Browse skills

Helps developers send conversion and event data to Google Ads, Google Analytics, and Floodlight through the Data Manager API. It covers destination setup, data formatting, validation, migration from other APIs, and checking processing results.

• Implement offline conversion uploads to Google Ads
• Send recommended or custom GA4 events
• Migrate event ingestion from another Google API

Integrate Google's IMA DAI SDK for dynamic ad insertion into web, mobile, and TV video players. The skill guides setup and stream requests for live or on-demand HLS and DASH content configured in Google Ad Manager.

• Adding DAI live playback to a web video player
• Integrating on-demand video playback on Android or iOS
• Implementing DAI playback for tvOS, Cast, or Roku

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.

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

Create Terraform files that define alerts for AI agent latency, errors, token use, safety, security, and response quality. Check telemetry and existing policies first, then validate the generated configuration. Quality alerts require Vertex AI.

• Configure alerts for agent latency and error rates
• Monitor rapid increases in token usage
• Monitor safety triggers and permission denials

Manage saved prompts in Agent Platform with Python, including creation, listing, retrieval, version tracking, and deletion. Retrieve a specific version and fill template variables to reuse a prompt with its associated model.

• Create a managed prompt template
• List saved prompts and inspect their contents
• Retrieve a specific version and fill template variables

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.

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

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.

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

Manage BigQuery datasets, tables, views, and jobs, and run SQL queries for basic data analysis. Provides setup examples and references for data ingestion, command-line operations, client libraries, access permissions, and infrastructure configuration.

• Create BigQuery datasets and tables
• Search and aggregate data with SQL
• Load data and manage processing jobs

Audit Google Mobile Ads SDK integration in iOS, Android, or Unity projects. Check test IDs, ad units, SKAdNetwork IDs, adapter compatibility, and ad preloading, then report findings and next steps in a table.

• Audit mobile ad integration before launch
• Check for remaining test IDs and invalid formats
• Review SKAdNetwork IDs and adapter compatibility

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.

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

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.

• 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

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.

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

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.

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

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.

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

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.

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

Find relevant Google Cloud monitoring metrics for a service or resource. Retrieves current metric definitions through the API, filters them by the requested concepts, and presents selected metrics with their names, data types, units, and monitored resources.

• Find CPU metrics for Compute Engine
• Identify Cloud Storage write throughput and request metrics
• Check metric data types and units

Automate Google Analytics administration through its Admin API. Manage accounts, properties, data streams, custom dimensions for additional analysis fields, event settings, and product links, with guidance on authentication and official client libraries.

• List accessible accounts and properties
• Create properties and configure data retention
• Manage custom dimensions and key events

Design Google Cloud infrastructure with Terraform, validate it locally, and assess the planned changes for security, cost, and reliability. The skill then imports templates into Application Design Center, deploys them, investigates failures, and checks the deployed services.

• Designing and locally validating Terraform for GCP
• Assessing infrastructure plans before deployment
• Importing and deploying Application Design Center templates

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.

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

Investigate failing or slow BigQuery jobs and unexpected cost increases. Compare execution details and resource usage with a normal baseline to isolate bottlenecks, identify likely causes, and determine practical remediation steps.

• Investigate failed or slow BigQuery jobs
• Locate bottlenecks in execution stages
• Diagnose sudden increases in query or capacity costs

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.

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

Turn Cloud Monitoring metric definitions and resource filters into validated PromQL queries, a language for querying monitoring data. Choose suitable aggregation functions, preserve supplied resource names, and format queries for use in Cloud Monitoring.

• Convert Cloud Monitoring metric definitions into PromQL
• Filter monitoring queries to specific resources
• Choose aggregations that match metric types

Configure Cloud Logging within one Google Cloud project. Set storage locations, retention periods, routing rules, and viewing permissions; create metrics from logs; and adjust stored volume through exclusions or sampling, which retains only a portion of entries.

• Set regional log storage and retention periods
• Restrict access to sensitive logs
• Count specific errors with logs-based metrics

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.

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