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Agent Browser Jt

作者 JoeyTbuilds · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
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在 OpenClaw 中安装
/install agent-browser-jt
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's commands and capabilities are consistent with a headless browser CLI, but there are red flags you should check before installing or using it with real credentials: 1) Metadata mismatch — the registry metadata (owner/slug/version) does not match the included _meta.json; confirm the publisher and repository URL on GitHub. 2) Installing requires running npm install -g agent-browser and agent-browser install (which downloads Chromium) — review the npm package and its source code/maintainer before installing. 3) The skill encourages using 'state load' to load auth JSON files; do not load sensitive credentials or session files unless you trust the package and repository. 4) Network routing and request-mocking commands can rewrite requests (expected for automation) — avoid pointing the tool at sensitive internal systems until verified. If unsure, run the package in an isolated environment (container/VM) and inspect the installed binaries and npm package contents first.
功能分析
Type: OpenClaw Skill Name: agent-browser-jt Version: 1.0.0 The skill bundle provides documentation and instructions for using the `agent-browser` CLI tool, a headless browser automation utility optimized for AI agents. It includes standard automation features such as navigation, element interaction, session management, and state persistence (cookies/localStorage). While the tool possesses powerful capabilities like network interception and credential storage access, these are aligned with its stated purpose, and no evidence of malicious intent, data exfiltration, or prompt injection was found in SKILL.md or _meta.json.
能力评估
Purpose & Capability
The SKILL.md describes a CLI 'agent-browser' for headless automation and all runtime instructions match that purpose (navigation, snapshots, refs, sessions, network control). However, registry metadata (owner ID, slug, version) does not match the included _meta.json content (different ownerId, slug, and version), which is an inconsistency worth verifying with the publisher.
Instruction Scope
Instructions stay within browser automation scope (open, snapshot, click, state save/load, network routing). They do instruct the agent to save/load local state files (e.g., auth.json) and reference an env var (AGENT_BROWSER_SESSION) — these are reasonable for a browser tool but mean the agent may access local credential files if asked to load them. There are no instructions to read unrelated system files or to exfiltrate data, but loading/storing auth files is sensitive and should only be used with trusted files.
Install Mechanism
The skill is instruction-only and has no install spec; SKILL.md recommends installing via 'npm install -g agent-browser' and running 'agent-browser install' to download Chromium. Because the platform does not auto-download anything, risk is low from the skill itself — but installing the third-party npm package and downloading Chromium are external actions the user would perform and should be vetted (check npm package, GitHub repo, and package owner).
Credentials
No required environment variables or credentials are declared. SKILL.md optionally references AGENT_BROWSER_SESSION and uses local state files for cookies/storage; these are proportional to a browser automation tool. There are no unrelated credential requests in the skill files.
Persistence & Privilege
always is false and the skill allows normal autonomous invocation (platform default). The skill does not request to persist or modify other skills or global agent configuration in the provided files.
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-jt
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /agent-browser-jt 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-jt skill. - Provides fast, AI agent-oriented browser automation via a CLI. - Features accessibility tree snapshots and ref-based deterministic element selection. - Supports session isolation, multi-step workflows, network and state control, and compact JSON outputs. - Includes extensive commands for navigation, interaction, waiting, session management, screenshots, network traffic, and storage. - Optimized documentation with usage examples and best practices.
元数据
Slug agent-browser-jt
版本 1.0.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
常见问题

Agent Browser Jt 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 66 次。

如何安装 Agent Browser Jt?

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

Agent Browser Jt 是免费的吗?

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

Agent Browser Jt 支持哪些平台?

Agent Browser Jt 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 Jt?

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

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