Skip to content
cccskills
FreePublished on GitHub

google-agents-cli-onboarding

Set up Google's agents-cli and find the right workflow for building AI agents. Connects requirements planning, project creation, implementation, evaluation, deployment, publishing, and monitoring through specialized skills for the Gemini Enterprise Agent Platform.

OriginalShow the original description

Onboarding 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.

See how to install

Good for

  • Set up agents-cli and its specialized skills
  • Document agent requirements before writing code
  • Find the workflow for creating and evaluating an ADK agent
  • Find deployment, publishing, and monitoring workflows

Files included (1)

  • SKILL.md3.9 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

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:

uvx google-agents-cli setup

Alternatively, to install only the expert skills and let the agent handle execution:

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-evalValidate 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.

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

Reviews

No reviews yet. Tell others what you thought.

Comments

No login needed. Share how it worked for you, ask a question, or note where it did not run.

No comments yet. Be the first to write one.

Comments are published right away. Do not include personal information such as email addresses or phone numbers. Up to 2 URLs.

0 / 1,000 characters

This form is protected by reCAPTCHA, and the Google Privacy Policy and Terms of Service apply.

More skills from this repository

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
google/skills21.4KUpdated Oct 17, 2026

Deploy Model Garden models to Agent Platform endpoints, the addresses used for model requests. Check supported hardware and estimated hourly costs, inspect deployment progress, test predictions, and remove deployed resources after use.

  • Choose a deployable model and supported hardware
  • Estimate hourly deployment costs before approval
  • Check deployment progress and test predictions
google/skills21.4KUpdated Oct 17, 2026

Manages Agent Platform endpoints, the stable URLs used to serve online model predictions. It supports listing, inspecting, creating, updating, and deleting endpoints, plus troubleshooting permission errors, quota limits, and resources that are busy.

  • Listing endpoints and checking their configuration
  • Creating an endpoint before model deployment
  • Updating endpoint display names or labels
google/skills21.4KUpdated Oct 17, 2026

Evaluate AI models and agents on Google Cloud using test datasets and scoring criteria. Generate simulated user scenarios, analyze failures, and compare results across changes to guide improvements to prompts and code.

  • Build evaluation datasets from conversation logs
  • Generate simulated user scenarios
  • Choose scoring criteria for responses and tool use
google/skills21.4KUpdated Oct 17, 2026

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.

  • Send a test prompt to Gemini
  • Call Llama or DeepSeek with the OpenAI SDK
  • Write code to call an existing custom endpoint
google/skills21.4KUpdated Oct 17, 2026

Guides migration from Google AI Studio’s Gemini API to Gemini Enterprise Agent Platform on Google Cloud, covering billing, access permissions, authentication, and connection settings for SDKs and supported agent tools.

  • Moving a Gemini application to Google Cloud
  • Using Google Cloud credits for Gemini API calls
  • Unifying agent authentication and billing
google/skills21.4KUpdated Oct 17, 2026

See all skills by google

Report a problem with this skill