Intelligent web page fetcher that converts any URL into clean, readable Markdown content. Uses a multi-layer fallback strategy to ensure maximum compatibility.

💰 Pricing: 0.001 USDT per web fetch

⚠️ CRITICAL: Payment Integration (MUST READ FIRST)

This skill is monetized via SkillPay. Before fetching ANY URL, you MUST execute the payment verification step.

Payment Configuration

# ═══════════════════════════════════════════════════
# SkillPay Billing Integration
# ═══════════════════════════════════════════════════
import requests
BILLING_API_URL = 'https://skillpay.me'
BILLING_API_KEY = 'sk_d6d26f291dafc43acc8c2b6215b87cbc9b19c7d093aebdb2deeba42a3a0fea4b'
SKILL_ID = '4fb2d57e-e583-4ca3-8170-52df37a6572b'
HEADERS = {'X-API-Key': BILLING_API_KEY, 'Content-Type': 'application/json'}

Billing API Functions (MANDATORY)

⚠️ THIS CODE MUST BE EXECUTED BEFORE ANY WEB FETCH:

import requests
import os
BILLING_API_URL = 'https://skillpay.me'
BILLING_API_KEY = 'sk_d6d26f291dafc43acc8c2b6215b87cbc9b19c7d093aebdb2deeba42a3a0fea4b'
SKILL_ID = '4fb2d57e-e583-4ca3-8170-52df37a6572b'
HEADERS = {'X-API-Key': BILLING_API_KEY, 'Content-Type': 'application/json'}
# ① Check balance / 查余额
def check_balance(user_id: str) -> float:
    resp = requests.get(
        f'{BILLING_API_URL}/api/v1/billing/balance',
        params={'user_id': user_id},
        headers=HEADERS
    )
    return resp.json()['balance']  # USDT amount
# ② Charge per call / 每次调用扣费
def charge_user(user_id: str) -> dict:
    resp = requests.post(
        f'{BILLING_API_URL}/api/v1/billing/charge',
        headers=HEADERS,
        json={
            'user_id': user_id,
            'skill_id': SKILL_ID,
            'amount': 0.001,  # USDT per call
        }
    )
    data = resp.json()
    if data['success']:
        return {'ok': True, 'balance': data['balance']}
    # Insufficient balance → auto returns BNB Chain USDT payment link
    return {'ok': False, 'balance': data['balance'], 'payment_url': data.get('payment_url')}
# ③ Generate payment link / 生成充值链接
def get_payment_link(user_id: str, amount: float) -> str:
    resp = requests.post(
        f'{BILLING_API_URL}/api/v1/billing/payment-link',
        headers=HEADERS,
        json={'user_id': user_id, 'amount': amount}
    )
    return resp.json()['payment_url']  # BNB Chain USDT
USER_ID = os.environ.get("SKILLPAY_USER_ID", "anonymous_user")

Payment Workflow Integration

# ========================================
# STEP 0: CHARGE USER (MANDATORY)
# ========================================
# This must be the FIRST step before ANY web fetch
charge_result = charge_user(USER_ID)
if not charge_result['ok']:
    print(f"""
╔══════════════════════════════════════════════════════════════╗
║  💳 INSUFFICIENT BALANCE                                      ║
║                                                               ║
║  This web fetch costs 0.001 USDT.                            ║
║  Current balance: {charge_result['balance']:<41}║
║                                                               ║
║  Please top up at:                                            ║
║  {charge_result['payment_url']:<56}║
║                                                               ║
║  After payment, please retry your request.                   ║
╚══════════════════════════════════════════════════════════════╝
    """)
    raise SystemExit("Insufficient balance for web fetch")
print(f"✅ Charged 0.001 USDT. Remaining balance: {charge_result['balance']} USDT")

多层抓取策略 (Multi-Layer Fetch Strategy)

本 skill 采用智能多层回退策略，确保最大兼容性：

Layer 1: markdown.new（首选，最快）

Cloudflare 驱动的 URL→Markdown 转换服务，内置三层回退：

• 原生 Markdown: Accept: text/markdown 内容协商
• Workers AI: HTML→Markdown AI 转换
• 浏览器渲染: 无头浏览器处理 JS 重度页面

import requests
def fetch_via_markdown_new(url: str, method: str = "auto", retain_images: bool = True) -> str:
    """
    Layer 1: 使用 markdown.new 抓取网页
    
    Args:
        url: 目标网页 URL
        method: 转换方法 - "auto" | "ai" | "browser"
        retain_images: 是否保留图片链接
    
    Returns:
        str: Markdown 格式的网页内容
    """
    api_url = "https://markdown.new/"
    
    try:
        response = requests.post(
            api_url,
            headers={"Content-Type": "application/json"},
            json={
                "url": url,
                "method": method,
                "retain_images": retain_images
            },
            timeout=60
        )
        
        if response.status_code == 200:
            token_count = response.headers.get("x-markdown-tokens", "unknown")
            print(f"✅ [markdown.new] 抓取成功 (tokens: {token_count})")
            return response.text
        elif response.status_code == 429:
            print("⚠️ [markdown.new] 速率限制，切换到下一层...")
            return None
        else:
            print(f"⚠️ [markdown.new] 返回状态码 {response.status_code}，切换到下一层...")
            return None
            
    except requests.exceptions.RequestException as e:
        print(f"⚠️ [markdown.new] 请求失败: {e}，切换到下一层...")
        return None

支持的查询参数:

• method=auto|ai|browser - 指定转换方法
• retain_images=true|false - 是否保留图片
• 速率限制: 每 IP 每天 500 次请求

Layer 2: defuddle.md（备选方案）

开源的网页→Markdown 提取服务，由 Obsidian Web Clipper 创建者开发。

def fetch_via_defuddle(url: str) -> str:
    """
    Layer 2: 使用 defuddle.md 抓取网页
    
    Args:
        url: 目标网页 URL（不含 https:// 前缀亦可）
    
    Returns:
        str: 带有 YAML frontmatter 的 Markdown 内容
    """
    # defuddle 接受 URL 路径直接拼接
    clean_url = url.replace("https://", "").replace("http://", "")
    api_url = f"https://defuddle.md/{clean_url}"
    
    try:
        response = requests.get(api_url, timeout=60)
        
        if response.status_code == 200 and len(response.text.strip()) > 50:
            print(f"✅ [defuddle.md] 抓取成功")
            return response.text
        else:
            print(f"⚠️ [defuddle.md] 内容为空或失败 (status: {response.status_code})，切换到下一层...")
            return None
            
    except requests.exceptions.RequestException as e:
        print(f"⚠️ [defuddle.md] 请求失败: {e}，切换到下一层...")
        return None

Layer 3: Jina Reader（AI 内容提取）

Jina AI 的阅读器服务，擅长处理复杂页面。

def fetch_via_jina(url: str) -> str:
    """
    Layer 3: 使用 Jina Reader 抓取网页
    
    Args:
        url: 目标网页完整 URL
    
    Returns:
        str: 提取的主要文本内容
    """
    api_url = f"https://r.jina.ai/{url}"
    
    try:
        response = requests.get(
            api_url,
            headers={"Accept": "text/markdown"},
            timeout=60
        )
        
        if response.status_code == 200 and len(response.text.strip()) > 50:
            print(f"✅ [Jina Reader] 抓取成功")
            return response.text
        else:
            print(f"⚠️ [Jina Reader] 内容为空或失败 (status: {response.status_code})，切换到下一层...")
            return None
            
    except requests.exceptions.RequestException as e:
        print(f"⚠️ [Jina Reader] 请求失败: {e}，切换到下一层...")
        return None

额外功能: Jina 还支持搜索模式 https://s.jina.ai/YOUR_SEARCH_QUERY

Layer 4: Scrapling（终极兜底，反反爬）

强大的自适应爬虫框架，可绕过 Cloudflare Turnstile 等反爬机制。

# 安装 Scrapling
pip install scrapling
# 如需浏览器功能（反反爬）
pip install "scrapling[fetchers]"
scrapling install

def fetch_via_scrapling(url: str, use_stealth: bool = False) -> str:
    """
    Layer 4: 使用 Scrapling 抓取网页（终极兜底方案）
    
    Args:
        url: 目标网页 URL
        use_stealth: 是否使用隐身模式（绕过 Cloudflare 等）
    
    Returns:
        str: 提取的网页文本内容
    """
    try:
        if use_stealth:
            from scrapling.fetchers import StealthyFetcher
            page = StealthyFetcher.fetch(url)
        else:
            from scrapling.fetchers import Fetcher
            page = Fetcher.get(url)
        
        if page and page.status == 200:
            # 提取主要文本内容
            # 移除脚本和样式标签
            for tag in page.css('script, style, nav, footer, header'):
                tag.remove()
            
            # 获取主要内容区域
            main_content = (
                page.css('article') or 
                page.css('main') or 
                page.css('.content, .post, .article, #content') or
                page.css('body')
            )
            
            if main_content:
                text = main_content[0].text_content
                print(f"✅ [Scrapling{'(Stealth)' if use_stealth else ''}] 抓取成功")
                return text
            
        print(f"⚠️ [Scrapling] 抓取失败或内容为空")
        return None
        
    except ImportError:
        print("⚠️ [Scrapling] 未安装，请运行: pip install scrapling")
        return None
    except Exception as e:
        print(f"⚠️ [Scrapling] 抓取失败: {e}")
        return None

Workflow

Phase 0: Payment Verification (MANDATORY - DO NOT SKIP)

⚠️ CRITICAL: This phase MUST be completed BEFORE any other phase. DO NOT proceed without payment verification.

• Execute payment verification code (see Payment Verification Code section above)
• If payment fails: Return the payment URL to user and STOP
• If payment succeeds: Proceed to Phase 1

Phase 1: URL Analysis & Strategy Selection (MANDATORY)

当用户提供需要抓取的 URL 时：

• 接收 URL: 用户提供目标网址
• 分析 URL 特征: 判断网站类型和最佳抓取策略

| URL 特征 | 推荐策略 | |----------|----------| | 普通网页/博客/文档 | Layer 1 (markdown.new) → 自动回退 | | GitHub/技术文档 | Layer 1 (markdown.new) → Layer 3 (Jina) | | 需要登录/付费墙 | 提示用户需要认证，无法自动抓取 | | JavaScript 重度渲染 (SPA) | Layer 1 (markdown.new, method=browser) → Layer 4 (Scrapling) | | 反爬严格的网站 | Layer 4 (Scrapling, stealth mode) |

• 告知用户费用: "本次抓取将收取 0.001 USDT"

Phase 2: Execute Fetch (WITH PAYMENT)

⚠️ IMPORTANT: Execute payment verification BEFORE fetching!

使用以下智能抓取函数，自动按层级回退：

import requests
import os
# ═══════════════════════════════════════════════════
# STEP 0: SKILLPAY BILLING (MANDATORY)
# ═══════════════════════════════════════════════════
BILLING_API_URL = 'https://skillpay.me'
BILLING_API_KEY = 'sk_d6d26f291dafc43acc8c2b6215b87cbc9b19c7d093aebdb2deeba42a3a0fea4b'
SKILL_ID = '4fb2d57e-e583-4ca3-8170-52df37a6572b'
HEADERS = {'X-API-Key': BILLING_API_KEY, 'Content-Type': 'application/json'}
def charge_user(user_id: str) -> dict:
    resp = requests.post(
        f'{BILLING_API_URL}/api/v1/billing/charge',
        headers=HEADERS,
        json={'user_id': user_id, 'skill_id': SKILL_ID, 'amount': 0.001}
    )
    data = resp.json()
    if data['success']:
        return {'ok': True, 'balance': data['balance']}
    return {'ok': False, 'balance': data['balance'], 'payment_url': data.get('payment_url')}
USER_ID = os.environ.get("SKILLPAY_USER_ID", "anonymous_user")
charge_result = charge_user(USER_ID)
if not charge_result['ok']:
    print(f"""
╔══════════════════════════════════════════════════════════════╗
║  💳 INSUFFICIENT BALANCE                                      ║
║                                                               ║
║  This web fetch costs 0.001 USDT.                            ║
║  Current balance: {charge_result['balance']:<41}║
║                                                               ║
║  Please top up at (BNB Chain USDT):                          ║
║  {charge_result['payment_url']:<56}║
║                                                               ║
║  After payment, please retry your request.                   ║
╚══════════════════════════════════════════════════════════════╝
    """)
    raise SystemExit("Insufficient balance for web fetch")
print(f"✅ Charged 0.001 USDT. Remaining balance: {charge_result['balance']} USDT")
# ========================================
# STEP 1: INTELLIGENT MULTI-LAYER FETCH
# ========================================
def smart_fetch(url: str, prefer_method: str = "auto", retain_images: bool = True) -> dict:
    """
    智能多层抓取：自动按优先级尝试各层服务，直到成功。
    
    Args:
        url: 目标网页 URL
        prefer_method: markdown.new 的转换方法 ("auto", "ai", "browser")
        retain_images: 是否保留图片链接
    
    Returns:
        dict: {
            "success": bool,
            "content": str,        # Markdown 内容
            "source": str,         # 使用的抓取层级
            "url": str,            # 原始 URL
            "char_count": int      # 内容字符数
        }
    """
    # 确保 URL 有协议前缀
    if not url.startswith(("http://", "https://")):
        url = "https://" + url
    
    print(f"🔍 开始抓取: {url}")
    print("="  60)
    
    # --- Layer 1: markdown.new ---
    print("📡 Layer 1: 尝试 markdown.new ...")
    content = fetch_via_markdown_new(url, method=prefer_method, retain_images=retain_images)
    if content and len(content.strip()) > 100:
        return {"success": True, "content": content, "source": "markdown.new", "url": url, "char_count": len(content)}
    
    # --- Layer 2: defuddle.md ---
    print("📡 Layer 2: 尝试 defuddle.md ...")
    content = fetch_via_defuddle(url)
    if content and len(content.strip()) > 100:
        return {"success": True, "content": content, "source": "defuddle.md", "url": url, "char_count": len(content)}
    
    # --- Layer 3: Jina Reader ---
    print("📡 Layer 3: 尝试 Jina Reader ...")
    content = fetch_via_jina(url)
    if content and len(content.strip()) > 100:
        return {"success": True, "content": content, "source": "jina-reader", "url": url, "char_count": len(content)}
    
    # --- Layer 4: Scrapling (常规模式) ---
    print("📡 Layer 4a: 尝试 Scrapling (常规模式) ...")
    content = fetch_via_scrapling(url, use_stealth=False)
    if content and len(content.strip()) > 100:
        return {"success": True, "content": content, "source": "scrapling", "url": url, "char_count": len(content)}
    
    # --- Layer 4b: Scrapling (隐身模式) ---
    print("📡 Layer 4b: 尝试 Scrapling (隐身模式) ...")
    content = fetch_via_scrapling(url, use_stealth=True)
    if content and len(content.strip()) > 100:
        return {"success": True, "content": content, "source": "scrapling-stealth", "url": url, "char_count": len(content)}
    
    # 所有方法失败
    print("❌ 所有抓取方法均失败")
    return {"success": False, "content": None, "source": None, "url": url, "char_count": 0}

# ========================================
# 执行抓取
# ========================================
TARGET_URL = "{用户提供的 URL}"
result = smart_fetch(TARGET_URL)
if result["success"]:
    print(f"""
╔══════════════════════════════════════════════════════════════╗
║  ✅ 抓取成功                                                  ║
║                                                               ║
║  来源: {result['source']:<52}║
║  字符数: {result['char_count']:<50}║
║  URL: {result['url'][:50]:<52}║
╚══════════════════════════════════════════════════════════════╝
    """)
    
    # 输出 Markdown 内容
    print("\n--- 网页内容 (Markdown) ---\n")
    print(result["content"])
else:
    print(f"""
╔══════════════════════════════════════════════════════════════╗
║  ❌ 抓取失败                                                  ║
║                                                               ║
║  所有 4 层抓取方法均无法获取内容。                              ║
║  可能的原因:                                                   ║
║  - 目标网站需要登录/认证                                       ║
║  - 目标 URL 无效或不可达                                       ║
║  - 目标网站有极强的反爬机制                                     ║
║                                                               ║
║  建议:                                                        ║
║  - 检查 URL 是否正确                                          ║
║  - 尝试提供需要登录后的页面源码                                 ║
╚══════════════════════════════════════════════════════════════╝
    """)

Phase 3: Content Processing & Output

抓取成功后：

• 直接返回 Markdown 内容给用户
• 如果内容过长（超过 50000 字符），进行智能截取并提示用户
• 记录交易 ID 用于支付追踪

# 内容后处理
def process_content(content: str, max_chars: int = 50000) -> str:
    """处理和截取过长内容"""
    if len(content) <= max_chars:
        return content
    
    # 智能截取：在段落边界截断
    truncated = content[:max_chars]
    last_newline = truncated.rfind('\n\n')
    if last_newline > max_chars  0.8:
        truncated = truncated[:last_newline]
    
    truncated += f"\n\n---\n⚠️ 内容过长，已截取前 {len(truncated)} 字符（共 {len(content)} 字符）。"
    return truncated

使用场景示例

场景 1: 抓取技术文档

用户: 帮我抓取 https://docs.python.org/3/tutorial/index.html 的内容

执行流程:

• 支付验证 → 通过
• Layer 1 (markdown.new) → 尝试抓取
• 返回 Markdown 格式的 Python 教程内容

场景 2: 抓取 GitHub README

用户: 我想看看这个库的介绍 https://github.com/D4Vinci/Scrapling

执行流程:

• 支付验证 → 通过
• Layer 1 (markdown.new) → GitHub 页面通常成功
• 返回 Scrapling 项目的 README 内容

场景 3: 抓取反爬网站

用户: 帮我抓取这个网页 https://某反爬网站.com/article/123

执行流程:

• 支付验证 → 通过
• Layer 1 → 失败
• Layer 2 → 失败
• Layer 3 → 失败
• Layer 4 (Scrapling Stealth) → 使用隐身模式绕过反爬
• 返回提取的内容

场景 4: 搜索信息（使用 Jina Search）

用户: 帮我搜一下 "Python asyncio best practices 2025"

def search_via_jina(query: str) -> str:
    """使用 Jina Search 搜索信息"""
    api_url = f"https://s.jina.ai/{query}"
    
    try:
        response = requests.get(api_url, timeout=60)
        if response.status_code == 200:
            return response.text
        return None
    except:
        return None
# 执行搜索
search_result = search_via_jina("Python asyncio best practices 2025")
print(search_result)

Prerequisites (按需安装)

基础依赖（Layer 1-3 只需 requests）

pip install requests

Scrapling 依赖（Layer 4 - 仅在需要时安装）

# 基础安装
pip install scrapling
# 完整安装（含浏览器和反反爬功能）
pip install "scrapling[fetchers]"
scrapling install

💰 Revenue & Analytics

Track your earnings in real-time at SkillPay Dashboard.

• Price per fetch: 0.001 USDT
• Your revenue share: 95%
• Settlement: Instant (BNB Chain)

Powered by SkillPay - AI Skill Monetization Infrastructure