This skill should be used when users need to scrape websites, extract structured data, handle JavaScript-heavy pages, crawl multiple URLs, or build automated web data pipelines. Includes optimized extraction patterns with schema generation for efficient, LLM-free extraction.
Resources
3Install
npx skillscat add brettdavies/crawl4ai-skill/crawl4ai Install via the SkillsCat registry.
Crawl4AI
Overview
Crawl4AI provides comprehensive web crawling and data extraction capabilities. This skill supports both CLI (recommended for quick tasks) and Python SDK (for programmatic control).
Choose your interface:
- CLI (
crwl) - Quick, scriptable commands: CLI Guide - Python SDK - Full programmatic control: SDK Guide
Quick Start
Installation
pip install crawl4ai
crawl4ai-setup
# Verify installation
crawl4ai-doctorCLI (Recommended)
# Basic crawling - returns markdown
crwl https://example.com
# Get markdown output
crwl https://example.com -o markdown
# JSON output with cache bypass
crwl https://example.com -o json -v --bypass-cache
# See more examples
crwl --examplePython SDK
import asyncio
from crawl4ai import AsyncWebCrawler
async def main():
async with AsyncWebCrawler() as crawler:
result = await crawler.arun("https://example.com")
print(result.markdown[:500])
asyncio.run(main())For SDK configuration details: SDK Guide - Configuration (lines 61-150)
Core Concepts
Configuration Layers
Both CLI and SDK use the same underlying configuration:
| Concept | CLI | SDK |
|---|---|---|
| Browser settings | -B browser.yml or -b "param=value" |
BrowserConfig(...) |
| Crawl settings | -C crawler.yml or -c "param=value" |
CrawlerRunConfig(...) |
| Extraction | -e extract.yml -s schema.json |
extraction_strategy=... |
| Content filter | -f filter.yml |
markdown_generator=... |
Key Parameters
Browser Configuration:
headless: Run with/without GUIviewport_width/height: Browser dimensionsuser_agent: Custom user agentproxy_config: Proxy settings
Crawler Configuration:
page_timeout: Max page load time (ms)wait_for: CSS selector or JS condition to wait forcache_mode: bypass, enabled, disabledjs_code: JavaScript to executecss_selector: Focus on specific element
For complete parameters: CLI Config | SDK Config
Output Content
Every crawl returns:
- markdown - Clean, formatted markdown
- html - Raw HTML
- links - Internal and external links discovered
- media - Images, videos, audio found
- extracted_content - Structured data (if extraction configured)
Markdown Generation (Primary Use Case)
Crawl4AI excels at generating clean, well-formatted markdown:
CLI
# Basic markdown
crwl https://docs.example.com -o markdown
# Filtered markdown (removes noise)
crwl https://docs.example.com -o markdown-fit
# With content filter
crwl https://docs.example.com -f filter_bm25.yml -o markdown-fitFilter configuration:
# filter_bm25.yml (relevance-based)
type: "bm25"
query: "machine learning tutorials"
threshold: 1.0Python SDK
from crawl4ai.content_filter_strategy import BM25ContentFilter
from crawl4ai.markdown_generation_strategy import DefaultMarkdownGenerator
bm25_filter = BM25ContentFilter(user_query="machine learning", bm25_threshold=1.0)
md_generator = DefaultMarkdownGenerator(content_filter=bm25_filter)
config = CrawlerRunConfig(markdown_generator=md_generator)
result = await crawler.arun(url, config=config)
print(result.markdown.fit_markdown) # Filtered
print(result.markdown.raw_markdown) # OriginalFor content filters: Content Processing (lines 2481-3101)
Data Extraction
1. Schema-Based CSS Extraction (Most Efficient)
No LLM required - fast, deterministic, cost-free.
CLI:
# Generate schema once (uses LLM)
python scripts/extraction_pipeline.py --generate-schema https://shop.com "extract products"
# Use schema for extraction (no LLM)
crwl https://shop.com -e extract_css.yml -s product_schema.json -o jsonSchema format:
{
"name": "products",
"baseSelector": ".product-card",
"fields": [
{"name": "title", "selector": "h2", "type": "text"},
{"name": "price", "selector": ".price", "type": "text"},
{"name": "link", "selector": "a", "type": "attribute", "attribute": "href"}
]
}2. LLM-Based Extraction
For complex or irregular content:
CLI:
# extract_llm.yml
type: "llm"
provider: "openai/gpt-4o-mini"
instruction: "Extract product names and prices"
api_token: "your-token"crwl https://shop.com -e extract_llm.yml -o jsonFor extraction details: Extraction Strategies (lines 4522-5429)
Advanced Patterns
Dynamic Content (JavaScript-Heavy Sites)
CLI:
crwl https://example.com -c "wait_for=css:.ajax-content,scan_full_page=true,page_timeout=60000"Crawler config:
# crawler.yml
wait_for: "css:.ajax-content"
scan_full_page: true
page_timeout: 60000
delay_before_return_html: 2.0Multi-URL Processing
CLI (sequential):
for url in url1 url2 url3; do crwl "$url" -o markdown; donePython SDK (concurrent):
urls = ["https://site1.com", "https://site2.com", "https://site3.com"]
results = await crawler.arun_many(urls, config=config)For batch processing: arun_many() Reference (lines 1057-1224)
Session & Authentication
CLI:
# login_crawler.yml
session_id: "user_session"
js_code: |
document.querySelector('#username').value = 'user';
document.querySelector('#password').value = 'pass';
document.querySelector('#submit').click();
wait_for: "css:.dashboard"# Login
crwl https://site.com/login -C login_crawler.yml
# Access protected content (session reused)
crwl https://site.com/protected -c "session_id=user_session"For session management: Advanced Features (lines 5429-5940)
Anti-Detection & Proxies
CLI:
# browser.yml
headless: true
proxy_config:
server: "http://proxy:8080"
username: "user"
password: "pass"
user_agent_mode: "random"crwl https://example.com -B browser.ymlCommon Use Cases
Documentation to Markdown
crwl https://docs.example.com -o markdown > docs.mdE-commerce Product Monitoring
# Generate schema once
python scripts/extraction_pipeline.py --generate-schema https://shop.com "extract products"
# Monitor (no LLM costs)
crwl https://shop.com -e extract_css.yml -s schema.json -o jsonNews Aggregation
# Multiple sources with filtering
for url in news1.com news2.com news3.com; do
crwl "https://$url" -f filter_bm25.yml -o markdown-fit
doneInteractive Q&A
# First view content
crwl https://example.com -o markdown
# Then ask questions
crwl https://example.com -q "What are the main conclusions?"
crwl https://example.com -q "Summarize the key points"Resources
Provided Scripts
- scripts/extraction_pipeline.py - Schema generation and extraction
- scripts/basic_crawler.py - Simple markdown extraction
- scripts/batch_crawler.py - Multi-URL processing
Reference Documentation
| Document | Purpose |
|---|---|
| CLI Guide | Command-line interface reference |
| SDK Guide | Python SDK quick reference |
| Complete SDK Reference | Full API documentation (5900+ lines) |
Best Practices
- Start with CLI for quick tasks, SDK for automation
- Use schema-based extraction - 10-100x more efficient than LLM
- Enable caching during development -
--bypass-cacheonly when needed - Set appropriate timeouts - 30s normal, 60s+ for JS-heavy sites
- Use content filters for cleaner, focused markdown
- Respect rate limits - Add delays between requests
Troubleshooting
JavaScript Not Loading
crwl https://example.com -c "wait_for=css:.dynamic-content,page_timeout=60000"Bot Detection Issues
crwl https://example.com -B browser.yml# browser.yml
headless: false
viewport_width: 1920
viewport_height: 1080
user_agent: "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36"Content Not Extracted
# Debug: see full output
crwl https://example.com -o all -v
# Try different wait strategy
crwl https://example.com -c "wait_for=js:document.querySelector('.content')!==null"Session Issues
# Verify session
crwl https://site.com -c "session_id=test" -o all | grep -i sessionFor comprehensive API documentation, see Complete SDK Reference.