Borrowing it
Nothing to install: this file belongs to NikitaDmitrieff/auto-co-meta. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/NikitaDmitrieff/auto-co-meta/main/.claude/skills/web-scraping/SKILL.mdgit clone --depth 1 https://github.com/NikitaDmitrieff/auto-co-metaWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/nikitadmitrieff/auto-co-meta/web-scraping)<a href="https://agentmods.dev/skills/nikitadmitrieff/auto-co-meta/web-scraping"><img src="https://agentmods.dev/badge/skills/nikitadmitrieff/auto-co-meta/web-scraping/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/nikitadmitrieff/auto-co-meta/web-scraping"><img src="https://agentmods.dev/badge/skills/nikitadmitrieff/auto-co-meta/web-scraping.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00065 | $0.04488 |
| Opus 5 | $0.00032 | $0.02244 |
| Sonnet 5 | $0.00013 | $0.00898 |
| Haiku 4.5 | $0.00006 | $0.00449 |
Grade A, and why
web-scraping scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
def fetch(self, url: str) -> Optional[ScrapingResult]: ... How it starts
The opening of the file, as written. The whole thing — 619 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Web scraping methodology
Patterns for reliable, ethical web scraping with fallback strategies and anti-bot handling.
Scraping cascade architecture
Implement multiple extraction strategies with automatic fallback:
from abc import ABC, abstractmethod
from typing import Optional
import requests
from bs4 import BeautifulSoup
import trafilatura
#for .py files
from playwright.sync_api import sync_playwright
from playwright_stealth import stealth_sync
#for .ipynb files
import asyncio
from playwright.async_api import async_playwright
class ScrapingResult:
def __init__(self, content: str, title: str, method: str):
self.content = content
self.title = title
self.method = method # Track which method succeeded
class Scraper(ABC):
@abstractmethod
def fetch(self, url: str) -> Optional[ScrapingResult]: ...
class TrafilaturaСscraper(Scraper):
"""Fast, lightweight extraction for standard articles."""
def fetch(self, url: str) -> Optional[ScrapingResult]:
try:
downloaded = trafilatura.fetch_url(url)
if not downloaded:
return None
content = trafilatura.extract(
downloaded,
include_comments=False,
include_tables=True,
favor_recall=True
)
if not content or len(content) < 100:
return None
# Extract title separately
soup = BeautifulSoup(downloaded, 'html.parser')
title = soup.find('title')
title_text = title.get_text() if title else ''
return ScrapingResult(content, title_text, 'trafilatura')
except Exception:
return None
class RequestsScraper(Scraper):
"""HTTP requests with rotating user agents."""
USER_AGENTS = [
'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36',
'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36',
'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36',
]
def fetch(self, url: str) -> Optional[ScrapingResult]:
import random
headers = {
'User-Agent': random.choice(self.USER_AGENTS),
'Accept': 'text/html,application/xhtml+xml',
'Accept-Language': 'en-US,en;q=0.9',
}
try:
response = requests.get(url, headers=headers, timeout=30)
response.raise_for_status()
soup = BeautifulSoup(response.text, 'html.parser')
# Remove script/style elements
for element in soup(['script', 'style', 'nav', 'footer', 'aside']):
element.decompose()
# Find main content
main = soup.find('main') or soup.find('article') or soup.find('body')
content = main.get_text(separator='\n', strip=True) if main else ''
title = soup.find('title')
title_text = title.get_text() if title else ''
if len(content) < 100:
return None
return ScrapingResult(content, title_text, 'requests')
except Exception:
return None
class PlaywrightScraper(Scraper):
"""Heavy JavaScript rendering with stealth mode for anti-bot bypass."""
def fetch(self, url: str) -> Optional[ScrapingResult]:
try:
with sync_playwright() as p:
browser = p.chromium.launch(headless=True)
context = browser.new_context(
viewport={'width': 1920, 'height': 1080},
user_agent='Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36'
)
page = context.new_page()
# Apply stealth to avoid detection
stealth_sync(page)
page.goto(url, wait_until='networkidle', timeout=60000)
# Wait for content to load
page.wait_for_timeout(2000)
# Extract content
content = page.evaluate('''() => {
const article = document.querySelector('article, main, .content, #content');
return article ? article.innerText : document.body.innerText;
}''')
title = page.title()
browser.close()
if len(content) < 100:
return None
return ScrapingResult(content, title, 'playwright')
except Exception:
return None
class PlaywrightScraperAsync:
"""Async Playwright scraper for Jupyter notebooks (.ipynb files).
Jupyter notebooks run their own event loop, so sync Playwright won't work.
Use this async version with `await` in notebook cells.
"""
async def fetch(self, url: str) -> Optional[ScrapingResult]:
try:
async with async_playwright() as p:
browser = await p.chromium.launch(headless=True)
context = await browser.new_context(
viewport={'width': 1920, 'height': 1080},
user_agent='Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36'
)
page = await context.new_page()
# Note: playwright-stealth async version
# from playwright_stealth import stealth_async
# await stealth_async(page)
await page.goto(url, wait_until='networkidle', timeout=60000)
# Wait for content to load
await page.wait_for_timeout(2000)
# Extract content
content = await page.evaluate('''() => {
const article = document.querySelector('article, main, .content, #content');
return article ? article.innerText : document.body.innerText;
}''')
title = await page.title()
await browser.close()
if len(content) < 100:
return None
return ScrapingResult(content, title, 'playwright_async')
except Exception:
return None
# Usage in Jupyter notebook cells:
# scraper = PlaywrightScraperAsync()
# result = await scraper.fetch('https://example.com')
class ScrapingCascade:
"""Try multiple scrapers in order until one succeeds."""
def __init__(self):
self.scrapers = [
TrafilaturaСscraper(),
RequestsScraper(),
PlaywrightScraper(),
]
def fetch(self, url: str) -> Optional[ScrapingResult]:
for scraper in self.scrapers:
result = scraper.fetch(url)
if result:
return result
return None
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 619 lines · 65 tokens per session scan A 971f92ae1817
web-scraping is a skill published in the GitHub repository NikitaDmitrieff/auto-co-meta (43 stars, last pushed 2mo ago), licensed MIT. It adds 65 tokens to every session and 4,488 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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