Google

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.

中文简介正在准备中。当前显示英语简介。

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

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.

中文简介正在准备中。当前显示英语简介。

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

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.

中文简介正在准备中。当前显示英语简介。

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

Create and administer AlloyDB for PostgreSQL databases, including clusters, instances, backups, secure connections, and access permissions. It also covers command-line operations, infrastructure configuration, and MCP tools that let agents automate database tasks.

中文简介正在准备中。当前显示英语简介。

• Create an AlloyDB cluster and primary instance
• Manage backups and plan recovery
• Configure secure connections and access permissions

Plan and carry out agent deployments on Google Cloud using agents-cli. The guide covers deployment targets, permissions, secrets, automated build and deployment pipelines, verification, and recovery procedures for agents built with supported frameworks.

中文简介正在准备中。当前显示英语简介。

• Comparing Agent Runtime, Cloud Run, and GKE
• Setting up automated build and deployment pipelines
• Configuring secrets and service account permissions

Set up monitoring for deployed agents to inspect execution paths, latency, and model interactions. It explains Cloud Trace, prompt and response logging, BigQuery analytics, and external monitoring integrations, with checks for missing data and unwanted content capture.

中文简介正在准备中。当前显示英语简介。

• Investigating agent latency and execution errors
• Configuring prompt and response logging
• Analyzing agent events in BigQuery

Evaluate AI agents by preparing test cases, scoring responses and tool use, investigating failures, and comparing results after changes. Supports built-in checks and custom scoring rules, including evaluations performed by a language model.

中文简介正在准备中。当前显示英语简介。

• Create test cases for an AI agent
• Check response quality and tool use
• Investigate failed evaluation cases

Find API patterns and examples for coding agents with ADK, the Agent Development Kit. Covers tools, state, callbacks, multi-agent coordination, and graph workflows, with Python and Go references plus guidance on studying existing implementations.

中文简介正在准备中。当前显示英语简介。

• Adding tools and callbacks to an ADK agent
• Implementing state management and agent coordination
• Designing branching and parallel graph workflows

Guide development of a LangChain or LangGraph project created with agents-cli. It explains tool additions, local runs, evaluation, and serving while identifying the required graph structure and commands that differ from ADK projects.

中文简介正在准备中。当前显示英语简介。

• Adding tools to an existing agent
• Running and evaluating an agent locally
• Editing a graph while preserving its required interface

Register a deployed agent with Gemini, choose the appropriate registration method, and troubleshoot setup problems. Also covers managing agents and registering MCP servers, which expose tools to agents, in Google Cloud Agent Registry.

中文简介正在准备中。当前显示英语简介。

• Registering a deployed agent with Gemini
• Automating registration in a release pipeline
• Listing and updating registered agents

Create starter projects for AI agents, add deployment configuration and automated build and release pipelines to existing projects, or update generated project files. Supports Python and Go ADK templates and a prototype-first approach.

中文简介正在准备中。当前显示英语简介。

• Starting a Python or Go agent prototype
• Adding deployment configuration to an existing project
• Adding an automated build and release pipeline

Guide AI agent development from requirements and project setup through implementation, behavior evaluation, deployment, and monitoring. Provides coding rules, debugging steps, and links to specialized skills so each phase follows a defined process.

中文简介正在准备中。当前显示英语简介。

• Planning an agent's requirements and architecture
• Running and debugging an agent locally
• Evaluating responses and tool use before deployment