Google Cloud Recipe Auth logo

Google Cloud Recipe Auth

OrganizationPopular
google
google-cloud-recipe-auth

Provides expert guidance on authenticating and authorizing to Google Cloud services and APIs, covering human users, service identities, Application Default Credentials (ADC), and best practices for secure access.

Overview

Publishergoogle
Repositoryskills
Skill namegoogle-cloud-recipe-auth
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 Auth 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-auth .claude/skills/google-cloud-recipe-auth
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Google Cloud Recipe Auth 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 Auth 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 Auth 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.

Authenticating to Google Cloud

Authentication is the process of proving who you are. In Google Cloud, you represent a Principal (an identity like a user or a service). This is the first step before Authorization (determining what you can do).

Authentication

Clarifying Questions for the Agent

Before providing a specific solution, clarify the following with the user:

  1. Who or what is authenticating? (A human developer, a local script, or an application running in production?)
  2. Where is the code running? (Local laptop, Compute Engine, GKE, Cloud Run, or another cloud like AWS/Azure?)
  3. What is the target? (A Google Cloud API like Storage/BigQuery, or a custom application you built?)
  4. Are you using a high-level client library? (e.g., Python, Go, Node.js libraries usually handle ADC automatically.)

Human Authentication

For users to access Google Cloud, they need an identity that Google Cloud can recognize.

Types of User Identities

Google Cloud supports several ways to configure identities for your internal workforce (developers, administrators, employees):

  • Google-Managed Accounts: You can use Cloud Identity or Google Workspace to create managed user accounts. These are called managed accounts because your organization controls their lifecycle and configuration.
  • Federation using Cloud Identity or Google Workspace: You can federate identities to allow users to use their existing identity and credentials to sign in to Google services. Users authenticate against an external identity provider (IdP), but you must keep accounts synchronized into Google Cloud using tools like Google Cloud Directory Sync (GCDS) or an external authoritative source like Active Directory or Microsoft Entra ID.
  • Workforce Identity Federation: This lets you use an external IdP to authenticate and authorize a workforce using IAM directly. Unlike standard federation, you do not need to synchronize user identities from your existing IdP to Google Cloud identities. It supports syncless, attribute-based single sign-on.

Methods of Access for Developers and Administrators

Used for interacting with Google Cloud resources and APIs during development and management.

  • Google Cloud Console: The primary web interface. You authenticate using your Google Account (Gmail or Google Workspace).
  • gcloud CLI (gcloud auth login): Used to authenticate the CLI itself so you can run management commands (e.g., gcloud compute instances list). It uses a Credential (like an OAuth 2.0 refresh token) stored locally.
  • Local Development with App Default Credentials (ADC) (gcloud auth application-default login): This is different from CLI auth. It creates a local JSON file that Google Cloud Client Libraries (Python, Java, etc.) use to act as "you" when you run code on your laptop.
  • Service Account Impersonation: For security reasons, developers should avoid downloading Service Account keys entirely. Instead, they should authenticate as humans (gcloud auth login) and use Service Account Impersonation to run CLI commands or generate short-lived credentials. This is a critical best practice for local development and troubleshooting.

For End-Users and Customers

Used when a human (who is not a developer) needs to access a web application you've deployed on Google Cloud. Note: These are distinct from workforce identities.

  • Identity-Aware Proxy (IAP): Acts as a central authorization layer for web applications. It intercepts web requests and verifies the user's identity (via Google Workspace, Cloud Identity, or external providers) before letting them reach the application. It's often used to protect internal apps without a VPN, or secure customer portals.
  • Identity Platform: A Customer Identity and Access Management (CIAM) solution for adding consumer sign-in (email/password, phone, social) directly into the code of your custom-built applications.

Service-to-Service Authentication

When code runs in production, it should use a Service Account rather than a human user account.

Service Accounts and Service Agents

  • Service Account: A special identity intended for non-human users. It's like a "robot identity" with its own email address.
  • Service Agent: A service account managed by Google that allows a service (like Pub/Sub) to access your resources on your behalf.

Best Practice: Attaching Service Accounts

Instead of using Service Account Keys (dangerous JSON files), you should attach a custom service account to the Google Cloud resource. The resource's environment then provides a Token (a short-lived digital object) via a local metadata server.

  • Compute Engine: Assign a service account during VM creation.
  • Cloud Run: Assign a service account in the service configuration.

Special Cases & Advanced Topics

Kubernetes Engine (GKE)

Use Workload Identity Federation for GKE to map Kubernetes identities to IAM principal identifiers. This grants specific Kubernetes workloads access to specific Google Cloud APIs. Learn more here.

External Workloads (Workload Identity Federation)

For code running outside Google Cloud (e.g., AWS, Azure, or on-prem), do not use keys. Instead, use Workload Identity Federation to exchange an external token (like an AWS IAM role) for a short-lived Google Cloud access token.

API Keys

API keys are encrypted strings used for public data (e.g., Google Maps) or simplified access like Vertex AI Express Mode, which allows fast testing of Gemini models without complex setup. Both humans and services (e.g., Cloud Run-based AI agent) can use API keys, for the services that support it.

Note: API keys should be restricted to specific APIs and projects to minimize security risks. Store API keys in a secrets manager like Secret Manager to prevent accidental exposure.

OAuth 2.0 Access Scopes

While IAM is the modern way to handle authorization, legacy Compute Engine VMs and GKE node pools still rely on Access Scopes alongside IAM. If a VM's scope is restricted, the attached service account will fail to make API calls even if it has the correct IAM permissions. Check this first if attached service accounts are failing unexpectedly.

Short-Lived Credentials

The underlying mechanism for impersonation and secure service-to-service communication is the IAM Service Account Credentials API. This API generates short-lived access tokens, OpenID Connect (OIDC) ID tokens, or self-signed JSON Web Tokens (JWTs) dynamically, removing the need for static credentials.


Authorization

After Authentication, Google Cloud uses Identity and Access Management (IAM) to determine what the authenticated principal can do.

  • Allow Policy: A record that binds a Principal to a Role on a Resource.
  • Predefined Roles: Prebuilt roles like roles/storage.objectViewer or roles/bigquery.dataEditor. Always try to use these first.
  • Custom Roles: User-defined collections of specific permissions if predefined roles are too broad.

Examples

Human-to-Service (Local Python Development)

  1. Authn: Run gcloud auth application-default login to create local credentials (ADC).
  2. Authz: Grant your email the roles/storage.objectViewer role on a bucket.
  3. Code: Use the Python storage.Client(). It automatically finds your local credentials via ADC. Note: ADC searches in a specific order—first checking the GOOGLE_APPLICATION_CREDENTIALS environment variable, then the local gcloud JSON file, and finally the attached service account metadata server.

Service-to-Service (Cloud Run to Cloud SQL)

  1. Authn: Attach a custom Service Account to your Cloud Run service.
  2. Authz: Grant that Service Account the roles/cloudsql.client role on the project.
  3. Code: The Cloud Run environment provides the token automatically to the connection driver.

Calling a Custom Application (OIDC)

When calling a private Cloud Run service from another service, the caller generates a Google-signed OpenID Connect (OIDC) ID Token and passes it in the Authorization: Bearer <TOKEN> header.


Validation Checklist

  • Is the user running code locally? Suggest gcloud auth application-default login or Service Account Impersonation.
  • Is the user attempting to use Service Account keys locally? Strongly discourage this and recommend impersonation.
  • Is the user running in production? Recommend attaching a custom, least-privilege service account, NOT using keys.
  • Is the user relying on the Compute Engine Default Service Account? Recommend creating a custom service account instead.
  • Is the user running on another cloud? Recommend Workload Identity Federation.
  • Is the user calling a custom app? Recommend OIDC ID Tokens.
  • Has the user restricted their API Keys? Check for appropriate API Key Restrictions.

References

Frequently asked questions

What does the Google Cloud Recipe Auth AI skill do?

Provides expert guidance on authenticating and authorizing to Google Cloud services and APIs, covering human users, service identities, Application Default Credentials (ADC), and best practices for secure access.

Why use Google Cloud Recipe Auth on TypingMind?

Because you install it once and use it with any model. Google Cloud Recipe Auth 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 Auth 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-auth. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Google Cloud Recipe Auth?

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 Auth?

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

Is the Google Cloud Recipe Auth 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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