browser-use AI浏览器自动化

让AI代理控制浏览器自动化网页操作。支持 Claude/GPT/Gemini/Ollama，可执行填表、购物、搜索等任务。

Security Scan

The skill's README-style instructions request multiple API keys, encourage running remote install scripts (curl | sh), and advise reusing local Chrome profiles and syncing auth to a cloud endpoint — these actions can expose credentials and persist code beyond the skill, and they are not fully justified by the metadata.

Purpose & Capability

The skill claims to enable browser automation (filling forms, shopping, search). That purpose reasonably explains needing LLM API keys and possibly a BrowserUse API key. However the registry metadata declares no required env vars or credentials while the SKILL.md explicitly instructs creating a .env with BROWSER_USE_API_KEY, GOOGLE_API_KEY, ANTHROPIC_API_KEY, OPENAI_API_KEY. This mismatch (metadata says 'none', instructions require many keys) is an incoherence that should be explained by the author.

Instruction Scope

The instructions direct the user/agent to: reuse a local Chrome instance (chrome_instance_path), run cloud sync that uploads authentication (curl https://browser-use.com/profile.sh | BROWSER_USE_API_KEY=XXXX sh), and recommend cloud 'Stealth' + CAPTCHA solutions. Reusing local browser profiles and the explicit cloud-sync command can expose cookies, sessions, and credentials; piping an externally hosted script to sh is high-risk. The SKILL.md also instructs cloning into ~/.openclaw/workspace/skills and adding services to the agent runtime, which expands the agent's operational scope.

Install Mechanism

Although the skill package has no formal install spec, SKILL.md suggests multiple install flows: uv/uvx commands, git clone from GitHub, npx clawhub install, and running a remote profile.sh via curl. The curl | sh pattern (https://browser-use.com/profile.sh) is especially high risk because it executes remote code without review. Using npx/git to fetch code is common, but the combination with an unverified remote script and cloud install instructions is disproportionate for a README-only skill.

Credentials

The SKILL.md asks for several high-sensitivity secrets (BROWSER_USE_API_KEY, GOOGLE_API_KEY, ANTHROPIC_API_KEY, OPENAI_API_KEY) and suggests storing them in a .env and sending a BROWSER_USE_API_KEY to a remote install script. It also instructs reusing local Chrome profiles (which implicitly grants access to local session data). The registry declared no required env vars — this is inconsistent and the requested credentials plus profile reuse are more access than the metadata led you to expect.

Persistence & Privilege

The documentation instructs cloning the repo into the agent's skills directory, adding an MCP service, and copying SKILL.md into other agent skill locations — all actions that persist new code/configuration into the agent environment. While not marked always:true, these are operations that give the skill lasting presence and modify agent config. Combined with the remote-script execution and credential-sync steps, this increases attack surface and persistence risk.

What to consider before installing

Key things to consider before installing: 1) The SKILL.md asks you to run a remote script with curl | sh (curl -fsSL https://browser-use.com/profile.sh | BROWSER_USE_API_KEY=XXXX sh). Do not run that without reviewing the script contents — piping remote scripts to sh can execute arbitrary code. 2) The README asks you to store multiple LLM and service API keys and to reuse a local Chrome profile path; that can expose session cookies and allow the skill to operate on your accounts. Only provide API keys you trust the project with and consider using least-privilege keys or separate accounts. 3) The registry metadata claims no required env vars, but the instructions require several — ask the author to reconcile this. 4) Prefer installing inside an isolated environment (dedicated VM/container) and inspect any downloaded scripts/repos before execution. 5) If you need this capability but don't trust the source, look for an audited project (official GitHub repo, verified domain) or implement automation with well-known browser-automation tools you control. If you want, I can: (a) fetch and summarize the referenced GitHub repo and browser-use.com script (if you allow), or (b) point to safer alternatives and hardening steps for running browser automation.

browser-use

🌐 Make websites accessible for AI agents
GitHub: browser-use/browser-use (90k+ ⭐)
License: MIT | Language: Python 3.11+ | 安装方式: uv

---

一、核心定位

browser-use 让 AI 代理能够控制浏览器完成网页自动化任务，核心理念：

Tell your computer what to do, and it gets it done.

---

二、核心能力

能力	说明
填表	自动填写表单、求职申请
购物	读取购物列表，自动在 Instacart 下单
搜索比价	帮用户找 PC 配件、比较价格
网页操作	点击、输入、截图、导航
多平台集成	Gmail、Slack、Notion 等 1000+ 集成

---

三、安装方式

3.1 快速安装（uv）

# 1. 创建环境并安装
uv init && uv add browser-use && uv sync

# 2. 安装 Chromium（若无浏览器）
uvx browser-use install

# 3. 运行第一个代理
uvx browser-use init --template default

3.2 OpenClaw 集成安装

# 克隆到 skills 目录
cd /root/.openclaw/workspace/skills
git clone https://github.com/browser-use/browser-use.git browser-use

# 或直接安装
npx clawhub@latest install browser-use

---

四、配置 API Key

4.1 环境变量配置

# 创建 .env 文件
cat > .env << EOF
# Browser Use 云端 API（推荐，支持 Stealth + Proxy）
BROWSER_USE_API_KEY=your-key

# 或使用其他 LLM
GOOGLE_API_KEY=your-key
ANTHROPIC_API_KEY=your-key
OPENAI_API_KEY=your-key
EOF

4.2 API Key 获取

服务	地址	费用
Browser Use Cloud	cloud.browser-use.com	免费额度 + 按量付费
Google AI	aistudio.google.com	免费额度
Anthropic	console.anthropic.com	按量付费
OpenAI	platform.openai.com	按量付费
Ollama（本地）	ollama.com	免费（自托管）

---

五、快速开始

5.1 基础代理代码

from browser_use import Agent, Browser, ChatBrowserUse
import asyncio

async def main():
    browser = Browser()  # 本地浏览器
    # browser = Browser(use_cloud=True)  # 云端 Stealth 浏览器

    agent = Agent(
        task="Find the number of stars of the browser-use repo",
        llm=ChatBrowserUse(),  # 或 ChatAnthropic(model='claude-sonnet-4-6')
        browser=browser,
    )
    await agent.run()

if __name__ == "__main__":
    asyncio.run(main())

5.2 指定 LLM 提供商

# Google Gemini
from browser_use import ChatGoogle
agent = Agent(task="...", llm=ChatGoogle(model='gemini-3-flash-preview'), browser=browser)

# Anthropic Claude
from browser_use import ChatAnthropic
agent = Agent(task="...", llm=ChatAnthropic(model='claude-sonnet-4-6'), browser=browser)

# 本地 Ollama
from browser_use import ChatOllama
agent = Agent(task="...", llm=ChatOllama(model='llama3'), browser=browser)

---

六、CLI 工具

6.1 常用命令

# 打开网页
browser-use open https://example.com

# 查看可点击元素
browser-use state

# 点击元素（按索引）
browser-use click 5

# 输入文本
browser-use type "Hello World"

# 截图
browser-use screenshot page.png

# 关闭浏览器
browser-use close

6.2 模板生成

# 生成默认模板
uvx browser-use init --template default

# 生成高级配置模板
uvx browser-use init --template advanced

# 生成自定义工具示例
uvx browser-use init --template tools

---

七、自定义工具

from browser_use import Agent, Browser, Tools

# 定义自定义工具
tools = Tools()

@tools.action(description='获取指定 GitHub 仓库的星数')
def get_github_stars(repo: str) -> str:
    """查询 GitHub 仓库的星数"""
    import requests
    r = requests.get(f"https://api.github.com/repos/{repo}")
    return r.json().get("stargazers_count", "Unknown")

# 创建代理
agent = Agent(
    task="查询 browser-use 仓库的星数",
    llm=ChatBrowserUse(),
    browser=Browser(),
    tools=tools,
)
await agent.run()

---

八、认证与持久化

8.1 复用 Chrome 配置

from browser_use import Agent, Browser

browser = Browser(
    chrome_instance_path="/path/to/chrome",  # 复用本地 Chrome
)

agent = Agent(
    task="登录我的 Gmail 并发送邮件",
    llm=ChatBrowserUse(),
    browser=browser,
)

8.2 同步云端配置

# 同步认证信息到云端
curl -fsSL https://browser-use.com/profile.sh | \
  BROWSER_USE_API_KEY=XXXX sh

---

九、云端 vs 开源

特性	开源版	云端版（推荐）
费用	免费（需自备 LLM API）	免费额度 + 按量
Stealth	❌ 需自配	✅ Proxy 轮换 + CAPTCHA 解决
维护	需自己运维	✅ 全托管
自定义工具	✅ 深度集成	✅ 支持
并发规模	受限于本地资源	✅ 可水平扩展

---

十、应用场景示例

10.1 求职申请

agent = Agent(
    task="Fill in this job application with my resume and information.",
    llm=ChatBrowserUse(),
    browser=Browser(),
)
await agent.run()

10.2 购物

agent = Agent(
    task="Put this list of items into my instacart: milk, eggs, bread.",
    llm=ChatBrowserUse(),
    browser=Browser(),
)
await agent.run()

10.3 比价搜索

agent = Agent(
    task="Help me find parts for a custom PC within budget $1500.",
    llm=ChatBrowserUse(),
    browser=Browser(),
)
await agent.run()

---

十一、故障排除

问题	解决方案
Chromium 未安装	uvx browser-use install
API Key 报错	检查 .env 文件配置
浏览器无法启动	chrome --version 确认已安装 Chrome
被网站检测	使用云端版 Browser(use_cloud=True)
任务失败	增加 max_steps 参数

---

十二、OpenClaw 集成

12.1 MCP 服务方式（推荐）

# 安装 MCP
cd /root/.openclaw/workspace
npx clawhub@latest install browser-use-mcp

# 添加到 mcporter 配置
openclaw mcp add browser-use --command "python -m browser_use.mcp"

12.2 Claude Code Skill

mkdir -p ~/.claude/skills/browser-use
curl -o ~/.claude/skills/browser-use/SKILL.md \
  https://raw.githubusercontent.com/browser-use/browser-use/main/skills/browser-use/SKILL.md

---

十三、费用参考

ChatBrowserUse 模型定价（推荐）

类型	价格（每 1M tokens）
输入	$0.20
缓存输入	$0.02
输出	$2.00

其他模型对比

模型	特点
bu-30b-a3b-preview	Browser Use 专用优化模型
claude-sonnet-4-6	Anthropic 最新旗舰
gemini-3-flash-preview	Google 高效模型
llama3（Ollama）	免费本地运行

---

十四、使用方式

触发场景

用户说「帮我自动填表」→ browser-use 填表示例
用户说「自动帮我购物」→ browser-use 购物示例
用户说「AI 控制浏览器」→ 展示 browser-use 能力
用户说「安装 browser-use」→ 执行安装步骤
用户说「配置 API key」→ 执行配置流程

组合使用

用户：「帮我自动化完成这个求职申请流程」
→ 分析表单字段
→ 调用 browser-use Agent
→ 配置 ChatBrowserUse() LLM
→ 自动执行填表 + 上传简历

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十五、关联技能

关联技能	关系
chrome-devtools-mcp	浏览器自动化底层工具
browser-automation-stealth	隐身浏览器技术
cognee-memory	记忆管理（跨会话持久化）
ai-research-tools	科研数据自动采集

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十六、注意事项

⚠️ 注意事项：
- Python >= 3.11 required
- 建议使用 uv 管理依赖
- 云端版有免费额度
- 部分网站有反爬机制，建议使用云端 stealth 浏览器
- 遵守网站使用条款，勿用于非法爬虫

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本技能整合 browser-use 完整安装配置与应用指南