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Agent Browser Clawdbot 0

作者 auroechan · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
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当前安装
1
版本数
在 OpenClaw 中安装
/install agent-browser-clawdbot-0
功能描述
Headless browser automation CLI optimized for AI agents with accessibility tree snapshots and ref-based element selection
使用说明 (SKILL.md)

Agent Browser Skill

Fast browser automation using accessibility tree snapshots with refs for deterministic element selection.

Why Use This Over Built-in Browser Tool

Use agent-browser when:

  • Automating multi-step workflows
  • Need deterministic element selection
  • Performance is critical
  • Working with complex SPAs
  • Need session isolation

Use built-in browser tool when:

  • Need screenshots/PDFs for analysis
  • Visual inspection required
  • Browser extension integration needed

Core Workflow

# 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

Key Commands

Navigation

agent-browser open \x3Curl>
agent-browser back | forward | reload | close

Snapshot (Always use -i --json)

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

Interactions (Ref-based)

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

Get Information

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

Check State

agent-browser is visible @e2 --json
agent-browser is enabled @e3 --json
agent-browser is checked @e4 --json

Wait

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"

Sessions (Isolated Browsers)

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 ...

State Persistence

agent-browser state save auth.json        # Save cookies/storage
agent-browser state load auth.json        # Load (skip login)

Screenshots & PDFs

agent-browser screenshot page.png
agent-browser screenshot --full page.png
agent-browser pdf page.pdf

Network Control

agent-browser network route "**/ads/*" --abort           # Block
agent-browser network route "**/api/*" --body '{"x":1}'  # Mock
agent-browser network requests --filter api              # View

Cookies & Storage

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

Tabs & Frames

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

Snapshot Output Format

{
  "success": true,
  "data": {
    "snapshot": "...",
    "refs": {
      "e1": {"role": "heading", "name": "Example Domain"},
      "e2": {"role": "button", "name": "Submit"},
      "e3": {"role": "textbox", "name": "Email"}
    }
  }
}

Best Practices

  1. Always use -i flag - Focus on interactive elements
  2. Always use --json - Easier to parse
  3. Wait for stability - agent-browser wait --load networkidle
  4. Save auth state - Skip login flows with state save/load
  5. Use sessions - Isolate different browser contexts
  6. Use --headed for debugging - See what's happening

Example: Search and Extract

agent-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

Example: Multi-Session Testing

# 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

Installation

npm install -g agent-browser
agent-browser install                     # Download Chromium
agent-browser install --with-deps         # Linux: + system deps

Credits

Skill created by Yossi Elkrief (@MaTriXy)

agent-browser CLI by Vercel Labs

安全使用建议
This skill is coherent and documents usage of agent-browser CLI. Before installing or running it, verify you trust the npm package and the GitHub project (supply-chain risk), run it in an isolated environment if possible, and be cautious with state save/load files (they can contain cookies or tokens). Avoid loading auth state from untrusted sources and don't expose secret files to the tool. If you need visual debugging or screenshots for auditing, use the built-in browser tool as suggested by the SKILL.md.
功能分析
Type: OpenClaw Skill Name: Developer: Version: Description: OpenClaw Agent Skill The skill provides a CLI wrapper for 'agent-browser', a headless browser automation tool. It includes high-risk capabilities such as full network access, the ability to extract and save session cookies/local storage to the filesystem ('agent-browser cookies', 'agent-browser state save'), and the execution of arbitrary JavaScript within the browser context ('agent-browser wait --fn'). While these features are aligned with the stated purpose of browser automation and the documentation (SKILL.md) is functional and transparent, the broad permissions and potential for handling sensitive authentication data meet the criteria for suspicious risky capabilities.
能力评估
Purpose & Capability
Name/description describe a headless browser CLI and the SKILL.md only references the agent-browser CLI, snapshots, refs, sessions, state save/load, network routing, etc. There are no unrelated env vars, binaries, or config paths requested — capabilities are coherent with browser automation.
Instruction Scope
Instructions stay within browser automation: navigation, snapshots, ref-based interaction, session/state management, network routing. These commands necessarily provide access to cookies/localStorage and can mock/abort network requests; that is expected for this tool but is powerful (able to access site data and intercept requests). The SKILL.md does not instruct reading arbitrary host files or environment secrets beyond an optional AGENT_BROWSER_SESSION var.
Install Mechanism
The skill is instruction-only (no install spec). The doc suggests installing via npm (npm install -g agent-browser) and running agent-browser install to download Chromium. This is a normal third-party installation path; it does mean executing code from npm and downloading a browser binary, which are standard but carry the usual supply-chain/privilege risks.
Credentials
No required environment variables, credentials, or config paths are declared. The only env mentioned is an optional AGENT_BROWSER_SESSION for session selection. The SKU commands allow saving/loading state files (cookies/storage) which could contain sensitive tokens — that is a functional capability of the browser tool rather than an unexplained credential request.
Persistence & Privilege
Skill is not always-included, is user-invocable, and does not request persistent platform-level privileges. It does not attempt to modify other skills or system configuration in the instructions.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install agent-browser-clawdbot-0
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /agent-browser-clawdbot-0 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.0
- Initial release of agent-browser skill. - Provides fast, deterministic browser automation using accessibility tree snapshots and ref-based element selection. - Supports multi-step workflows, session isolation, and advanced state management. - Includes comprehensive CLI for navigation, interaction, network control, cookies/storage, tabs/frames, and state persistence. - Optimized for AI agents; ideal for complex SPAs and scenarios where performance and precise element targeting are critical.
元数据
Slug agent-browser-clawdbot-0
版本 1.0.0
许可证 MIT-0
累计安装 4
当前安装数 4
历史版本数 1
常见问题

Agent Browser Clawdbot 0 是什么?

Headless browser automation CLI optimized for AI agents with accessibility tree snapshots and ref-based element selection. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 246 次。

如何安装 Agent Browser Clawdbot 0?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install agent-browser-clawdbot-0」即可一键安装,无需额外配置。

Agent Browser Clawdbot 0 是免费的吗?

是的,Agent Browser Clawdbot 0 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Agent Browser Clawdbot 0 支持哪些平台?

Agent Browser Clawdbot 0 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Agent Browser Clawdbot 0?

由 auroechan(@auroechan)开发并维护,当前版本 v1.0.0。

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