Generate production-ready Google Cloud code examples from official repositories including ADK samples, Genkit templates, Vertex AI notebooks, and Gemini patterns.

MITAuto-check passedDevOps & Cloud

Install GCP Examples Expert

skills CLI
$ npx skills add jeremylongshore/tons-of-skills-marketplace --skill gcp-examples-expert -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install jeremylongshore/tons-of-skills-marketplace gcp-examples-expert --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/jeremylongshore/tons-of-skills-marketplace.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/.curated/gcp-examples-expert .claude/skills/gcp-examples-expert && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
gcp-examples-expert
GitHub stars
2.8k
Token cost
~1.6k tokens
SKILL.md length
633 words
Files
10 (incl. scripts, references)
Skills in repo
3,342
Repo updated
First seen
Licence
MIT

At a glance

Generate production-ready Google Cloud code examples from official repositories including ADK samples, Genkit templates, Vertex AI notebooks, and Gemini patterns.

  • Works in 10 steps: Identify the target framework by… → Select the appropriate source repository… → Adapt the template to the specified… → …
  • Asked to show ADK example
  • SKILL.md covers Overview, Prerequisites, Instructions and Output, plus 3 more sections
  • Runs Shell scripts from its folder; calls gcloud and npm

What it does

GCP Examples Expert is an agent skill from jeremylongshore/tons-of-skills-marketplace. Generate production-ready Google Cloud code examples from official repositories including ADK samples, Genkit templates, Vertex AI notebooks, and Gemini patterns. Use when asked to "show ADK example" or "provide GCP starter kit". Trigger with relevant phrases based on skill purpose.

Its SKILL.md is about 1.6k tokens, which your agent loads only when the skill is triggered. The skill folder holds 11 other files, including scripts and reference files (for example `references/ARD.md`, `references/PRD.md` and `references/best-practices-applied.md`). Compatibility notes: Designed for Claude Code

It sits in DevOps & Cloud, covering Project scaffolding. It works with Google Cloud, Vertex AI and Firebase. The repository describes itself as: Model-agnostic agent-skills platform with a harness-free canonical layer, verified adapters, and the ccpi package manager. Explore at tonsofskills.com. The licence is MIT.

When your agent uses it

  • Asked to show ADK example
  • Provide GCP starter kit
  • With relevant phrases based on skill purpose

Example prompts

  • “show ADK example”
  • “provide GCP starter kit”
  • “/gcp-examples-expert”

Requirements

  • Python 3
  • Node.js
  • A Bash shell
  • Compatibility (from SKILL.md): Designed for Claude Code
  • Pre-approved tools (allowed-tools): Read, Write, Edit, Grep, Glob, Bash(cmd:*)

Workflow steps

10 steps, taken from the first numbered list in SKILL.md.

  1. Identify the target framework by matching the request to one of six categories: ADK agents, Agent Starter Pack, Genkit flows, Vertex AI…
  2. Select the appropriate source repository and code pattern from ${CLAUDE_SKILL_DIR}/references/code-example-categories.md
  3. Adapt the template to the specified programming language (TypeScript, Python, or Go)
  4. Configure security settings: IAM least-privilege service accounts, VPC Service Controls, Model Armor for prompt injection protection
  5. Add monitoring instrumentation: Cloud Monitoring dashboards, alerting policies, structured logging, OpenTelemetry tracing
  6. Set auto-scaling parameters with appropriate min/max instance counts for the deployment target
  7. Include cost optimization: select Gemini 2.5 Flash for simple tasks, Gemini 2.5 Pro for complex reasoning, batch predictions for bulk…
  8. Generate deployment configuration for the target platform (Cloud Run, Firebase Functions, or Vertex AI Endpoints)
  9. Provide Terraform or IaC templates for reproducible infrastructure provisioning
  10. Cite the source repository and link to official documentation for each pattern used

What it can do on your machine

Read from SKILL.md and the folder at commit cfae287. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Write
    • Edit
    • Grep
    • Glob
    • Bash(cmd:*)

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/ (Shell), which the agent can run.

    Shell commands in SKILL.md call:

    • gcloud
    • npm

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • github.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

  • Compatibility

    Designed for Claude Code

    From compatibility in the SKILL.md frontmatter.

Context cost

GCP Examples Expert loads about 1.6k tokens when it runs, and up to ~10k if it reads all its reference files. Until then it costs about 76 tokens; SKILL.md has 633 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~76
When it runs · the whole SKILL.md, loaded when a task matches
~1.6k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~10k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from jeremylongshore/tons-of-skills-marketplace at commit cfae287, republished under its MIT licence (© jeremylongshore). 633 words, ~1,551 tokens.

Download SKILL.mdSave it as .claude/skills/gcp-examples-expert/SKILL.md (or your agent's skills folder). This skill also uses 9 other files; get the full folder from GitHub.
name
gcp-examples-expert
description
Generate production-ready Google Cloud code examples from official repositories including ADK samples, Genkit templates, Vertex AI notebooks, and Gemini patterns. Use when asked to "show ADK example" or "provide GCP starter kit". Trigger with relevant phrases based on skill purpose.
allowed-tools
Read, Write, Edit, Grep, Glob, Bash(cmd:*)
compatibility
Designed for Claude Code
version
2.25.0
author
Jeremy Longshore <jeremy@intentsolutions.io>
license
MIT
effort
medium
argument-hint
[framework or use-case]
tags
ai, gcp, gcp-examples

GCP Examples Expert

Overview

Generate production-ready Google Cloud Platform code examples sourced from official repositories including ADK samples, Agent Starter Pack, Firebase Genkit, Vertex AI samples, Generative AI examples, and AgentSmithy. This skill maps user requirements to the appropriate GCP framework and delivers working code with security, monitoring, and deployment best practices baked in.

Prerequisites

  • Google Cloud project with billing enabled and Vertex AI API activated
  • gcloud CLI authenticated with appropriate IAM roles (Vertex AI User, Cloud Run Developer)
  • Node.js 18+ for Genkit/TypeScript examples or Python 3.10+ for ADK/Vertex AI examples
  • Firebase CLI for Genkit deployments (npm install -g firebase-tools)
  • API keys or service account credentials configured via Secret Manager (never hardcoded)

Instructions

  1. Identify the target framework by matching the request to one of six categories: ADK agents, Agent Starter Pack, Genkit flows, Vertex AI training, Generative AI multimodal, or AgentSmithy orchestration
  2. Select the appropriate source repository and code pattern from ${CLAUDE_SKILL_DIR}/references/code-example-categories.md
  3. Adapt the template to the specified programming language (TypeScript, Python, or Go)
  4. Configure security settings: IAM least-privilege service accounts, VPC Service Controls, Model Armor for prompt injection protection
  5. Add monitoring instrumentation: Cloud Monitoring dashboards, alerting policies, structured logging, OpenTelemetry tracing
  6. Set auto-scaling parameters with appropriate min/max instance counts for the deployment target
  7. Include cost optimization: select Gemini 2.5 Flash for simple tasks, Gemini 2.5 Pro for complex reasoning, batch predictions for bulk workloads
  8. Generate deployment configuration for the target platform (Cloud Run, Firebase Functions, or Vertex AI Endpoints)
  9. Provide Terraform or IaC templates for reproducible infrastructure provisioning
  10. Cite the source repository and link to official documentation for each pattern used

See ${CLAUDE_SKILL_DIR}/references/workflow.md for the phased workflow and ${CLAUDE_SKILL_DIR}/references/best-practices-applied.md for the full best-practices checklist.

Output

  • Complete, runnable code example with imports, configuration, and error handling
  • Deployment configuration (Cloud Run service YAML, Firebase function config, or Terraform module)
  • Environment variable template listing required secrets and API keys
  • Monitoring setup: dashboard JSON, alerting policy definitions, log-based metrics
  • Cost estimate guidance based on model selection and expected throughput
  • Source repository citation and documentation links
Show full SKILL.md (291 more words)Show less

Error Handling

ErrorCauseSolution
Invalid GCP project or API not enabledVertex AI API disabled or project ID misconfiguredRun gcloud services enable aiplatform.googleapis.com; verify project ID in gcloud config list
Permission denied on Vertex AI resourcesService account missing required IAM rolesGrant roles/aiplatform.user and roles/run.developer; check VPC-SC perimeter allows access
Model not available in regionRequested Gemini model not deployed in specified locationUse us-central1 or europe-west4 where Gemini models are available; check regional availability docs
Quota exceeded for API callsRate limit hit on Vertex AI prediction endpointRequest quota increase via Cloud Console; implement exponential backoff with jitter
Dependency version conflictIncompatible versions of AI SDK, Genkit, or provider packagesPin versions in package.json or requirements.txt; use lockfile to ensure reproducibility

See ${CLAUDE_SKILL_DIR}/references/errors.md for additional error scenarios.

Examples

Scenario 1: ADK Agent with Code Execution -- Create a production ADK agent using google/adk-samples patterns. Enable Code Execution Sandbox with 14-day state TTL, configure Memory Bank for persistent context, apply VPC Service Controls and IAM least-privilege. Deploy to Vertex AI Agent Engine.

Scenario 2: Genkit RAG Flow -- Implement a retrieval-augmented generation system using Firebase Genkit. Define a retriever with text-embedding-gecko embeddings, connect to a vector database, build a RAG flow with Zod-validated input/output schemas. Deploy to Cloud Run with auto-scaling (2-10 instances).

Scenario 3: Gemini Multimodal Analysis -- Analyze video content using the generative-ai repository patterns. Create a multimodal prompt combining video URIs with text questions using Gemini 2.5 Pro. Include safety filter configuration, token counting for cost estimation, and structured output parsing.

See ${CLAUDE_SKILL_DIR}/references/example-interactions.md for detailed interaction examples.

Resources

© jeremylongshore, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 9 other files (scripts, references) in skills/.curated/gcp-examples-expert of jeremylongshore/tons-of-skills-marketplace.

  • SKILL.md
  • references/ARD.md
  • references/PRD.md
  • references/best-practices-applied.md
  • references/code-example-categories.md
  • references/errors.md
  • references/example-interactions.md
  • references/examples.md
  • references/workflow.md
  • scripts/create-example.sh

Open the folder on GitHubat commit cfae287

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Google Cloud Filestore Log Troubleshootinggoogle/skills21k—~2.9kAutomated safety check: PassApache-2.0
Architect For Startupsaws/agent-toolkit-for-aws2.8k—~3.7kAutomated safety check: PassApache-2.0
Gcloudsundial-org/awesome-openclaw-skills663—~3kAutomated safety check: PassNone
Agent Platform Alert Configurationgoogle/skills21k—~4.2kAutomated safety check: PassApache-2.0

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Categories

Questions about GCP Examples Expert

What does GCP Examples Expert do?

Generate production-ready Google Cloud code examples from official repositories including ADK samples, Genkit templates, Vertex AI notebooks, and Gemini patterns. GCP Examples Expert is an agent skill from jeremylongshore/tons-of-skills-marketplace. Generate production-ready Google Cloud code examples from official repositories including ADK samples, Genkit templates, Vertex AI notebooks, and Gemini patterns.

When should I use GCP Examples Expert?

GCP Examples Expert fits situations like: asked to show ADK example; provide GCP starter kit; with relevant phrases based on skill purpose.

How do I install GCP Examples Expert in Claude Code?

Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill gcp-examples-expert -a claude-code`. Or copy the skill folder (skills/.curated/gcp-examples-expert in jeremylongshore/tons-of-skills-marketplace) into .claude/skills/gcp-examples-expert in your project. Claude Code loads it when a task matches its description.

How do I install GCP Examples Expert in Codex?

Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill gcp-examples-expert -a codex`. Or copy the skill folder (skills/.curated/gcp-examples-expert in jeremylongshore/tons-of-skills-marketplace) into .agents/skills/gcp-examples-expert in your project. Codex loads it when a task matches its description.

Can I use GCP Examples Expert in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill gcp-examples-expert -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/gcp-examples-expert, .gemini/skills/gcp-examples-expert, .github/skills/gcp-examples-expert and .opencode/skills/gcp-examples-expert in your project.

What does GCP Examples Expert need to run?

Going by SKILL.md and its folder, GCP Examples Expert needs a shell for the scripts in its folder and the command-line tools its instructions call (gcloud and npm). Our summary lists: Python 3; Node.js; A Bash shell. Its frontmatter pre-approves these tools: Read, Write, Edit, Grep, Glob, Bash(cmd:*). Compatibility (from SKILL.md): Designed for Claude Code.

Does GCP Examples Expert access the network?

SKILL.md names 1 domain. As links in the text: github.com. This is read from the text; nothing was executed.

Is GCP Examples Expert safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does GCP Examples Expert use?

GCP Examples Expert is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does GCP Examples Expert use?

About 1.6k tokens (SKILL.md is roughly 6.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 8.8k tokens, read only when the agent opens those files.

What are the alternatives to GCP Examples Expert?

Skills that share tags, products or a category with GCP Examples Expert: Google Agents CLI Scaffold (pifferologo/cloud-agents-cli, 129 stars), Google Cloud Filestore Log Troubleshooting (google/skills, 21k stars), Architect For Startups (aws/agent-toolkit-for-aws, 2.8k stars) and Gcloud (sundial-org/awesome-openclaw-skills, 663 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains GCP Examples Expert?

jeremylongshore (a GitHub user) maintains it in jeremylongshore/tons-of-skills-marketplace, which has 2,827 GitHub stars. The repository holds 3,342 skills in this directory. The repository was last updated on October 10, 2026.

Source: jeremylongshore/tons-of-skills-marketplace on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.