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Cloud Build Basics

OrganizationPopular
google
cloud-build-basics

Teaches the fundamentals of Google Cloud Build (GCB). Covers core concepts, API enablement, console navigation to the Build History page, and the end-to-end workflow for creating and manually running a basic build trigger. Do not use for managing private pools or complex pipeline architectures.

Overview

Publishergoogle
Repositoryskills
Skill namecloud-build-basics
Stars
20.1K
Forks
1.6K
Bundled files
3
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.

  • 3 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

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

Installation

Install the Cloud Build Basics 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/skills/cloud/cloud-build-basics .claude/skills/cloud-build-basics
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Cloud Build Basics 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 Cloud Build Basics 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 Cloud Build Basics 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.

Google Cloud Build Basics

Prerequisites

Before starting, ensure the following prerequisites are met:

  1. Google Cloud SDK: Ensure the Google Cloud SDK is installed and configured.
  2. Authentication: Authenticate the gcloud CLI:
    bash
    gcloud auth login
    gcloud auth application-default login
  3. Project ID: Know the target Google Cloud Project ID. Set the context:
    bash
    gcloud config set project <PROJECT_ID>
  4. Enable Cloud Build API: The Cloud Build API must be enabled for the project.
    bash
    gcloud services enable cloudbuild.googleapis.com
  5. Permissions: Ensure the user or service account has the necessary permissions, such as roles/cloudbuild.builds.editor and roles/serviceusage.serviceUsageAdmin (to enable the API).

Core Concepts

Google Cloud Build (GCB) is a serverless platform that executes your builds on Google Cloud. It translates your source code into deployable artifacts, such as Docker containers or Java archives.

ConceptDescription
cloudbuild.yamlThe required configuration file that defines the build steps. It is written in YAML or JSON.
Build StepsA sequence of actions (steps) GCB performs. Each step runs a command inside a specific Docker container (the builder). Common builders include gcr.io/cloud-builders/gcloud, gcr.io/cloud-builders/docker, and custom containers.
ArtifactsThe output of the build, typically a container image pushed to Google Container Registry (GCR) or Artifact Registry (AR), or other deployable files.
TriggersAutomation rules that invoke a build in response to an event, such as a push to a Git repository, a Pub/Sub message, or a manual request.

Navigation: Viewing Build History

The Cloud Build Build History page is the central place to monitor the status of past and ongoing builds.

  1. Open the Cloud Console: Navigate to the Google Cloud Console.
  2. Go to Cloud Build: Use the search bar or the navigation menu to find Cloud Build.
  3. Select Build History: In the left navigation pane, select History (or use the direct URL: https://console.cloud.google.com/cloud-build/builds).
  4. Review Builds:
    • Status: Check the status column (SUCCESS, FAILURE, WORKING, QUEUED).
    • Region: Use the region filter at the top to view builds that ran in a specific region (important for regional worker pools).
    • Logs: Click on a specific Build ID to view the detailed logs, execution steps, and build summary. This is crucial for debugging failed builds.

[!NOTE] If this is your first time visiting the page, you might see the "zero-state" experience, which offers options to run a sample build or create your first trigger (as noted in the cb-list-build-zero-state skill). Note that region settings for triggers and builds are immutable after creation and must be chosen deliberately.

Creating a Basic Automated Trigger

This process defines an automation rule to run a build whenever code is pushed to a specified Git branch.

Step 1: Start Trigger Creation

  1. Navigate to the Cloud Build Triggers page (https://console.cloud.google.com/cloud-build/triggers).
  2. Click Create trigger.

Step 2: Configure Trigger Settings

  1. Name: Provide a unique, descriptive name (e.g., github-main-branch-build).
  2. Region: Select the region where the trigger configuration will be stored (e.g., global or a specific regional endpoint). Note: Trigger and build region settings are immutable after creation and must be chosen deliberately.
  3. Event: Select the event type. For automated CI/CD, select Push to a branch.
  4. Source: Select the repository source:
    • Repository: Connect your source repository (GitHub, Bitbucket, Cloud Source Repositories, etc.). If needed, authorize the connection.
    • Repository Name: Select the specific repository you want to link.
  5. Branch: Enter the branch pattern (e.g., ^main$ or ^develop).

Step 3: Configure Build Settings

  1. Configuration: Select Cloud Build configuration file (yaml or json).
  2. Location: Keep the default Repository and specify the path to your build configuration file (e.g., cloudbuild.yaml).
    • Alternative: For very simple builds, you can choose Inline to paste the YAML configuration directly into the trigger.
  3. (Optional) Service Account: For production environments, select a dedicated service account with limited permissions to enforce the principle of least privilege.

Step 4: Save and Test

  1. Click Create. The trigger is now active and will run automatically on the next matching Git push.

[!TIP] The cb-create-trigger skill provides detailed gcloud commands for creating triggers across all types (GitHub, Pub/Sub, Webhook) and configurations (inline, Dockerfile, YAML). Use that skill for CLI automation.

Running an Existing Trigger Manually

Sometimes you need to run a trigger on demand, outside of its normal automation flow (e.g., to rebuild an old commit or test a new substitution).

[!IMPORTANT] Substitution Immutability: You can only override values for substitution variables that are already defined in the trigger configuration. You cannot introduce new substitution variable keys at runtime.

Option A: Via the Cloud Console

  1. Navigate to the Cloud Build Triggers page (https://console.cloud.google.com/cloud-build/triggers).
  2. Locate the trigger you wish to run.
  3. Click the vertical ellipsis (⋮) next to the trigger and select Run.
  4. A dialog will appear, allowing you to specify:
    • Source branch/tag: Choose the specific Git reference to build from.
    • Substitution Variables: Override any existing substitution variables (e.g., set _VERSION to a new value).
  5. Click Run trigger. The build will start immediately, and you can monitor its status on the History page.

Option B: Via the gcloud CLI

Use the gcloud builds triggers run command to invoke the trigger and optionally override parameters.

bash
# Run the trigger against the 'main' branch
gcloud builds triggers run <TRIGGER_NAME> \
    --region=<REGION> \
    --branch=main

# Run the trigger and override a substitution variable
gcloud builds triggers run <TRIGGER_NAME> \
    --region=<REGION> \
    --branch=main \
    --substitutions=_IMAGE_TAG="20231027-manual"

# Monitor the initiated build
# Note: The run command outputs the build ID. Use it to check status:
# gcloud builds log <BUILD_ID> --region=<REGION>

[!NOTE] The cb-run-trigger skill provides more complex invocation examples, including running against a specific commit SHA or using tags.

Related Skills

  • cb-create-trigger: Detailed CLI-focused instructions for creating all trigger types.
  • cb-list-build-zero-state: Advanced management of the Cloud Build dashboard and onboarding zero state.
  • cb-run-trigger: Comprehensive guide to manually running triggers using various gcloud options.

External Resources & Documentation

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Cloud Build Basics AI skill do?

Teaches the fundamentals of Google Cloud Build (GCB). Covers core concepts, API enablement, console navigation to the Build History page, and the end-to-end workflow for creating and manually running a basic build trigger. Do not use for managing private pools or complex pipeline architectures.

Why use Cloud Build Basics on TypingMind?

Because you install it once and use it with any model. Cloud Build Basics 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 Cloud Build Basics in TypingMind?

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

Which AI models can use Cloud Build Basics?

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 Cloud Build Basics?

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

Is the Cloud Build Basics 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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