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Agent Browser Bwm

作者 blueworldmarketing · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install agent-browser-bwm
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 essentially instructs the agent to drive the external 'agent-browser' CLI. Before using it: (1) Verify you want an agent that can execute CLI commands on your machine. (2) Confirm the upstream package (https://github.com/vercel-labs/agent-browser and the npm package) is trustworthy before running npm install -g or agent-browser install (which downloads Chromium). (3) Be careful when using state load/save — those JSON files can contain cookies or tokens; don't load untrusted files. (4) Network routing and mocking features can alter requests during automation; use them only when intended. If you need higher assurance, inspect the agent-browser package source and its npm release before installing.
功能分析
Type: OpenClaw Skill Name: agent-browser-bwm Version: 1.0.0 The skill bundle provides a standard interface for the 'agent-browser' CLI tool (a legitimate Vercel Labs project) used for headless browser automation. The SKILL.md file contains comprehensive documentation for navigation, element interaction, and session management, all of which are consistent with the stated purpose of the tool. No evidence of malicious intent, data exfiltration, or prompt injection was found.
能力评估
Purpose & Capability
The SKILL.md consistently describes a CLI tool for headless browser automation and all commands, session/state features, and network controls align with that purpose. It does not request unrelated binaries or credentials.
Instruction Scope
Instructions are restricted to invoking the agent-browser CLI and using its features (snapshots, refs, state save/load, network routing). This is in-scope for a browser automation skill. Note: state load/save commands access local files (e.g., auth.json) which may contain sensitive cookies or tokens — that is expected for session persistence but is a place to exercise caution.
Install Mechanism
There is no platform install spec in the skill bundle (instruction-only). The SKILL.md recommends installing via npm (npm install -g agent-browser) and running agent-browser install to download Chromium. Installing from npm and downloading a browser binary is a reasonable, expected mechanism — users should confirm they trust the package and its source before running those commands.
Credentials
The skill declares no required environment variables or credentials. References to AGENT_BROWSER_SESSION and using filesystem state are proportional to the stated functionality and are optional usage patterns rather than required secrets.
Persistence & Privilege
always:false and default model-invocation behavior are present. The skill does not request permanent platform presence or modify other skills' configs; it only documents running a CLI and storing/reading session files, which is appropriate for this use case.
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-bwm
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /agent-browser-bwm 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 the agent-browser skill (v1.0.0). - Provides fast, deterministic headless browser automation optimized for AI agents. - Supports accessibility tree snapshots with ref-based element selection for reliable automation. - Includes extensive CLI commands for navigation, interaction, information retrieval, session management, network control, and state persistence. - Features session isolation, advanced wait options, and state save/load for robust multi-workflow automation.
元数据
Slug agent-browser-bwm
版本 1.0.0
许可证 MIT-0
累计安装 1
当前安装数 1
历史版本数 1
常见问题

Agent Browser Bwm 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 65 次。

如何安装 Agent Browser Bwm?

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

Agent Browser Bwm 是免费的吗?

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

Agent Browser Bwm 支持哪些平台?

Agent Browser Bwm 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 Bwm?

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

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