Google

Diagnose interrupted or repeatedly restarting AI training jobs managed by JobSet on GKE. Correlate restart metrics, node events, host health, and worker logs to distinguish Spot VM preemptions, infrastructure failures, and application crashes, then recommend responses.

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• Investigating repeated JobSet restarts
• Checking whether Spot VM preemptions interrupted training
• Tracing recurring failures to a physical host

Convert Snowflake dbt SQL models to BigQuery through a bulk migration workflow. Preserve Jinja template logic while adapting configuration, explicit type conversions, JSON access, and deduplication patterns, with translated files saved in their directory structure.

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• Migrating Snowflake dbt models to BigQuery in bulk
• Preserving dbt references and incremental processing logic
• Adapting JSON, array, and STRUCT access during migration

Reserve remote Android devices on Google's Developer Device Platform and connect through ADB, Android's device control tool. Check session status and expiration, extend usage time, or cancel sessions and release resources.

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• Find and reserve a remote Android device
• Connect to a reserved device through ADB
• Check session status and expiration

Call Gemini and OpenMaaS models such as Llama, DeepSeek, and Qwen through Google Cloud Agent Platform. Prepare authentication and SDK code, run prompts, configure connection endpoints, and troubleshoot common request errors.

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• Send a test prompt to Gemini
• Call Llama or DeepSeek with the OpenAI SDK
• Write code to call an existing custom endpoint

Implement full-screen ads at natural transitions in mobile apps using the Google Mobile Ads SDK. Follow platform-specific guidance for Android, iOS, or Unity, covering ad loading, event handling, display, and implementation verification.

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• Add full-screen ads between app screens
• Implement interstitial ads on Android or iOS
• Integrate interstitial ads into a Unity app

Integrate the Google Mobile Ads SDK into an Android, iOS, or Unity app for AdMob or Ad Manager. Follow platform-specific steps to add dependencies, set the application identifier, initialize the SDK, and verify the integration.

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• Add the SDK to an Android app
• Configure the SDK for an iOS app
• Integrate mobile ads into a Unity project

Add Google Mobile Ads banners to Android, iOS, or Unity apps. Guides implementation from defining the ad view and choosing its size to handling load events, loading the banner, and checking the completed integration.

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• Add a banner ad to an Android app
• Place an adaptive banner at the top or bottom of an iOS app
• Integrate a banner ad into a Unity app

Set up credentials and a development environment for your first Google Ads API request to retrieve campaigns. Choose from six official client libraries or direct HTTP requests, with guidance for account IDs, developer tokens, and common authorization errors.

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• Prepare credentials for a first Google Ads API integration
• Build an example that retrieves advertising campaigns
• Choose a client library or direct REST requests

Migrate an existing Android app from the legacy Google Mobile Ads SDK to GMA Next-Gen SDK. The skill maps dependencies, imports, classes, and methods, and guides changes to initialization, ad callbacks, and UI thread handling.

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• Replace legacy advertising SDK dependencies
• Update ad imports, classes, and method calls
• Adapt initialization and UI updates in callbacks

Diagnose declines in Google Ads conversions, conversion value, and leads by comparing periods, traffic, device breakdowns, impression share, and account changes. Use live account data through the Google Ads MCP Server or receive queries and diagnostic guidance for manual execution.

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• Investigate sudden drops in conversions or conversion value
• Identify budget or ad rank limits on impression share
• Separate traffic declines from conversion rate declines

Choose a Google Cloud database by clarifying data needs, workload, and scale. The skill explains its recommendation and prepares validated Terraform configurations or provisioning scripts for review before infrastructure changes are made.

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• Choosing a database for a new Google Cloud application
• Clarifying data models, workloads, and scale requirements
• Preparing and validating database provisioning code for review

Inspect and manage model tuning jobs, which adapt models through additional training, in Agent Platform. List jobs, check their status and details, and cancel running jobs after reviewing the target and explicitly confirming the action.

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• List running model tuning jobs
• Check the status and details of a specific job
• Cancel a long-running job after confirmation

Create custom Google Analytics reports with user counts, page views, and breakdowns by city or date. The skill covers API setup, authentication, and checking whether selected measurements and grouping fields can be used together.

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• Report active users by city and date
• Automate recurring analytics reports
• Check which report fields work together

Explore document collections in Agent Platform RAG Engine, list their files, and retrieve relevant passages with source references. Use retrieved material to generate answers grounded in the collection through Python SDKs.

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• Listing available document collections and files
• Inspecting a specific RAG corpus
• Finding relevant passages and their sources

Configure Google Cloud logs across multiple projects, either by storing them centrally or querying them together where they already reside. The skill guides routing, access permissions, and log views, and helps diagnose missing logs and permission failures.

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• Collect logs from multiple projects in one central bucket
• Query distributed logs without copying their data
• Set log access boundaries by project or log type

Prepare to fine-tune open models or Gemini models on Agent Platform. Check the environment, convert and validate training data, choose supported models and settings, and estimate tuning costs for open models.

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• Checking whether an Agent Platform tuning environment is ready
• Converting and validating training datasets
• Choosing models and training settings for a task

Generate Python code to clean, transform, analyze, visualize, and model BigQuery data with BigQuery DataFrames. The skill keeps processing in the cloud and uses familiar table operations, with guidance for previews, schema checks, and machine learning.

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• Clean and transform BigQuery data with Python
• Preview data and check column types
• Visualize aggregated or sampled data

Implement rewarded ads with the Google Mobile Ads SDK on Android, iOS, or Unity. Add a user interface for choosing to view an ad for a reward, and follow steps for loading, event handling, display, and verification.

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• Add ads users choose to view for in-app rewards
• Implement rewarded ads on Android or iOS
• Integrate rewarded ads into a Unity app

Write SQL that uses BigQuery’s built-in machine learning and generative AI for forecasting, anomaly detection, identifying drivers of change, searching by meaning, and classifying or summarizing text stored in your data.

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• Forecasting future values from time-series data
• Detecting anomalies and investigating drivers of change
• Searching documents by meaning

Guides implementation of audience uploads, individual removals, and full replacements through the Data Manager API. It covers formatting and hashing identifiers, validating requests, and checking processing results for Customer Match and supported device ID audiences.

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• Upload Customer Match audience members
• Remove selected users from an audience
• Clear or replace an entire audience

Build Cloud Monitoring requests from metric definitions and resource details. Generate JSON parameters, filters, and aggregation settings for retrieving time series data, then validate the request against the live API.

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• Build JSON requests to retrieve monitoring data
• Filter metrics for specific VMs or databases
• Set aggregation intervals and resource grouping

Integrate video and audio ads into websites, apps, and TV platforms with Google IMA SDK. Follow platform-specific guidance for client-side ad requests, playback coordination, error handling, and cleanup after ads finish.

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• Adding video ads to a website
• Integrating ads into mobile and TV apps
• Coordinating ad playback with main content

Prepare a local development environment for the Data Manager API with authentication and library installation guidance. It covers five programming languages and companion utilities for formatting, hashing, and encrypting user identifiers before ingestion.

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• Preparing a local environment for the Data Manager API
• Installing client and identifier utility libraries
• Configuring local credentials and access scopes

Retrieve BigQuery execution records and resource metrics using the right tool for each task. The skill guides monitoring tool selection and SQL queries for performance investigations, capacity analysis, and reviews of billable compute and storage usage.

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• Retrieve execution details for a slow job
• Check compute capacity contention and queue delays
• Review reserved capacity and autoscaling limits