template ensures that users validate syntax, verify parameters, propose dry-run commands when applicable, and seek authorization for potentially sensitive operations. This structured approach minimizes the risk of errors and enhances the overall efficiency of using the gcloud CLI.

Overall, the Gcloud CLI Skill is designed for developers and DevOps professionals who require a reliable method for managing GCP resources through the command line, ensuring that their interactions with the gcloud CLI are both safe and effective.

When to use it

Use this skill when planning or executing `gcloud` CLI commands to ensure safety and accuracy in command syntax.

When not to use it

This skill is not suitable for writing Google Cloud client library code or making raw REST/gRPC API requests.

What you can build with it

Validating a Command

When planning to execute a `gcloud` command, use this skill to validate the command syntax with `gcloud help <command>` first.

Creating a Deployment Plan

Use this skill to generate a structured deployment plan that includes mandatory syntax validation and parameter checks.

Executing Sensitive Operations

Before executing commands that could affect production environments, ensure you follow the skill's guidelines for validation and authorization.

How to install Gcloud CLI Skill

View source

1. Install with the skills CLI

npx skills add google/skills/gcloud --agent claude-code

2. Or install it manually

Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.

Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs

Inside SKILL.md

Written by google

gcloud CLI Skill for AI Agents

[!CAUTION]

MANDATORY PRE-CONDITION: EXPLICIT LEAF-LEVEL SYNTAX VALIDATION

All pre-existing knowledge of gcloud commands, flags, flag values, and positional argument syntax is stale and prone to hallucination.

NEVER propose command parameters, output flag options, execute commands, OR outline step-by-step plans for any gcloud task before validating leaf-level syntax via gcloud help <command> (or including leaf-level help lookup as a mandatory step in the plan).

Mandatory Action Rules:

  1. Direct Execution & Code Generation: ALWAYS invoke gcloud help <leaf_command> (e.g. gcloud help compute instances create or gcloud help sql instances create) before proposing or executing the final command syntax.

  2. Planning & Strategy Queries: When asked for a plan, strategy, or next steps to achieve a user goal (e.g., "What is your plan to accomplish X..."), the response MUST explicitly include running gcloud help <leaf_command> as Step 1 of the plan before proposing flags or executing commands.

  3. Non-Transitive Validation: Parent command group help (e.g. gcloud help compute) is not sufficient for leaf-level syntax validation. Validation must occur at the specific leaf subcommand level.

  4. FORBIDDEN Web Search Fallback: NEVER use search_web, web search, or external documentation search tools for gcloud CLI syntax. gcloud help <leaf_command> is the EXCLUSIVE authorized authority for command syntax.

  5. User Flag & Project Preservation: When proposing intermediate command steps, ALWAYS preserve all user-specified flags (including --project=<project_id>) in the proposed response text.

  6. Mandatory Plan Template: When generating a plan, the response MUST copy this exact 4-step structure:

    • Step 1: Syntax Validation via gcloud help <leaf_command>
    • Step 2: Parameter Verification (confirming required and optional flags, and explicitly checking if the --dry-run or --validate-only flag is supported)
    • Step 3: Dry-Run Command Proposal (If --dry-run or --validate-only is supported, there MUST be a --dry-run or --validate-only invocation before the next step.)
    • Step 4: Command Proposal & Authorization (If the command is on the "Prohibited Operations" denylist, state that autonomous execution is forbidden, and the user MUST be explicitly asked for authorization to proceed. If the command is NOT on the denylist, propose or proceed with execution, while following ALL "Execution Constraints" below.)

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 the current platform (Linux, macOS, Windows, etc.).

2. Authorization

Authenticate the CLI with Google Cloud. Choose the flow that matches the 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)

  • Action: ALWAYS call gcloud help <command> for the exact command that is intended to be 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 or presenting plans. Validation is not transitive from parent groups.

2. Data Reduction Strategies (Mandatory)

Minimize the volume of data returned by gcloud to save context window space and reduce latency. DO NOT execute any list command without including at least one data reduction flag (--limit, --filter, or --format).

  • Projection: Use --format="json(key1, key2, ...)" to select only the specific fields needed for the 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 the context window with redundant data. To prevent this, discover a resource's schema before executing queries. If 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.
  • Non-Interactive Execution (--quiet / -q): Pass the --quiet (or -q) global flag on all execution commands (e.g., gcloud pubsub topics delete temp-topic --quiet --project=test-project). AI agents run in headless, non-interactive environments without a TTY or stdin input handler. Without --quiet, commands that prompt for user confirmation (such as deleting resources, approving defaults, or selecting unspecified regions) will pause execution indefinitely waiting for input, causing background task timeouts. Including --quiet forces non-interactive mode, causing gcloud to automatically accept safe default choices or fail immediately with an explicit error if required parameters are missing.
  • No Blind Lists: NEVER execute a list command without --limit, --filter, or --format.

4. Project and Location Scoping (Critical)

To ensure commands are deterministic, non-interactive, and target the correct environment, they must explicitly provide 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 the location flag is omitted (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 the correct region, zone, or location for a service is not known, 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)

NEVER execute 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): If the --dry-run or --validate-only flag (or equivalent) is listed in the command help output, ALWAYS include the flag in the proposed command or initial execution step. ALWAYS preview changes with --dry-run or --validate-only prior to actual execution.

  • 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), operation status must be polled for completion, if needed for the next step.

  • Non-Interactive Flag (--quiet): Include --quiet (or -q) on all proposed or executed commands to guarantee non-interactive execution without waiting for TTY confirmation prompts.

Structured Workflows

Discovery Workflow

When asked to perform a task on a service that is unfamiliar:

  1. Invoke Help: Call gcloud help <COMMAND> on the target leaf command prior to execution.
  2. Traverse Command Tree: Run help on command groups (e.g., gcloud help compute or gcloud help) to discover available subgroups and commands if the exact command is unknown.
  3. Discover Schema: Run gcloud <GROUP> <RESOURCE> list --limit=1 --format=json to inspect JSON keys before constructing filters or projections. DO NOT execute unconstrained list commands without scoping flags (e.g., --limit=1) to prevent context window exhaustion.
  4. Enforce Data Reduction: Include data reduction flags (--limit, --filter, --format) on all command executions.

Quick Reference / Cheat Sheet

TaskCommand Template
Discover Schemagcloud <GROUP> <RESOURCE> list --limit=1 --format=json
Filtered Listgcloud <GROUP> <RESOURCE> list --filter="status:RUNNING"
Specific Columnsgcloud <GROUP> <RESOURCE> list --format="json(name, id)"
Learn Filtersgcloud topic filters
Learn Formatsgcloud topic formats
Learn Projectionsgcloud topic projections
Asynchronous Opgcloud <COMMAND> --async
Check Operationgcloud operations describe <OPERATION_ID>
Common commandsgcloud cheat-sheet
List Regions (GCE)gcloud compute regions list --project=<PROJECT_ID>
List Zones (GCE)gcloud compute zones list --project=<PROJECT_ID>
List Locationsgcloud <GROUP> locations list --project=<PROJECT_ID>

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

Frequently asked questions about Gcloud CLI Skill

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