# Google Agents CLI: One-Command Skill Injection for Enterprise RAG Agents

> The open-source CLI launched April 22, 2026, as part of Gemini Enterprise Agent Platform supplies seven skills for scaffolding, LLM-as-judge evaluation, and deployment to Agent Runtime, extending Karpathy-inspired workflows to production RAG systems.

*Published 2026-07-08 · By Diane Okafor*

Google Agents CLI is an open-source tool that injects seven specialized skills into coding agents via a single setup command to enable full-lifecycle enterprise RAG agent builds with LLM-as-judge evaluations and deployment to Gemini Enterprise Agent Platform.

Enterprise teams building retrieval-augmented generation agents must coordinate code generation, evaluation, and production rollout across multiple tools and environments. The Agents CLI addresses these coordination challenges by supplying a standardized command set that aligns development steps with established agentic engineering practices.

Organizations increasingly depend on RAG agents for data-intensive tasks, which raises the priority of repeatable processes for scaffolding, testing, and deployment.

## What Background Does Agent Development Present for Enterprises?

Andrej Karpathy has promoted agentic engineering methods that position AI systems as autonomous agents handling multi-step workflows. Enterprises have adopted similar methods for RAG agents that must retrieve information and execute reasoning sequences.

Without unified tooling, teams often assemble separate scripts for each lifecycle stage, increasing maintenance overhead and risk of inconsistent results.

## How Does the Agents CLI Address These Issues?

Google introduced the Agents CLI on April 22, 2026, within the Gemini Enterprise Agent Platform on Google Cloud. The tool functions as the programmatic backbone for the agent development lifecycle.

It supplies a machine-readable interface that connects directly to the Agent Development Kit and supports end-to-end management from initial code creation through evaluation and cloud deployment.

## What Are the Technical Capabilities of the Agents CLI?

A single setup command adds seven skills to the coding agent environment. The skills include workflow management, ADK code patterns, scaffolding from templates such as agentic_rag, evaluation with LLM-as-judge and adaptive rubrics, deployment to Agent Runtime or Cloud Run or GKE, Gemini Enterprise registration and publishing, and observability configuration.

The CLI accepts commands such as scaffold, eval generate, eval grade, eval optimize, deploy, and publish gemini-enterprise. It also supports infrastructure tasks for RAG datastores and CI-CD pipelines.

Users can execute the setup through uvx google-agents-cli setup or npx skills add google/agents-cli depending on their runtime preference.

- Execute the setup command to inject the seven skills into the coding agent.
- Run the scaffold command to generate agent code from the agentic_rag template.
- Use eval generate to create test scenarios.
- Apply eval grade to score scenarios with LLM-as-judge methods.
- Execute deploy to target Agent Runtime, Cloud Run, or GKE.
- Run publish gemini-enterprise to register the agent with the enterprise platform.

Selected Agents CLI Commands and Their Primary FunctionsCommandFunctionscaffoldCreates agent code from ADK templates including agentic_rageval generateProduces evaluation scenarios for assessmenteval gradeScores scenarios using LLM-as-judge and adaptive rubricsdeployDeploys to Agent Runtime, Cloud Run, or GKEpublishRegisters agent with Gemini Enterprise

The evaluation workflow produces structured outputs that teams can review before proceeding to deployment stages.

## How Does the Tool Support Different Development Modes?

Agents CLI functions in Agent Mode when paired with coding agents including Claude Code, Gemini CLI, Codex, and Cursor. The injected skills guide the coding agent through each lifecycle step.

Standalone Human Mode allows direct command execution by developers without an intervening coding agent. Local development proceeds through AI Studio before cloud deployment.

## What Are the Market and Stakeholder Implications?

Chief AI officers and implementation teams gain a consistent interface that reduces the need for bespoke scripts across RAG projects. The quantitative scorecard output supplies measurable performance data that supports ROI assessments.

Direct deployment paths to Google Cloud services allow teams to maintain control over infrastructure choices while accelerating movement from prototype to production.

## What Reactions Have Emerged from Early Users?

> Today, we are thrilled to introduce Agents CLI in Agent Platform, the unified programmatic backbone for the Agent Development Lifecycle (ADLC) on Google Cloud.Ivan Cheung, Pier Paolo Ippolito, Elia Secchi, Google authors

Community feedback has noted the alignment between the CLI capabilities and established agentic engineering principles.

## What Comes Next for Agent Development on Google Cloud?

Documentation and codelabs accompany the release, enabling teams to replicate the demonstrated RAG workflow. Continued integration with additional Google Cloud services is expected to expand template options and evaluation criteria.

Early adopters can apply the current feature set to standardize agent builds while monitoring platform updates for further lifecycle automation.

## Sources

1. [Agents CLI is a specialized tool designed specifically for AI coding agents like Gemini CLI, Claude Code, and Cursor.](https://developers.googleblog.com/agents-cli-in-agent-platform-create-to-production-in-one-cli/)
2. [The CLI and skills for building agents on Gemini Enterprise Agent Platform include 7 skills for eval with LLM-as-judge, deploy, publish gemini-enterprise.](https://github.com/google/agents-cli)
3. [Agents CLI provides a unified, machine-readable interface enabling end-to-end agent lifecycle management with LLM-as-judge criteria and the agentic_rag template example.](https://docs.cloud.google.com/gemini-enterprise-agent-platform/agents/quickstart-adk)
4. [In a demonstrated RAG agent build using the agentic_rag template, the tool generated 20 eval scenarios scored via LLM-as-judge and returned a quantitative scorecard.](https://www.linkedin.com/posts/alanblount_the-right-take-on-agents-cli-httpslnkdin-activity-7477407025132396544-F0w5)

---
Source: https://aiintelreport.com/ai-agents/google-agents-cli-enterprise-rag
Index: https://aiintelreport.com/llms.txt · Full text: https://aiintelreport.com/llms-full.txt