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Agent Skill · 研究检索

browser-automation-core(浏览器自动化核心)

browser-automation-core 用于记录任务执行中的错误、用户纠正、经验和能力缺口,适合在 OpenClaw 中希望让 Agent 持续沉淀问题、修正和最佳实践时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

browser-automation-core 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为接触敏感数据;许可证为 MIT-0,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 24,382。

总安装 4,032周安装 168GitHub Stars 公开资料未说明下载 1,344核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
1.0.0

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:browser-automation-core(浏览器自动化核心)
来源仓库:https://github.com/stefanferreira/browser-automation-core
安装命令:
openclaw skills install browser-automation-core
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install browser-automation-core

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

browser-automation-core 是 OpenClaw 代理的基础浏览器交互能力库。为 Facet 等项目提供统一的导航、点击与内容捕获抽象层。封装了常见错误处理逻辑与重试机制提升任务鲁棒性。内部实现依赖特定 DOM 结构假设,跨站点适配可能存在兼容问题。

开发者应优先使用暴露的标准接口而非直接调用底层方法。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install browser-automation-core;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要接触敏感数据,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

browser-automation-core 怎么安装?

在终端执行 openclaw skills install browser-automation-core。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

browser-automation-core 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

browser-automation-core 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

browser-automation-core 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

browser-automation-core 用的人多吗?

公开数据是累计安装 4,032 次,近一周安装 168 次,下载 1,344 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

browser-automation-core 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
browser-automation-core

浏览器自动化核心 · 本页

4,032—接触敏感数据MIT-0通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
browser-automation-core
description
Core browser automation library for OpenClaw agents. Provides reusable navigation, interaction, and capture capabilities for both Facet (Onshape learning) and Ace (competition entry). Use when any agent needs to automate web browser interactions.

Browser Automation Core Skill

Purpose

A reusable browser automation library that provides common web interaction capabilities for multiple OpenClaw agents. Designed to be extended by agent-specific skills while maintaining a single, well-tested core.

Primary Users

  1. Facet - Onshape CAD learning automation
  2. Ace - Competition entry and form filling
  3. Future agents - Any web automation needs

Architecture

browser-automation-core/          # This skill
├── navigation/                   # URL loading, waiting
├── interaction/                  # Click, type, select
├── capture/                      # Screenshot, HTML capture
├── forms/                        # Form detection and filling
└── sessions/                     # Tab/window management

facets-browser-learning/          # Facet-specific extension
└── uses core + Onshape-specific logic

ace-competition-automation/       # Ace-specific extension  
└── uses core + competition-specific logic

Core Capabilities

Navigation

  • URL loading with timeout and retry
  • Wait conditions (element visible, page loaded)
  • History management (back, forward, refresh)
  • Tab/window control (open, close, switch)

Interaction

  • Element finding (CSS selectors, XPath, text)
  • Basic actions (click, type, clear, submit)
  • Mouse operations (hover, drag, scroll)
  • Keyboard operations (key presses, shortcuts)

Capture

  • Screenshots (full page, element, viewport)
  • HTML capture (page source, element HTML)
  • Text extraction (visible text, attributes)
  • Performance metrics (load times, resources)

Forms

  • Form detection (find all forms on page)
  • Field mapping (match fields to data)
  • Validation (required fields, formats)
  • Submission (submit buttons, AJAX handling)

Sessions

  • Cookie management (save/load sessions)
  • Authentication state (login persistence)
  • Profile management (user agent, viewport)
  • Cleanup (close browsers, clear data)

Quick Start

Installation

# Install from ClawHub (when published)
npx clawhub@latest install browser-automation-core

# Or use local development version
cp -r /path/to/skill /root/.openclaw/workspace/skills/

Basic Usage

# Example: Navigate and take screenshot
from browser_core import BrowserAutomation

browser = BrowserAutomation()
browser.navigate("https://example.com")
browser.take_screenshot("example.png")
browser.close()

Agent-Specific Examples

For Facet (Onshape Learning)
from browser_core import BrowserAutomation
from facets_onshape import OnshapeAutomation

browser = BrowserAutomation()
onshape = OnshapeAutomation(browser)

# Login to Onshape
onshape.login(email="facet.ai.oc@gmail.com", password="***")

# Navigate to tutorials
onshape.navigate_to_tutorial("getting-started")

# Complete tutorial steps
onshape.complete_tutorial_step(1)
onshape.take_progress_screenshot()
For Ace (Competition Entry)
from browser_core import BrowserAutomation
from ace_competition import CompetitionAutomation

browser = BrowserAutomation()
competition = CompetitionAutomation(browser)

# Navigate to competition
competition.navigate_to_competition("https://competition.example.com")

# Fill entry form
entry_data = {
    "name": "Stef Ferreira",
    "email": "ace@supplystoreafrica.com",
    "phone": "+27726386189"
}
competition.fill_entry_form(entry_data)

# Submit and capture proof
competition.submit_entry()
competition.capture_submission_proof()

Configuration

Environment Variables

# Browser settings
export BROWSER_HEADLESS="true"           # Run without display
export BROWSER_TIMEOUT="30"              # Default timeout seconds
export BROWSER_VIEWPORT="1280,720"       # Window size
export BROWSER_USER_AGENT="OpenClaw Agent" # Custom user agent

# CDP settings (OpenClaw browser)
export CDP_URL="http://localhost:18800/json"
export CDP_WEBSOCKET="ws://localhost:18800/devtools/page/..."

# Storage settings
export SCREENSHOT_DIR="/path/to/screenshots"
export SESSION_DIR="/path/to/sessions"

OpenClaw Integration

{
  "skills": {
    "browser-automation-core": {
      "enabled": true,
      "config": {
        "cdpUrl": "http://localhost:18800/json",
        "headless": true,
        "timeout": 30,
        "screenshotDir": "/root/.openclaw/workspace/screenshots"
      }
    }
  }
}

Implementation Details

CDP (Chrome DevTools Protocol)

This skill uses OpenClaw's built-in browser via CDP:

  • Connection: WebSocket to ws://localhost:18800/devtools/page/...
  • Commands: Standard CDP methods (Page.navigate, DOM.querySelector, etc.)
  • Events: Async event handling for page loads, network requests

Error Handling

  • Retry logic: Automatic retry on network failures
  • Timeout management: Configurable timeouts per operation
  • Fallback strategies: Alternative selectors, different interaction methods
  • Recovery procedures: Page reload, session restore

Performance

  • Connection pooling: Reuse WebSocket connections
  • Command batching: Batch CDP commands when possible
  • Caching: Cache page structure, element positions
  • Parallel operations: Async operations where safe

Extension Points

Creating Agent-Specific Extensions

1. Create Extension Skill
python3 /usr/lib/node_modules/openclaw/skills/skill-creator/scripts/init_skill.py facets-browser-learning
2. Import Core Library
# In extension skill
import sys
sys.path.append("/root/.openclaw/workspace/skills/browser-automation-core")
from browser_core import BrowserAutomation

class OnshapeAutomation:
    def __init__(self):
        self.browser = BrowserAutomation()
    
    def onshape_specific_method(self):
        # Use core capabilities
        self.browser.navigate("https://cad.onshape.com")
        # Add Onshape-specific logic
3. Add Specialized Logic
  • Site-specific selectors (Onshape CSS classes, competition form fields)
  • Domain-specific workflows (tutorial navigation, competition rules)
  • Custom capture requirements (progress tracking, entry proof)
  • Error handling for specific sites

Testing Strategy

Unit Tests

# Test core functionality
cd /root/.openclaw/workspace/skills/browser-automation-core
python3 -m pytest tests/unit/

Integration Tests

# Test with actual browser
python3 tests/integration/test_navigation.py
python3 tests/integration/test_forms.py

Agent-Specific Tests

# Test Facet extension
cd /root/.openclaw/workspace/skills/facets-browser-learning
python3 tests/test_onshape_automation.py

# Test Ace extension  
cd /root/.openclaw/workspace/skills/ace-competition-automation
python3 tests/test_competition_automation.py

Common Use Cases

Use Case 1: Form Filling (Ace)

# Competition entry automation
data = {
    "full_name": "Stef Ferreira",
    "email": "ace@supplystoreafrica.com",
    "phone": "+27726386189",
    "address": "123 Street, City, South Africa"
}

browser.navigate(competition_url)
browser.fill_form("form#entry-form", data)
browser.click("button[type='submit']")
browser.wait_for_element(".success-message")
browser.take_screenshot("entry_proof.png")

Use Case 2: Tutorial Navigation (Facet)

# Onshape learning automation
browser.navigate("https://cad.onshape.com")
browser.login(credentials)  # Custom method in extension
browser.navigate("/learning/tutorials")

# Complete tutorial
tutorial_steps = browser.extract_tutorial_steps()
for step in tutorial_steps:
    browser.complete_step(step)  # Custom method
    browser.take_screenshot(f"step_{step.number}.png")
    
browser.capture_certificate()

Use Case 3: Multi-Page Workflow

# Complex automation across multiple pages
browser.open_new_tab()
browser.navigate_to_login()
browser.login(credentials)

browser.switch_to_tab(0)
browser.fill_application_form(data)

browser.switch_to_tab(1)
browser.verify_email_confirmation()

browser.capture_all_tabs_screenshots()

Error Recovery Patterns

CORS Issues (Screenshots/Evaluate Not Working)

Problem: Browser automation fails with CORS errors when taking screenshots or evaluating JavaScript.

Solution: Ensure browser is started with --remote-allow-origins=* flag:

# Browser startup command must include:
--remote-debugging-port=18800 --remote-allow-origins=*

Verification:

curl http://localhost:18800/json/version
# Should return browser info without CORS errors

Network Issues

try:
    browser.navigate(url)
except NetworkError:
    browser.reload()
    browser.wait_for_network_idle()
    # Retry operation

Element Not Found

# Try multiple selectors
selectors = [
    "button.submit",
    "input[type='submit']",
    ".submit-button",
    "//button[contains(text(), 'Submit')]"
]

for selector in selectors:
    if browser.element_exists(selector):
        browser.click(selector)
        break

Form Validation Errors

browser.submit_form()
if browser.has_validation_errors():
    errors = browser.get_validation_errors()
    for field, message in errors:
        browser.fix_field(field, message)
    browser.submit_form()  # Retry

Performance Optimization

Batch Operations

# Instead of sequential commands
browser.click("button1")
browser.click("button2")
browser.type("input1", "text")

# Use batch commands
commands = [
    {"method": "click", "selector": "button1"},
    {"method": "click", "selector": "button2"},
    {"method": "type", "selector": "input1", "text": "text"}
]
browser.execute_batch(commands)

Caching Strategies

# Cache page structure
if not browser.has_cached_structure(url):
    structure = browser.extract_page_structure()
    browser.cache_structure(url, structure)

# Use cached selectors
selectors = browser.get_cached_selectors(url)

Security Considerations

Credential Management

  • Never hardcode credentials in scripts
  • Use environment variables or secure storage
  • Implement credential rotation
  • Log credential usage (without exposing values)

Session Isolation

  • Separate browser sessions per agent
  • Clear cookies and storage between sessions
  • Use incognito/private mode when possible
  • Implement session timeout

Input Validation

  • Validate all user inputs before browser interaction
  • Sanitize URLs to prevent navigation to malicious sites
  • Limit file system access from browser
  • Monitor for suspicious behavior

Maintenance

Versioning

  • Semantic versioning (MAJOR.MINOR.PATCH)
  • Backward compatibility for minor versions
  • Deprecation warnings for breaking changes
  • Migration guides between major versions

Updates

  • Monthly security updates
  • Quarterly feature updates
  • Annual architecture reviews
  • Continuous integration testing

Monitoring

  • Usage statistics (which agents use which features)
  • Error rates and common failures
  • Performance metrics (load times, success rates)
  • Agent-specific success tracking

Contributing

Adding New Features

  1. Check if feature belongs in core or extension
  2. Write tests for new functionality
  3. Update documentation
  4. Submit pull request

Reporting Issues

  1. Include agent context (Facet, Ace, etc.)
  2. Provide reproduction steps
  3. Include screenshots/logs
  4. Suggest possible solutions

Extension Development

  1. Follow core API patterns
  2. Reuse existing utilities when possible
  3. Write agent-specific tests
  4. Document extension capabilities

References

CDP Documentation

Related Skills

  • facets-browser-learning - Facet extension
  • ace-competition-automation - Ace extension
  • browser-testing - Testing utilities

External Resources


Version: 1.0.0 Last Updated: 2026-03-30 Maintainer: Bob (OpenClaw Agent) License: MIT Status: Active Development

平台分布

OpenClaw

74.25%
按下载量换算998

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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