Google Agents CLI：从搭建到部署一条命令

npx agents-cli skills install

npm install -g @google/agents-cli

mkdir my-agent && cd my-agent
npx agents-cli init

# 交互式选择：
# - Agent name: expense-tracker
# - Model: gemini-2.5-flash（便宜快速）或 gemini-2.5-pro（能力强）
# - Tools: RAG（知识库检索）/ Custom Tools（自定义工具）/ Google Search / Code Execution / grounding

my-agent/
├── agent.py              # Agent 入口：定义 tools、instructions、model
├── requirements.txt       # Python 依赖
├── eval/
│   ├── eval_dataset.jsonl # Eval 测试集
│   └── eval_config.yaml   # Eval 配置
├── deploy/
│   ├── deployment.yaml    # 部署配置
│   └── secrets.yaml       # 密钥配置
└── .agents/
    └── skills/            # 7 个 injected skills

# 在项目根目录执行
npx agents-cli skills install

# Skills 会安装到：
# - .agents/skills/（通用）
# - .claude/skills/（Claude Code）
# - .cursor/skills/（Cursor）
# 同时通过 symlink 链接到你使用的所有 Agent

# 在 Claude Code / Cursor 里：
"用 /scaffold skill 搭建一个 expense-tracker agent，
它能记录费用、分类、查询月度报表，
数据存在 Cloud Firestore 里。"

from google.adk import Agent, Tool

def log_expense(amount: float, category: str, description: str) -> dict:
    """Log a new expense to Cloud Firestore."""
    # ... Firestore 写入逻辑
    return {"status": "logged", "amount": amount, "category": category}

def get_monthly_report(month: str, year: int) -> dict:
    """Query expenses for a given month and generate a report."""
    # ... Firestore 查询逻辑
    return {"month": month, "year": year, "total": total, "by_category": breakdown}

agent = Agent(
    name="expense-tracker",
    model="gemini-2.5-flash",
    instructions="""You are an expense tracking assistant.
    Help users log expenses, categorize them, and generate monthly reports.
    Always confirm the amount and category before logging.""",
    tools=[log_expense, get_monthly_report],
)

# 用 eval skill 的指引运行本地测试
npx agents-cli test

# 或用 ADK 的内置 dev server
adk dev --port 8080
# 打开 http://localhost:8080 交互式测试你的 Agent

# 在 Claude Code / Cursor 里：
"用 /eval skill 为 expense-tracker 写一个 eval 数据集，
覆盖以下场景：
1. 正常记录费用
2. 金额为负数（应该拒绝）
3. 类别不在预定义列表中（应该建议替代）
4. 查询不存在月份的报表（应该返回空而不是报错）
5. 同一天记录超过 50 条费用（应该警告）
"

{"input": "记录午餐 35 元，类别餐饮", "expected_behavior": "should call log_expense with amount=35, category=food", "pass_criteria": "expense logged successfully"}
{"input": "记录 -100 元退款", "expected_behavior": "should reject negative amount", "pass_criteria": "error message about invalid amount"}
{"input": "记录打车费 50 元，类别交通", "expected_behavior": "should call log_expense with amount=50, category=transport", "pass_criteria": "expense logged successfully"}
{"input": "查询 2026 年 13 月的报表", "expected_behavior": "should reject invalid month", "pass_criteria": "error message about invalid month"}
{"input": "记录办公耗材 200 元", "expected_behavior": "should suggest category 'office_supplies' and ask for confirmation", "pass_criteria": "category suggestion presented"}

npx agents-cli eval run

# 输出：
# Test case 1/5: [PASS]
# Test case 2/5: [PASS]
# Test case 3/5: [FAIL] Agent logged the expense without confirming category
# Test case 4/5: [PASS]
# Test case 5/5: [PASS]
#
# Summary: 4/5 passed (80%)
# Failures: see eval/results/failure_analysis.md

# 在 Claude Code / Cursor 里：
"用 /security skill 审查 expense-tracker 的安全风险。"

# 部署到 Agent Runtime（Google 的全托管运行时）
npx agents-cli publish gemini-enterprise

# 或部署到 Cloud Run
npx agents-cli publish cloud-run

# 或部署到 GKE
npx agents-cli publish gke

# 1. 安装
npm install -g @google/agents-cli

# 2. 创建项目
npx agents-cli init my-first-agent

# 3. 进入项目，安装 skills
cd my-first-agent
npx agents-cli skills install

# 4. 打开你的 Coding Agent（Claude Code / Cursor）
#    说："用 /scaffold skill 搭建一个简单的 weather agent"

# 5. 本地测试
npx agents-cli test

# 6. 部署（需要先配好 Google Cloud 项目）
npx agents-cli publish gemini-enterprise