Agent skill · software engineering · aiskillstore
google-agents-cli-scaffold
This skill should be used when the user wants to "create an agent project", "start a new ADK project", "build me a new agent", "add CI/CD to my project", "add deployment", "enhance my project", or "upgrade my project". Part of the Google ADK (Agent Development Kit) skills suite. Covers `agents-cli scaffold create`, `scaffold enhance`, and `scaffold upgrade` commands, template options, deployment targets, and the prototype-first workflow. Do NOT use for writing agent code (use google-agents-cli-adk-code) or deployment operations (use google-agents-cli-deploy).
Why this skill is useful
Adds specific commands and templates for creating and enhancing ADK agent projects that the AI wouldn't reliably generate on its own.
What it needs
Requires agents-cli installed locally. About 6k tokens when loaded. Last updated 2026-08-07. 405 stars on the source repository.
What this skill does
ADK Project Scaffolding Guide Requires: agents-cli (uv tool install google-agents-cli) — install uv first if needed. Use the agents-cli CLI to create new ADK agent projects or enhance existing ones with deployment, CI/CD, and infrastructure scaffolding. --- Prerequisite: Clarify Requirements (MANDATORY for new projects) Before scaffolding a new project, load /google-agents-cli-workflow and complete Phase 0 — clarify the user's requirements before running any scaffold create command. Ask what the agent should do, what tools/APIs it needs, and whether they want a prototype or full deployment. --- Step 1: Choose Architecture Mapping user choices to CLI flags: Choice CLI flag -------- ---------- RAG with vector search --agent agenticrag --datastore agentplatformvectorsearch RAG with document search --agent agenticrag --datastore agentplatformsearch A2A protocol --agent adka2a Prototype (no deployment) --prototype Deployment target --deployment-target <agentruntime\ cloudrun\ gke> CI/CD runner --cicd-runner <githubactions\ googlecloudbuild> Session storage --session-type <inmemory\ cloudsql\ agentplatformsessions> Product name mapping The platform formerly known as "Vertex AI" is now Gemini Enterprise Agent Platform (short: Agent Platform). Users may refer to products by different names. Map them to the correct CLI values: User may say CLI value ------------- ----------- Agent Engine, Vertex AI Agent Engine, Agent Runtime --deployment-target agentruntime Vertex AI Search, Agent Search --datastore agentplatformsearch Vertex AI Vector Search, Vector Search --datastore agentplatformvectorsearch Agent Engine sessions, Agent Platform Sessions --session-type agentplatformsessions The vertexai Python SDK package name is unchanged. --- Step 2: Create or Enhance the Project Create a New Project Constraints: Project name must be 26 characters or less, lowercase letters, numbers, and hyphens only. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills aiskillstore/google-agents-cli-scaffold