Headless browser automation CLI optimized for AI agents with accessibility tree snapshots and ref-based element selection
数据来源:ClawHub。 在 ClawSkills 查看
选择你使用的 Agent
方法一:命令行安装(推荐)
推荐(无需提前安装 clawhub)
npx clawhub@latest --dir ~/.claude/skills install agent-browser-clawdbot或使用 clawhub CLI(需提前安装)
clawhub --dir ~/.claude/skills install agent-browser-clawdbot⚠️ 需要 Node.js 18+,没有 Node?请使用下方方法二直接下载 ZIP。 安装 Node.js →
方法二:手动下载安装(无需 Node)
下载 ZIP,解压后将文件夹放到以下路径,重启 Agent 即可:
安装路径
~/.claude/skills/agent-browser-clawdbot/💡解压后将文件夹放到上方路径,重启 Agent 即可生效
--- name: agent-browser description: Headless browser automation CLI optimized for AI agents with accessibility tree snapshots and ref-based element selection metadata: {"clawdbot":{"emoji":"🌐","requires":{"commands":["agent-browser"]},"homepage":"https://github.com/vercel-labs/agent-browser"}} ---
Fast browser automation using accessibility tree snapshots with refs for deterministic element selection.
Use agent-browser when:
Use built-in browser tool when:
# 1. Navigate and snapshot
agent-browser open https://example.com
agent-browser snapshot -i --json
# 2. Parse refs from JSON, then interact
agent-browser click @e2
agent-browser fill @e3 "text"
# 3. Re-snapshot after page changes
agent-browser snapshot -i --json
agent-browser open <url>
agent-browser back | forward | reload | close
agent-browser snapshot -i --json # Interactive elements, JSON output
agent-browser snapshot -i -c -d 5 --json # + compact, depth limit
agent-browser snapshot -s "#main" -i # Scope to selector
agent-browser click @e2
agent-browser fill @e3 "text"
agent-browser type @e3 "text"
agent-browser hover @e4
agent-browser check @e5 | uncheck @e5
agent-browser select @e6 "value"
agent-browser press "Enter"
agent-browser scroll down 500
agent-browser drag @e7 @e8
agent-browser get text @e1 --json
agent-browser get html @e2 --json
agent-browser get value @e3 --json
agent-browser get attr @e4 "href" --json
agent-browser get title --json
agent-browser get url --json
agent-browser get count ".item" --json
agent-browser is visible @e2 --json
agent-browser is enabled @e3 --json
agent-browser is checked @e4 --json
agent-browser wait @e2 # Wait for element
agent-browser wait 1000 # Wait ms
agent-browser wait --text "Welcome" # Wait for text
agent-browser wait --url "**/dashboard" # Wait for URL
agent-browser wait --load networkidle # Wait for network
agent-browser wait --fn "window.ready === true"
agent-browser --session admin open site.com
agent-browser --session user open site.com
agent-browser session list
# Or via env: AGENT_BROWSER_SESSION=admin agent-browser ...
agent-browser state save auth.json # Save cookies/storage
agent-browser state load auth.json # Load (skip login)
agent-browser screenshot page.png
agent-browser screenshot --full page.png
agent-browser pdf page.pdf
agent-browser network route "**/ads/*" --abort # Block
agent-browser network route "**/api/*" --body '{"x":1}' # Mock
agent-browser network requests --filter api # View
agent-browser cookies # Get all
agent-browser cookies set name value
agent-browser storage local key # Get localStorage
agent-browser storage local set key val
agent-browser tab new https://example.com
agent-browser tab 2 # Switch to tab
agent-browser frame @e5 # Switch to iframe
agent-browser frame main # Back to main
{
"success": true,
"data": {
"snapshot": "...",
"refs": {
"e1": {"role": "heading", "name": "Example Domain"},
"e2": {"role": "button", "name": "Submit"},
"e3": {"role": "textbox", "name": "Email"}
}
}
}
-i flag - Focus on interactive elements--json - Easier to parseagent-browser wait --load networkidlestate save/load--headed for debugging - See what's happeningagent-browser open https://www.google.com
agent-browser snapshot -i --json
# AI identifies search box @e1
agent-browser fill @e1 "AI agents"
agent-browser press Enter
agent-browser wait --load networkidle
agent-browser snapshot -i --json
# AI identifies result refs
agent-browser get text @e3 --json
agent-browser get attr @e4 "href" --json
# Admin session
agent-browser --session admin open app.com
agent-browser --session admin state load admin-auth.json
agent-browser --session admin snapshot -i --json
# User session (simultaneous)
agent-browser --session user open app.com
agent-browser --session user state load user-auth.json
agent-browser --session user snapshot -i --json
npm install -g agent-browser
agent-browser install # Download Chromium
agent-browser install --with-deps # Linux: + system deps
Skill created by Yossi Elkrief (@MaTriXy)
agent-browser CLI by Vercel Labs
安装 Agent Browser 后,可以对 AI 说这些话来触发它
Help me get started with Agent Browser
Explains what Agent Browser does, walks through the setup, and runs a quick demo based on your current project
Use Agent Browser to headless browser automation CLI optimized for AI agents with access...
Invokes Agent Browser with the right parameters and returns the result directly in the conversation
What can I do with Agent Browser in my ai agent & automation workflow?
Lists the top use cases for Agent Browser, with example commands for each scenario
将技能文件夹放到 ~/.claude/skills/agent-browser-clawdbot/ 目录(个人级,所有项目可用),或 .claude/skills/agent-browser-clawdbot/(项目级)。重启 AI 客户端后,用 /agent-browser-clawdbot 主动调用,或让 AI 根据上下文自动发现并使用。
Agent Browser 支持 Claude、Cursor、OpenClaw,可与这些 AI 平台无缝集成,扩展其能力。
Agent Browser 可免费安装使用。请查阅仓库了解许可证信息。
Headless browser automation CLI optimized for AI agents with accessibility tree snapshots and ref-based element selection
Agent Browser 属于「AI Agent & Automation」分类,该分类的技能帮助 AI 智能体在此领域执行专业任务。
Automate my ai agent & automation tasks using Agent Browser
Identifies repetitive steps in your workflow and sets up Agent Browser to handle them automatically