| name | description |
|---|---|
page-analysis |
Analyze web page content, structure, and layout to understand what a page contains and how it is organized.
Trigger when the user asks to: analyze a page, understand page structure, inspect a website,
summarize page content, examine page layout, review a web page, or describe what is on a page.
|
Analyze and understand web page content, structure, and interactive elements using Python code execution. Produces a comprehensive breakdown of what is on the page and how it is organized.
All code runs in a persistent namespace via execute_code. All browser functions are async -- use await.
await navigate('https://example.com')
state = await browser.get_browser_state_summary()
print(f'Title: {state.title}')
print(f'URL: {state.url}')
print(f'Interactive elements: {len(state.dom_state.selector_map)}')
print(f'Tabs: {len(state.tabs)}')meta = await evaluate('''
(function(){
return {
title: document.title,
description: document.querySelector('meta[name="description"]')?.content,
canonical: document.querySelector('link[rel="canonical"]')?.href,
ogTitle: document.querySelector('meta[property="og:title"]')?.content,
ogImage: document.querySelector('meta[property="og:image"]')?.content,
lang: document.documentElement.lang,
charset: document.characterSet
};
})()
''')
import json
print(json.dumps(meta, indent=2))tech = await evaluate('''
(function(){
const t = [];
if (window.__NEXT_DATA__) t.push('Next.js');
if (window.__NUXT__) t.push('Nuxt.js');
if (document.querySelector('[data-reactroot]') || document.querySelector('#__next')) t.push('React');
if (document.querySelector('[ng-version]')) t.push('Angular');
if (window.jQuery) t.push('jQuery');
if (window.Vue) t.push('Vue.js');
if (document.querySelector('[data-svelte]')) t.push('Svelte');
return t;
})()
''')
print(f'Technologies detected: {tech}')stats = await evaluate('''
(function(){
return {
headings: document.querySelectorAll('h1,h2,h3,h4,h5,h6').length,
paragraphs: document.querySelectorAll('p').length,
images: document.querySelectorAll('img').length,
links: document.querySelectorAll('a').length,
forms: document.querySelectorAll('form').length,
tables: document.querySelectorAll('table').length,
lists: document.querySelectorAll('ul,ol').length,
buttons: document.querySelectorAll('button,[role="button"]').length,
inputs: document.querySelectorAll('input,textarea,select').length,
iframes: document.querySelectorAll('iframe').length,
scripts: document.querySelectorAll('script').length,
stylesheets: document.querySelectorAll('link[rel="stylesheet"]').length
};
})()
''')
import json
print('Content statistics:')
print(json.dumps(stats, indent=2))headings = await evaluate('''
(function(){
return Array.from(document.querySelectorAll('h1,h2,h3,h4,h5,h6')).map(h => ({
tag: h.tagName,
text: h.textContent.trim().substring(0, 80)
}));
})()
''')
for h in headings:
indent = ' ' * (int(h['tag'][1]) - 1)
print(f'{indent}{h["tag"]}: {h["text"]}')state = await browser.get_browser_state_summary()
elements_by_tag = {}
for idx, el in state.dom_state.selector_map.items():
tag = el.tag_name
elements_by_tag.setdefault(tag, []).append({
'index': idx,
'text': el.get_all_children_text(max_depth=1)[:50],
'type': el.attributes.get('type', ''),
'href': el.attributes.get('href', '')[:50] if el.attributes.get('href') else '',
})
for tag, elems in sorted(elements_by_tag.items()):
print(f'\n{tag} ({len(elems)} elements):')
for e in elems[:5]:
print(f' [{e["index"]}] text="{e["text"]}" type={e["type"]} href={e["href"]}')
if len(elems) > 5:
print(f' ... and {len(elems) - 5} more')dims = await evaluate('''
(function(){
return {
viewportWidth: window.innerWidth,
viewportHeight: window.innerHeight,
scrollHeight: document.body.scrollHeight,
scrollWidth: document.body.scrollWidth,
scrollable: document.body.scrollHeight > window.innerHeight
};
})()
''')
import json
print(json.dumps(dims, indent=2))
if dims['scrollable']:
pages = dims['scrollHeight'] / dims['viewportHeight']
print(f'Page is approximately {pages:.1f} viewport heights long')import re
# Get page text for Python-side analysis
text_content = await evaluate('document.body.innerText')
# Find emails
emails = re.findall(r'[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}', text_content)
print(f'Emails found: {emails}')
# Find phone numbers
phones = re.findall(r'\+?\d[\d\s()-]{7,}', text_content)
print(f'Phone numbers found: {phones}')
# Find dates
dates = re.findall(r'\d{4}-\d{2}-\d{2}|\w+ \d{1,2},? \d{4}', text_content)
print(f'Dates found: {dates}')- Start with
evaluate()for metadata and DOM statistics -- gives a fast structured overview. - Use
browser.get_browser_state_summary()for interactive element analysis. - Use Python regex on extracted text for pattern matching (emails, phones, dates, prices).
- For long pages, use
await scroll(down=True)and re-extract to analyze below-fold content. - Variables persist between calls, so you can build a comprehensive analysis incrementally.