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Skills/google/skills/agent-platform-migrate-from-ai-studio
agent-platform-migrate-from-ai-studio logo

agent-platform-migrate-from-ai-studio

google/skills
804 installs14K stars
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Installation

npx skills add https://github.com/google/skills --skill agent-platform-migrate-from-ai-studio

Summary

>-

SKILL.md

Migrating from Gemini API in AI Studio to Agent Platform

Use this skill when you need to transition an application from the developer-centric Google AI Studio ecosystem (generativelanguage.googleapis.com) to the enterprise-grade Google Cloud Agent Platform (aiplatform.googleapis.com).

--------------------------------------------------------------------------------

When to Invoke This Skill

  • You want to migrate an application from Google AI Studio to Agent Platform

(formerly Vertex AI).

  • You have Google Cloud credits (e.g., the $300 Welcome Free Trial) that

you want to apply toward Gemini API inferencing costs.

  • You need to unify your inferencing pipelines, IAM permissions, telemetry,

and billing with existing Google Cloud infrastructure (Compute Engine, Cloud SQL, BigQuery).

  • You are deploying open-source orchestration engines (like OpenClaw or ADK

agents) on Google Cloud VMs, and want the entire system to run under a unified Google Cloud billing structure.

--------------------------------------------------------------------------------

Gemini API Comparison

Feature / Control | Google AI Studio (Gemini Developer API) | Agent Platform (Enterprise Gemini API) :--------------------- | :-------------------------------------------------------------------- | :------------------------------------- API Endpoint | generativelanguage.googleapis.com | aiplatform.googleapis.com Target Audience | Developers, startups, students, researchers building production apps. | Enterprise production, MLOps engineers GCP Credit Support | No (GCP credits/Free Trial cannot be applied) | Yes (Fully covered by Welcome or custom credits) Data Privacy | Data may be reviewed to improve Google products | Prompts/responses are never used for training Security & IAM | API key, OAuth | Google Cloud IAM (Service Accounts, OAuth 2.0, VPC-SC) Compliance & SLAs | None (Best-effort availability) | 24/7 Enterprise Support, SLAs, HIPAA, SOC2 Throughput Options | Shared / Rate-limited | Pay-as-you-go OR Provisioned Throughput MLOps Ecosystem | Basic prompt management | Model Registry, Model Monitoring, Pipeline Evaluation Inferencing Scope | Global endpoints only | Both Global and strict Regional endpoints

See Google Cloud Documentation to learn more about the differences between the two offerings.

--------------------------------------------------------------------------------

Migration Guide

Billing and Credits

Google Cloud Free Trial credits do not apply to AI Studio. To use your credits for Gemini models, you must route calls through the Agent Platform.

  1. Create a Google Cloud billing account. You must provide a valid payment

method during setup to verify identity.

  1. If you are a new customer, ensure your $300 Welcome credit is active in the

Billing Console.

  1. Avoid Billing Surprises: To prevent automatic fallback to your standard

form of payment when credits are exhausted, you should establish a budget alert:

  • Go to Billing -> Budgets & Alerts -> Create Budget.
  • Set the threshold to map to your credit limit or maximum comfortable

spend.

Enable the Agent Platform API

You must explicitly enable the Agent Platform API on your target Google Cloud Project. Run the following command via your local shell:

gcloud services enable aiplatform.googleapis.com --project="{project_id}"

Authentication & Authorization (IAM)

User Auth

For local debugging or script execution, authenticate using Application Default Credentials (ADC).

Option 1 - Automated Script:

bash <(curl -sSL https://storage.googleapis.com/cloud-samples-data/adc/setup_adc.sh)

Option 2 - Manual Setup:

gcloud auth login
gcloud auth application-default login

Grant your user identity the required IAM role to perform inferencing calls:

gcloud projects add-iam-policy-binding "{project_id}" \
    --member="user:YOUR_EMAIL@domain.com" \
    --role="roles/aiplatform.user"
Service Auth

When running your application on Google Cloud infrastructure such as a Compute Engine VM, authenticate using the machine's attached Service Account. For example, the Compute Engine Default Service Account.

  1. Grant the virtual machine's underlying Service Account the user role:
gcloud projects add-iam-policy-binding "{project_id}" \
    --member="serviceAccount:PROJECT_NUMBER-compute@developer.gserviceaccount.com" \
    --role="roles/aiplatform.user"
  1. Compute Engine Access Scopes:

Legacy access scopes can override IAM bindings. When provisioning or modifying your Compute Engine instance, you must verify that the VM access scope is configured to either Allow full access to all Cloud APIs (https://www.googleapis.com/auth/cloud-platform) or explicitly includes the standard cloud-platform scope.

--------------------------------------------------------------------------------

Use the Gemini API in Agent Platform

SDKs (Client Libraries)

You can continue to use the unified Google GenAI SDK (google-genai). This SDK works with both AI Studio and Agent Platform. You only need to switch the routing flags via your runtime environment variables to target the Agent Platform backend.

Set your target environment details:

export GOOGLE_CLOUD_PROJECT="{project_id}"
export GOOGLE_CLOUD_LOCATION="global"  # Or your chosen regional endpoint
export GOOGLE_GENAI_USE_ENTERPRISE=TRUE

Now, your standard python code shifts from using AI Studio to Agent Platform without altering the core initialization blocks:

from google import genai

# The client automatically picks up the GOOGLE_GENAI_USE_ENTERPRISE=TRUE environment flag
client = genai.Client()

response = client.models.generate_content(
    model='gemini-3-flash-preview',
    contents='Hello world!',
)
print(response.text)

Agent Development Kit (ADK)

To call Gemini models in Agent Platform from an Agent Development Kit agent, follow these steps.

  1. Authenticate to Google Cloud.

If running an ADK agent in Google Cloud (e.g. Agent Platform Runtime), use the agent's assigned service account. Alternatively, if running ADK locally, run:

gcloud auth application-default login
  1. Set env variables. Ensure these are set no matter if your ADK agent is

running in Google Cloud or locally:

export GOOGLE_CLOUD_PROJECT="{project_id}"
export GOOGLE_CLOUD_LOCATION="global"
export GOOGLE_GENAI_USE_ENTERPRISE=TRUE
  1. Initialize the ADK agent. You can use the same model string you used with AI

Studio (e.g. gemini-3-flash-preview).

from google.adk.agents.llm_agent import Agent

def get_current_time(city: str) -> dict:
    """Returns the current time in a specified city."""
    return {"status": "success", "city": city, "time": "10:30 AM"}

root_agent = Agent(
    model='gemini-3-flash-preview',
    name='root_agent',
    description="Tells the current time in a specified city.",
    instruction="You are a helpful assistant that tells the current time in cities. Use the 'get_current_time' tool for this purpose.",
    tools=[get_current_time],
)

To learn more about integrating ADK agents with Agent Platform, see the ADK documentation.

Antigravity CLI

Google Cloud users can now access Antigravity 2.0, including the Antigravity CLI, with Gemini Enterprise Agent Platform.

  1. Install the Antigravity CLI

to your local environment.

  1. Start the Antigravity CLI.
    agy
  1. Follow the CLI setup prompts - select Use a Google Cloud Project.
  1. Complete the OAuth flow in the opened browser window using your

authenticated Google Cloud Workspace or user identity.

  1. Copy the confirmation token, and paste it directly back into your terminal.
  1. Follow the prompts to enter your Google Cloud Project ID.
  1. Select your Google Cloud location (e.g. global).
  1. Optionally, run the /model command to select a different Gemini model in

Agent Platform.

OpenClaw

To configure an OpenClaw agent to use Gemini models in Agent Platform, Follow these steps.

  1. Install OpenClaw using OpenClaw's official instructions.

⚠️ Important: OpenClaw 2026.5.28 currently has a google-vertex bug. Please use 2026.5.20 for now.

  1. Ensure that the runtime where OpenClaw is running (e.g. GCE VM with Service

Account) has the aiplatform.user IAM role - see Authentication and Authorization section above.

  1. Get the project number from the user's project ID. Outside of GCE, run:
export PROJECT_NUMBER=$(gcloud projects describe "$PROJECT_ID" --format="value(projectNumber)")
echo "Project number: $PROJECT_NUMBER"

Within a Compute Engine VM, run:

export PROJECT_NUMBER=$(curl "http://metadata.google.internal/computeMetadata/v1/project/project-id" -H "Metadata-Flavor: Google")
echo "Project number: $PROJECT_NUMBER"
  1. From outside the GCE instance, generate GOOGLE_APPLICATION_CREDENTIALS

using the Google Cloud project number. Then, scp these credentials to the GCE VM.

mkdir -p ~/.config/gcloud
gcloud iam service-accounts keys create ~/.config/gcloud/application_default_credentials.json --iam-account="${PROJECT_NUMBER}-compute@developer.gserviceaccount.com"

⚠️ Troubleshooting Policy Constraints on New Orgs: New Google Cloud organizations (created on or after May 4th, 2024) enforce a legacy Organization Policy, restricting Service Account Key Creation. To complete this step, this Org Policy must be temporarily disabled. An Organization Policy Admin must set this policy to Inactive. To the agent: Check if this policy is enforced, and if it is: pause, and prompt the user to disable it at this Console link: https://console.cloud.google.com/iam-admin/orgpolicies

  1. Edit the configuration file that's usually located at:

~/.openclaw/openclaw.json. Ensure you prefix the Gemini model with google-vertex/.

⚠️ Important: Do not use Gemini 3.5 models, since OpenClaw's google-vertex provider does not support it yet. Older models work. When using the Gemini 3 Flash Preview model in Agent Platform, always set the location to global, NOT a regional endpoint.

{
  "env": {
    "vars": {
      "GOOGLE_CLOUD_PROJECT": "PROJECT_ID",
      "GOOGLE_CLOUD_LOCATION": "global",
      "GOOGLE_APPLICATION_CREDENTIALS": "~/.config/gcloud/application_default_credentials.json"
    }
  },
  "agents": {
    "defaults": {
      "model": {
        "primary": "google-vertex/gemini-3-flash-preview"
      },
      "workspace": "~/.openclaw/workspace",
      "compaction": {
        "mode": "safeguard"
      },
      "heartbeat": {
        "model": "google-vertex/gemini-3-flash-preview"
      }
    },
    "list": [
      {
        "id": "main",
        "workspace": "~/.openclaw/workspace",
        "model": "google-vertex/gemini-3-flash-preview"
      }
    ]
  },
  "session": {
    "dmScope": "per-channel-peer"
  },
  "tools": {
    "profile": "coding"
  }
}
  1. Restart OpenClaw.
openclaw gateway restart
  1. Verify the OpenClaw connection to Agent Platform:
openclaw models status
openclaw agent --agent main --message "Hello world!"

--------------------------------------------------------------------------------

Additional Resources

  • Google Cloud Free Trial Features & Limits
  • Migrate from Google AI Studio to Gemini Enterprise Agent Platform
  • Gemini Enterprise Agent Platform - Models
  • Agent Development Kit Documentation - Connect to Models in Agent Platform
  • OpenClaw Documentation - Connect to Google models
  • Google Cloud Budget Alerts - Setup Guide

Score

0–100
67/ 100

Grade

C

Popularity17/30

804 installs — growing adoption. Source repo has 13,710 GitHub stars.

Completeness19/30

Documented: full SKILL.md body, one-line install. Missing: description, category/license metadata.

Trust25/25

Published by google — an official/recognized organization.

Freshness6/15

No update timestamp is tracked for this skill in our catalog.

Scored automatically from popularity, completeness, trust, and freshness — computed only from data in our catalog, never fabricated.

Proud of your score? Add this badge to your README.

Paste a snippet into your GitHub README. The badge updates automatically and links back to this page.

Agent Platform Migrate From Ai Studio skill score badge previewScore badge

Markdown

[![Agent Platform Migrate From Ai Studio skill](https://www.remoteopenclaw.com/skills/google/skills/agent-platform-migrate-from-ai-studio/badges/score.svg)](https://www.remoteopenclaw.com/skills/google/skills/agent-platform-migrate-from-ai-studio)

HTML

<a href="https://www.remoteopenclaw.com/skills/google/skills/agent-platform-migrate-from-ai-studio"><img src="https://www.remoteopenclaw.com/skills/google/skills/agent-platform-migrate-from-ai-studio/badges/score.svg" alt="Agent Platform Migrate From Ai Studio skill"/></a>

Agent Platform Migrate From Ai Studio FAQ

How do I install the Agent Platform Migrate From Ai Studio skill?

Run “npx skills add https://github.com/google/skills --skill agent-platform-migrate-from-ai-studio” in your terminal. The skill is added to your agent's skills directory and picked up automatically on the next run — no restart or extra configuration needed.

What does the Agent Platform Migrate From Ai Studio skill do?

>- The full SKILL.md on this page shows the exact instructions the skill gives your agent.

Is the Agent Platform Migrate From Ai Studio skill free?

Yes. Agent Platform Migrate From Ai Studio is a free, open-source skill published from google/skills. As with any third-party skill, review the source repository before installing it into an agent with sensitive access.

Does Agent Platform Migrate From Ai Studio work with Claude Code and OpenClaw?

Yes. Skills use the portable SKILL.md format, so Agent Platform Migrate From Ai Studio works with Claude Code, OpenClaw, Codex, Hermes, and any other agent that reads SKILL.md skills.

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