>- 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.
npx skills add https://github.com/google/skills --skill 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
> `
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.
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:
| Phase | Specialized Skill | Purpose / When to Load |
| :--- | :--- | :--- |
| 0 — Understand | google-agents-cli-workflow | Clarify intent. Define the agent spec in .agents-cli-spec.md before coding. |
| 1 — Study | google-agents-cli-workflow | Leverage samples. Study existing agent samples (e.g., ambient-expense) before scaffolding. |
| 2 — Scaffold | google-agents-cli-scaffold | Create/Enhance. Initialize the project structure, CI/CD, and infrastructure templates. |
| 3 — Build | google-agents-cli-adk-code | Implement. Write agent logic, tools, callbacks, and manage state using ADK APIs. |
| 4 — Evaluate | google-agents-cli-eval | Validate Quality. Run systematic evaluations (LLM-as-judge). |
| 5 — Deploy | google-agents-cli-deploy | Go Production. Deploy to Agent Runtime (Vertex AI), Cloud Run, or GKE. |
| 6 — Publish | google-agents-cli-publish | Register. Make your agent available as a tool in Gemini Enterprise. |
| 7 — Observe | google-agents-cli-observability | Monitor. Set up Cloud Trace, prompt-response logging, and BigQuery analytics. |
Below are the primary commands you will use throughout the development
lifecycle:
| Command | Description |
| :--- | :--- |
| agents-cli setup | Install the CLI and configure skills in your coding agent. |
| agents-cli scaffold <name> | Create a new agent project from a template. |
| agents-cli eval run | Run the agent and grade the traces in a single step (generate + grade). |
| agents-cli deploy | Deploy your agent to Google Cloud (Agent Runtime, Cloud Run, GKE). |
| agents-cli publish gemini-enterprise | Register your deployed agent with Gemini Enterprise. |
*For the full list of available commands and global options, run `agents-cli
--help`.*
Follow this sequence to initiate the development workflow:
uvx or npx command in the [!TIP] box aboveto install the CLI and enable the specialized skills in your environment.
agents-cli info to confirm the installationand view the active project configuration.
purpose, external tools, deployment target) and document them in
.agents-cli-spec.md before writing any code.
Report bugs or improvements at Google Agents CLI Issues.
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
Automatically creates user-facing changelogs from git commits by analyzing commit history, categorizing changes, and transforming technical commits into clear, customer-friendly release notes. Turns hours of manual changelog writing into minutes of automated generation.
Use when implementation is complete, all tests pass, and you need to decide how to integrate the work - guides completion of development work by presenting structured options for merge, PR, or cleanup
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
React Native and Expo best practices for building performant mobile apps. Use when building React Native components, optimizing list performance, implementing animations, or working with native modules. Triggers on tasks involving React Native, Expo, mobile performance, or native platform APIs.
React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.
Next.js best practices - file conventions, RSC boundaries, data patterns, async APIs, metadata, error handling, route handlers, image/font optimization, bundling
Use when starting feature work that needs isolation from current workspace or before executing implementation plans - creates isolated git worktrees with smart directory selection and safety verification
Take google/google-agents-cli-onboarding from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.
The instructions reference npx, uvx.
Without those the skill loads but fails at the first command.