Crawl Websites At Scale Agent Skill

# pip
pip install scrapy

# Ubuntu/Debian
sudo apt-get install -y python3-pip && pip install scrapy

# macOS
brew install python && pip install scrapy

# Verify installation
scrapy version

# Create a new Scrapy project
scrapy startproject myproject
cd myproject

# Generate a spider
scrapy genspider quotes quotes.toscrape.com

# Run the spider and save to JSON
scrapy crawl quotes -o output.json

# Run the spider and save to CSV
scrapy crawl quotes -o output.csv

import scrapy

class QuotesSpider(scrapy.Spider):
    name = "quotes"
    start_urls = ["https://quotes.toscrape.com"]

    def parse(self, response):
        for quote in response.css("div.quote"):
            yield {
                "text": quote.css("span.text::text").get(),
                "author": quote.css("small.author::text").get(),
                "tags": quote.css("a.tag::text").getall(),
            }

        # Follow pagination links
        next_page = response.css("li.next a::attr(href)").get()
        if next_page:
            yield response.follow(next_page, self.parse)

# Run with custom settings (rate limiting, retries)
scrapy crawl quotes \
  -s DOWNLOAD_DELAY=1 \
  -s AUTOTHROTTLE_ENABLED=True \
  -s RETRY_TIMES=3 \
  -o output.json

# Run from a script (no project required)
scrapy runspider spider.py -o output.json

import scrapy
from scrapy import signals
from scrapy.crawler import CrawlerProcess

class ArticleSpider(scrapy.Spider):
    name = "articles"
    custom_settings = {
        "DOWNLOAD_DELAY": 1,
        "AUTOTHROTTLE_ENABLED": True,
        "AUTOTHROTTLE_START_DELAY": 1,
        "AUTOTHROTTLE_MAX_DELAY": 10,
        "ROBOTSTXT_OBEY": True,
        "USER_AGENT": "open-skills-bot/1.0 (+https://github.com/besoeasy/open-skills)",
        "RETRY_TIMES": 3,
        "FEEDS": {"output.json": {"format": "json"}},
    }

    def __init__(self, start_url=None, *args, **kwargs):
        super().__init__(*args, **kwargs)
        self.start_urls = [start_url or "https://quotes.toscrape.com"]

    def parse(self, response):
        for article in response.css("article, div.post, div.entry"):
            yield {
                "url": response.url,
                "title": article.css("h1::text, h2::text").get("").strip(),
                "body": " ".join(article.css("p::text").getall()),
            }

        for link in response.css("a::attr(href)").getall():
            if link.startswith("/") or response.url in link:
                yield response.follow(link, self.parse)

    def errback(self, failure):
        self.logger.error(f"Request failed: {failure.request.url} — {failure.value}")


# Run without a Scrapy project
if __name__ == "__main__":
    process = CrawlerProcess()
    process.crawl(ArticleSpider, start_url="https://quotes.toscrape.com")
    process.start()

import scrapy

class XPathSpider(scrapy.Spider):
    name = "xpath_example"
    start_urls = ["https://quotes.toscrape.com"]

    def parse(self, response):
        for quote in response.xpath("//div[@class='quote']"):
            yield {
                "text": quote.xpath(".//span[@class='text']/text()").get(),
                "author": quote.xpath(".//small[@class='author']/text()").get(),
                "tags": quote.xpath(".//a[@class='tag']/text()").getall(),
            }

{
  "text": "The world as we have created it is a process of our thinking.",
  "author": "Albert Einstein",
  "tags": ["change", "deep-thoughts", "thinking", "world"]
}

You have scrapy web-scraping capability. When a user asks to scrape or crawl a website:

1. Confirm the target URL and data fields to extract (e.g., title, price, link)
2. Create a Scrapy spider using CSS or XPath selectors to target those fields
3. Enable ROBOTSTXT_OBEY=True and set DOWNLOAD_DELAY>=1 to be polite
4. Follow pagination links if the user needs data across multiple pages
5. Save results to output.json or output.csv

Always identify your bot with a descriptive USER_AGENT and never scrape login-protected or paywalled content.