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Agent Skills/Google Agents CLI onboarding
GoogleAgentsSKILL.mdVerified source

Agent Skill

Google Agents CLI onboarding

Install and use the Agents CLI across local development, testing, evaluation, deployment, and monitoring.

Install this skillView repository

Vendor-authored source · Apache-2.0 license.

Raw SKILL.mdInstall the Tokens& Agent Pack

Skill specification

Declared by Google in the package front matter. Trigger conditions are what the coding agent matches on before it loads the skill.

View package fields
Google Agents CLI onboarding SKILL.md front matter fields
Skill namegoogle-agents-cli-onboarding
Trigger conditionsOnboarding entrypoint for agents-cli in Agent Platform. It should be used when the user wants to "create a new agent", "develop an agent", "build an agent using ADK", "run the agent locally", "debug agent code", "test an agent", "evaluate an agent", "deploy an agent", "publish an agent", "monitor an agent", or needs the ADK (Agent Development Kit) development lifecycle.
Upstream categoryDevOps

Install google-agents-cli-onboarding

In a terminal with Node.js, npm and Git, run the command for your agent. The Skills CLI installs the complete package directory, including referenced files within it. Review its install prompt, then start a new agent session. A skill package does not set up an MCP server connection.

Claude Code

.claude/skills/google-agents-cli-onboarding/SKILL.md

Project skills are committed with the repo. Use the user directory for a personal install across every project.

Project install

npx skills add 'https://github.com/google/skills/tree/main/skills/cloud/google-agents-cli-onboarding' --skill 'google-agents-cli-onboarding' --agent 'claude-code'
Install for all projects instead

Personal install

npx skills add 'https://github.com/google/skills/tree/main/skills/cloud/google-agents-cli-onboarding' --skill 'google-agents-cli-onboarding' --agent 'claude-code' --global

Codex

.agents/skills/google-agents-cli-onboarding/SKILL.md

Codex reads `.agents/skills/` as its primary location, which is also the cross-platform default other clients honour.

Project install

npx skills add 'https://github.com/google/skills/tree/main/skills/cloud/google-agents-cli-onboarding' --skill 'google-agents-cli-onboarding' --agent 'codex'
Install for all projects instead

Personal install

npx skills add 'https://github.com/google/skills/tree/main/skills/cloud/google-agents-cli-onboarding' --skill 'google-agents-cli-onboarding' --agent 'codex' --global

Cursor

.agents/skills/google-agents-cli-onboarding/SKILL.md

Cursor also loads `.agents/skills/`, `.claude/skills/`, and `.codex/skills/`, so one committed copy can serve several clients.

Project install

npx skills add 'https://github.com/google/skills/tree/main/skills/cloud/google-agents-cli-onboarding' --skill 'google-agents-cli-onboarding' --agent 'cursor'
Install for all projects instead

Personal install

npx skills add 'https://github.com/google/skills/tree/main/skills/cloud/google-agents-cli-onboarding' --skill 'google-agents-cli-onboarding' --agent 'cursor' --global

Gemini CLI

.agents/skills/google-agents-cli-onboarding/SKILL.md

Gemini CLI reads `.agents/skills/` first when both directories exist.

Project install

npx skills add 'https://github.com/google/skills/tree/main/skills/cloud/google-agents-cli-onboarding' --skill 'google-agents-cli-onboarding' --agent 'gemini-cli'
Install for all projects instead

Personal install

npx skills add 'https://github.com/google/skills/tree/main/skills/cloud/google-agents-cli-onboarding' --skill 'google-agents-cli-onboarding' --agent 'gemini-cli' --global

GitHub Copilot

.agents/skills/google-agents-cli-onboarding/SKILL.md

The Skills CLI uses the shared `.agents/skills/` directory for Copilot project installs.

Project install

npx skills add 'https://github.com/google/skills/tree/main/skills/cloud/google-agents-cli-onboarding' --skill 'google-agents-cli-onboarding' --agent 'github-copilot'
Install for all projects instead

Personal install

npx skills add 'https://github.com/google/skills/tree/main/skills/cloud/google-agents-cli-onboarding' --skill 'google-agents-cli-onboarding' --agent 'github-copilot' --global

SKILL.md

View raw source

Published by Google under Apache-2.0. Rendered from the package in github.com/google/skills/tree/main/skills/cloud/google-agents-cli-onboarding.

Read full skill instructions

Google Agents CLI Onboarding

[!TIP] One-Time Setup: To install the CLI and enable all 7 specialized development skills in your coding agent, run the setup command: bash uvx google-agents-cli setup Alternatively, to install only the expert skills and let the agent handle execution: bash npx skills add google/agents-cli

Overview

This skill serves as the entrypoint for agents-cli — Google's toolkit for building, evaluating, and deploying AI agents on the Gemini Enterprise Agent Platform.

Use this skill to perform the initial setup and identify the correct specialized workflows for your task.

The Agent Development Lifecycle

After running the setup, the following specialized skills become available and will activate automatically based on your requests. Use this table to identify which skill to load for your current phase:

PhaseSpecialized SkillPurpose / When to Load
0 — Understandgoogle-agents-cli-workflowClarify intent. Define the agent spec in .agents-cli-spec.md before coding.
1 — Studygoogle-agents-cli-workflowLeverage samples. Study existing agent samples (e.g., ambient-expense) before scaffolding.
2 — Scaffoldgoogle-agents-cli-scaffoldCreate/Enhance. Initialize the project structure, CI/CD, and infrastructure templates.
3 — Buildgoogle-agents-cli-adk-codeImplement. Write agent logic, tools, callbacks, and manage state using ADK APIs.
4 — Evaluategoogle-agents-cli-eval

Key CLI Commands

Below are the primary commands you will use throughout the development lifecycle:

CommandDescription
agents-cli setupInstall the CLI and configure skills in your coding agent.
agents-cli scaffold <name>Create a new agent project from a template.
agents-cli eval runRun the agent and grade the traces in a single step (generate + grade).
agents-cli deployDeploy your agent to Google Cloud (Agent Runtime, Cloud Run, GKE).
agents-cli publish gemini-enterpriseRegister your deployed agent with Gemini Enterprise.

For the full list of available commands and global options, run `agents-cli --help`.

Next Steps

Follow this sequence to initiate the development workflow:

  1. Execute Setup: Run the uvx or npx command in the [!TIP] box above to install the CLI and enable the specialized skills in your environment.
  2. Verify Installation: Run agents-cli info to confirm the installation and view the active project configuration.
  3. Initiate Phase 0: Ask the user for their core requirements (agent purpose, external tools, deployment target) and document them in .agents-cli-spec.md before writing any code.

Reporting Issues

Report bugs or improvements at Google Agents CLI Issues.

Supporting Links

  • Google Agents CLI Documentation

More Google Agent Skills

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Agent Platform eval flywheel

Build eval datasets, choose quality metrics, analyze failures, and compare agent improvements systematically.

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Call Gemini and OpenMaaS models with current SDKs, correct endpoints, authentication, and error handling.

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Create, retrieve, version, list, and safely delete managed prompts using repeatable Python workflows.

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Agent Platform RAG engine

Manage RAG corpora and files, retrieve grounded context, and generate corpus-grounded responses.

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Discover, register, version, generate, update, and inspect skills in Gemini Enterprise Agent Platform.

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AI Studio to Agent Platform migration

Move Gemini applications from Google AI Studio to cloud IAM, billing, telemetry, and enterprise infrastructure.

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Validate Quality. Run systematic evaluations (LLM-as-judge).
5 — Deploygoogle-agents-cli-deployGo Production. Deploy to Agent Runtime (Vertex AI), Cloud Run, or GKE.
6 — Publishgoogle-agents-cli-publishRegister. Make your agent available as a tool in Gemini Enterprise.
7 — Observegoogle-agents-cli-observabilityMonitor. Set up Cloud Trace, prompt-response logging, and BigQuery analytics.