Google Cloud Recipe Onboarding logo

Google Cloud Recipe Onboarding

OrganizationPopular
google
google-cloud-recipe-onboarding

Guides a developer's first steps on Google Cloud, covering account creation, billing setup, project management, and deploying a first resource. Use when a new developer wants to initialize their first Google Cloud project, configure billing, and verify deployment. Don't use for enterprise organization setup (use Google Cloud Setup guided flow for that instead). Don't use for complex multi-project architectures.

Overview

Publishergoogle
Repositoryskills
Skill namegoogle-cloud-recipe-onboarding
Stars
20.1K
Forks
1.6K
Bundled files
Instructions only
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by google on GitHub. Read the source before you install it.

Installation

Install the Google Cloud Recipe Onboarding AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/google/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/plugins/cloud/google-cloud-developer/skills/google-cloud-recipe-onboarding .claude/skills/google-cloud-recipe-onboarding
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Google Cloud Recipe Onboarding in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Google Cloud Recipe Onboarding on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Google Cloud Recipe Onboarding is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Onboarding to Google Cloud

This skill provides a streamlined, non-interactive "happy path" for a singleton developer to get started with Google Cloud. It covers everything from environment verification and authentication to project selection, billing account linkage, and downstream safety chaining.

[!IMPORTANT] For autonomous agents executing this skill:

  1. Check-Before-Mutate Audits: Always perform silent pre-execution state audits prior to proposing or executing any project or billing changes.
  2. Single-Question Policy: Ask the user for exactly one operational parameter or confirmation at a time during interactive execution.
  3. Non-Interactive Output: Append non-interactive overrides (--quiet, --format="json") to all mutation commands to guarantee deterministic, machine-parseable outputs and prevent terminal hangs.
  4. First Turn Interaction Rules (Trigger Turn): When the developer first triggers this skill with a general onboarding request (e.g. says "I want to get started with Google Cloud"):
    • Preamble Guidance: Proactively include a short orienting preamble guiding the developer to create a Google Cloud account (pointing to the console at https://console.cloud.google.com/) and run gcloud auth login to authorize their workstation, even if they appear to be already logged in.
    • First Turn Single-Question: Perform pre-flight audits silently, but do not present a complete parameters summary table or ask for final consent in the first turn. Instead, ask the developer exactly one initial operational question (e.g., "Would you like to reuse an existing active project, or create a brand new one?"). Note: If the developer's initial prompt explicitly states "I approve the onboarding configuration", "Let's proceed with onboarding", or requests a dry-run plan (e.g., "Show me the exact plan or dry-run commands"), bypass the general preamble and initial question, and proceed directly to the requested step.

Overview

For an individual developer, onboarding to Google Cloud involves verifying local terminal tools, establishing an authenticated session, selecting or instantiating a workspace (Project), and linking it to an active billing account. Google Cloud offers a Free Tier and a Free Trial with $300 in credits for first-time users. Learn more here.


Prerequisites

  • A personal Google Account (e.g., @gmail.com) or Google Workspace / Cloud Identity account.
  • A valid payment method (credit card or bank account) required for identity verification and to activate the $300 Free Trial credit introduced in the Overview.

Steps

Section 1: Verify Host Tooling Setup

Before soliciting input or proposing mutations, silently audit the host system's active tooling and environment status.

  1. Check if the gcloud CLI binary is installed and accessible:

    bash
    which gcloud
  2. Check if there is an active authenticated identity session:

    bash
    gcloud auth list --format="json"
  3. If the pre-execution audit for which gcloud returns a valid path, proceed directly to Section 2: Authenticate and Route Session.

  4. If the binary is missing, halt execution and direct the agent to install gcloud using the gcloud skill. Provide the official Google Cloud CLI Installation Guide to the developer for steps to set up authentication.


Section 2: Authenticate and Route Session

Authorize the gcloud CLI to access Google Cloud using the developer's Google Account, and verify that the account is appropriate for standalone developer onboarding.

  1. Execute Credentials Authentication:

    bash
    gcloud auth login

    [!IMPORTANT] New User / Unauthenticated Guidance: If the pre-execution state audits or command failures confirm that the developer is unauthenticated (e.g., gcloud auth list is empty or active credentials are missing):

    1. Guide them to create a Google Cloud account by navigating to the Google Cloud Console.
    2. Instruct them to execute the gcloud auth login command to authorize their local workstation terminal session.
    3. Do not attempt project creation or resource configuration until authentication is completed successfully.
  2. Verify Active Identity:

    bash
    gcloud config get-value account --format="json"
  3. Programmatic Enterprise Routing Guardrail: Before proceeding, verify if the account is bound to a corporate organization, as enterprise setups must follow a different architecture:

    bash
    gcloud organizations list --format="json"
    • Note that new Free Trial accounts automatically receive a Self-Owned Organization (SOO). To distinguish between a personal Free Trial account and an enterprise organization, inspect the JSON output:
      • Enterprise Organization (Halt Execution): If the output list contains an organization node where owner.directoryCustomerId is present (confirming a domain-verified Google Workspace or Cloud Identity organization), or if the user's prompt explicitly mentions corporate landing zones or multi-tenant project structures:
      • Personal Account / Free Trial SOO (Proceed): If the output list is empty [], or if it contains a Self-Owned Organization (where owner.directoryCustomerId is absent and displayName is not a verified domain name), proceed to Section 3: Select or Instantiate Your Google Cloud Project.

Section 3: Select or Instantiate Your Google Cloud Project

Google Cloud resources are organized into Projects. When developers sign up for a Free Trial via the console, Google Cloud automatically creates a default project (e.g., "My First Project"). Always audit the active environment first to reuse existing projects and prevent token-burning collision errors.

  1. Silent Project Discovery: List active, accessible projects (limited to prevent context window overflow):

    bash
    gcloud projects list --filter="lifecycleState=ACTIVE" --limit=20 --format="json"
  2. Reuse Existing Project (Recommended): If the list returns an active project, present it to the developer and propose setting it as the default working project:

    bash
    gcloud config set project {PROJECT_ID} --quiet
  3. Create Custom Project: If no projects exist, or if the developer explicitly requests a brand new workspace:

    • Solicit a custom PROJECT_ID and PROJECT_NAME from the developer (Single-Question Policy).

    • Structured Confirmation & Consent Gate (Mandatory): Before running any project creation or billing linkage commands, the agent must present a structured markdown table summarizing the target parameters:

      ParameterValue
      Target Project ID{PROJECT_ID}
      Target Project Name{PROJECT_NAME}
      Active Identity Account{ACCOUNT}
      Target Billing Account ID{BILLING_ACCOUNT_ID}

      Ask the user the exact consent query: "I am ready to initialize your Google Cloud project and link billing. Do you want me to proceed?"

      CRITICAL: The agent MUST NOT execute any gcloud projects create or billing link commands during this turn. You must display this table, ask the exact consent query, and strictly stop to wait for the user's positive affirmation.

    • Project ID Collision Suffix Recovery: If the project creation command fails because the PROJECT_ID is already taken globally (returning a PROJECT_ID_COLLISION or ALREADY_EXISTS error):

      • Automatically append a random 4-digit suffix (e.g., changing my-project to my-project-8472).
      • Propose this new available project ID to the developer and re-solicit consent before retrying.
    • Execute Project Creation: Once explicit user consent is confirmed:

      bash
      gcloud projects create {PROJECT_ID} --name="{PROJECT_NAME}" --quiet --format="json"
    • Set the active working project:

      bash
      gcloud config set project {PROJECT_ID} --quiet

Section 4: Verify and Link Billing

To deploy resources on Google Cloud, your project must be linked to an active Cloud Billing account.

  1. Audit Billing Status: Check if the active project is already linked to a billing account:

    bash
    gcloud billing projects describe {PROJECT_ID} --format="json"
  2. If the output contains "billingEnabled": true, skip linkage and proceed immediately to Section 5: Skill Chaining (Spend Controls & Workloads).

  3. Discover Available Billing Accounts: If the project is unlinked, query the available billing account handles linked to the authenticated user identity:

    bash
    gcloud billing accounts list --format="json"
  4. Link Billing Account: Propose linking the project to the discovered Billing Account ID, and execute:

    bash
    gcloud billing projects link {PROJECT_ID} --billing-account={BILLING_ACCOUNT_ID} --format="json"

Section 5: Skill Chaining (Spend Controls & Workloads)

Onboarding setup is now complete. To safeguard your environment and deploy workloads, you can chain to downstream specialized skills:

  1. Billing Spend Controls: To avoid accidental cost overruns, consider setting up a programmatic control to automatically disable billing. When billing is disabled, all Google Cloud services and usage in the project are terminated to stop further costs:
  1. Deploy Workloads: To deploy your first resource, trigger the downstream specialized skill matching your target application (e.g., cloud-run-basics or bigquery-basics). If the specialized skill is not locally available, direct the developer to the corresponding official quickstart, such as the Cloud Run Container Deployment Quickstart. Note: Those downstream specialized skills are individually responsible for dynamically enabling their own required service APIs (e.g., run.googleapis.com) inline during execution.

Validation Logic

After completing the onboarding steps, programmatically verify the completed environment state using these diagnostic commands:

  1. Verify CLI Installation:

    bash
    which gcloud
  2. Verify Authenticated Identity:

    bash
    gcloud config get-value account
  3. Verify Project Workspace Existence:

    bash
    gcloud projects describe {PROJECT_ID} --format="json"
  4. Verify Billing Linkage (Ensure the JSON output contains "billingEnabled": true):

    bash
    gcloud billing projects describe {PROJECT_ID} --format="json"

Additional Resources

Frequently asked questions

What does the Google Cloud Recipe Onboarding AI skill do?

Guides a developer's first steps on Google Cloud, covering account creation, billing setup, project management, and deploying a first resource. Use when a new developer wants to initialize their first Google Cloud project, configure billing, and verify deployment. Don't use for enterprise organization setup (use Google Cloud Setup guided flow for that instead). Don't use for complex multi-project architectures.

Why use Google Cloud Recipe Onboarding on TypingMind?

Because you install it once and use it with any model. Google Cloud Recipe Onboarding is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Google Cloud Recipe Onboarding in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/google/skills/tree/main/plugins/cloud/google-cloud-developer/skills/google-cloud-recipe-onboarding. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Google Cloud Recipe Onboarding?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Google Cloud Recipe Onboarding?

As many as you like. As long as a model supports skills, you can use Google Cloud Recipe Onboarding with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Google Cloud Recipe Onboarding AI skill free?

Yes. It is published on GitHub by google under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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