Google Agents Cli ScaffoldSAFE

The CLI and skills that turn any coding assistant into an expert at creating, evaluating, and deploying AI agents on Google Cloud.

The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.

---
name: google-agents-cli-scaffold
description: >
  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 agents-cli 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 (ADK projects: use google-agents-cli-adk-code) or
  deployment operations (use google-agents-cli-deploy).
metadata:
  author: Google
  license: Apache-2.0
  version: 1.11.0
  requires:
    bins:
      - agents-cli
    install: "uv tool install google-agents-cli"
---

# Project Scaffolding Guide

> **Requires:** `agents-cli` (`uv tool install google-agents-cli`) — [install uv](https://docs.astral.sh/uv/getting-started/installation/index.md) first if needed.

Use the `agents-cli` CLI to create new 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 |
|--------|----------|
| Retrieval/RAG, sandboxed execution, cross-session memory, OAuth consent, guardrails, scheduled runs | **No flag** — these come from clone-and-study recipes. **ADK Python:** see the topic index in `/google-agents-cli-adk-code` → `references/samples.md`; on other frameworks, see the sample index the framework template ships |
| A2A protocol | built into the scaffolded app — scaffold normally (**ADK Python:** `--agent adk`, the default; **ADK Go:** `--agent adk_go`) |
| Prototype (no deployment) | `--prototype` |
| Deployment target | `--deployment-target <agent_runtime\|cloud_run\|gke>` |
| CI/CD runner | `--cicd-runner <github_actions\|google_cloud_build>` |
| Session storage | `--session-type <in_memory\|cloud_sql\|agent_platform_sessions>` |

### Product name mapping

Current names (and older names users may say) → CLI values (`vertexai` SDK package name unchanged):

- Agent Runtime in Gemini platform (Agent Engine / Vertex AI Agent Engine / Agent Runtime) → `--deployment-target agent_runtime`
- Sessions in Gemini platform (Agent Engine sessions / Agent Platform Sessions) → `--session-type agent_platform_sessions`
- Search / Vector Search in Gemini platform (Vertex AI Search / Vertex AI Vector Search) / RAG → clone-and-study recipe, not a flag

> **Removed flags.** `--datastore`, the `agentic_rag` template, and `agents-cli infra datastore` /
> `agents-cli data-ingestion` no longer exist. If you reach for one, you want a recipe instead.

---

## Step 2: Create or Enhance the Project

### Create a New Project

```bash
agents-cli scaffold create <project-name> \
  --agent <template> \
  --deployment-target <target> \
  --region <region> \
  --prototype
```

**Constraints:**
- Project name must be **26 characters or less**, lowercase letters, numbers, and hyphens only.
- Do NOT `mkdir` the project directory before running `create` — the CLI creates it automatically. If you mkdir first, `create` will fail or behave unexpectedly.
- Auto-detect the guidance filename based on the IDE you are running in and pass `--agent-guidance-filename` accordingly (`GEMINI.md` for Antigravity CLI, `CLAUDE.md` for Claude Code, `AGENTS.md` for OpenAI Codex/other).
- When enhancing an existing project, check where the agent code lives. If it's not in `app/`, pass `--agent-directory <dir>` (e.g. `--agent-directory agent`). Getting this wrong causes enhance to miss or misplace files.

### Reference Files

| File | Contents |
|------|----------|
| `references/flags.md` | Full flag reference for `create` and `enhance` commands |

### Enhance an Existing Project

```bash
agents-cli scaffold enhance . --deployment-target <target>
agents-cli scaffold enhance . --cicd-runner <runner>
```

Run this from inside the project directory (or pass the path instead of `.`).

### Upgrade a Project

Upgrade an existing project to a newer agents-cli version, intelligently applying updates while preserving your customizations:

```bash
agents-cli scaffold upgrade                # Upgrade current directory
agents-cli scaffold upgrade <project-path> # Upgrade specific project
agents-cli scaffold upgrade --dry-run      # Preview changes without applying
agents-cli scaffold upgrade --auto-approve  # Auto-apply non-conflicting changes
agents-cli scaffold upgrade --force        # Overwrite scaffolding files when smart-merge fails
agents-cli scaffold upgrade --force --dry-run  # List what --force would overwrite
```

`--force` is a fallback for when smart-merge fails. Smart-merge also stops when the agents-cli version that created the project is not on PyPI, because it needs that version's template; use `--force` then too. It overwrites scaffolding files with the new template and keeps agent code, config files, `README.md`, the agent guidance file and eval datasets and config. It never removes dependencies or files the new template dropped (for example, a removed CI workflow), so remove unused ones by hand. Afterwards, check your imports and run your tests. Use `--dry-run` first to see which files change.

### Execution Modes

The CLI defaults to **strict programmatic mode** — all required params must be supplied as CLI flags or a `UsageError` is raised. No approval flags needed. Pass all required params explicitly.

### Common Workflows

**Always ask the user before running these commands.** Present the options (CI/CD runner, deployment target, etc.) and confirm before ex

SAFEgrade B · trust 89/100 Nothing in the source contradicts what it says it does. Grade A is reserved for packages that have also passed the behavioural sandbox.

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