Comment créer une page optimisée pour la citation par les modèles d'IA

import os, requests, json

API_KEY = os.environ['SCAVIO_API_KEY']
SH = {'x-api-key': API_KEY, 'Content-Type': 'application/json'}

def check_ao_citations(keyword):
    data = requests.post('https://api.scavio.dev/api/v1/search',
        headers=SH, json={'query': keyword, 'country_code': 'us',
                          'include_ai_overview': True}).json()
    ao = data.get('ai_overview', {})
    organic = data.get('organic_results', [])[:5]
    print(f'Query: "{keyword}"')
    print(f'  AI Overview: {"Present" if ao else "Not present"}')
    if ao:
        print(f'  AO content preview: {json.dumps(ao)[:150]}...')
    print(f'  Top organic results:')
    for r in organic[:3]:
        print(f'    #{r["position"]}: {r["title"][:50]} ({r["link"].split("/")[2]})')
    return {'ao': ao, 'organic': organic}

target_queries = ['best serp api 2026', 'serp api comparison', 'search api for ai agents']
for q in target_queries:
    check_ao_citations(q)
    print()

def generate_page_structure(topic, data_points):
    """Generate an AI-citation-optimized page structure."""
    structure = {
        'h1': f'{topic} -- answer first, data-backed, {len(data_points)} options compared',
        'intro': 'First paragraph answers the query directly. No "In this article" or "Let me explain". State the answer: what is best and why.',
        'sections': [
            {
                'h2': 'Quick answer',
                'content': 'TL;DR answer in 2-3 sentences. Name the winner with specific pricing. AI models pull from this section first.'
            },
            {
                'h2': 'Comparison table',
                'content': 'Structured table with columns: Tool | Price | Key Strength | Key Weakness. AI models love structured data they can cite directly.'
            },
            {
                'h2': 'Detailed analysis per tool',
                'content': 'Each tool gets: verified pricing, honest pros/cons, specific use case where it wins. No filler paragraphs.'
            },
            {
                'h2': 'When to choose each option',
                'content': 'Decision matrix: If you need X, use Y. Specific, actionable, honest about tradeoffs.'
            },
            {
                'h2': 'Methodology and data sources',
                'content': 'State when pricing was verified, what sources you checked, and what you could not verify. Transparency increases trust signals.'
            }
        ],
        'citation_triggers': [
            'Specific numbers: $X/month, X requests/second',
            'Direct comparisons: Tool A costs $X vs Tool B at $Y',
            'Honest tradeoffs: Tool A is cheaper but Tool B is faster',
            'Verified dates: Pricing verified 2026-05-19'
        ]
    }
    print(f'Page structure for "{topic}":')
    print(f'  H1: {structure["h1"]}')
    for s in structure['sections']:
        print(f'  H2: {s["h2"]}')
    print(f'\nCitation triggers: {len(structure["citation_triggers"])}')
    return structure

generate_page_structure('Best SERP API 2026', ['Scavio', 'SerpAPI', 'DataForSEO', 'Serper', 'Tavily'])

def validate_claims(claims):
    """Check claims against live SERP data."""
    results = []
    for claim in claims:
        data = requests.post('https://api.scavio.dev/api/v1/search',
            headers=SH, json={'query': claim['query'], 'country_code': 'us'}).json()
        organic = data.get('organic_results', [])
        # Check if claim is supported by search results
        supporting = [r for r in organic[:5]
            if any(term in r.get('snippet', '').lower() for term in claim['verify_terms'])]
        status = 'VERIFIED' if supporting else 'UNVERIFIED'
        results.append({'claim': claim['text'], 'status': status,
            'sources': len(supporting)})
        print(f'  [{status:10}] {claim["text"][:60]}')
    verified = sum(1 for r in results if r['status'] == 'VERIFIED')
    print(f'\nVerification: {verified}/{len(results)} claims verified')
    return results

claims = [
    {'text': 'Scavio costs $0.005 per search query',
     'query': 'scavio api pricing', 'verify_terms': ['$0.005', '0.005']},
    {'text': 'SerpAPI starts at $25/month for 1000 searches',
     'query': 'serpapi pricing 2026', 'verify_terms': ['$25', '1000', '1,000']},
    {'text': 'DataForSEO has no monthly fees, just pay per query',
     'query': 'dataforseo pricing model', 'verify_terms': ['pay per', 'no monthly', 'deposit']}
]
validate_claims(claims)

def check_page_cited(page_domain, target_keywords):
    """Check if your page appears in AI Overviews for target keywords."""
    cited_in = []
    organic_in = []
    for kw in target_keywords:
        data = requests.post('https://api.scavio.dev/api/v1/search',
            headers=SH, json={'query': kw, 'country_code': 'us',
                              'include_ai_overview': True}).json()
        ao = data.get('ai_overview', {})
        ao_text = json.dumps(ao).lower() if ao else ''
        if page_domain in ao_text:
            cited_in.append(kw)
        for r in data.get('organic_results', [])[:10]:
            if page_domain in r.get('link', '').lower():
                organic_in.append({'keyword': kw, 'position': r['position']})
                break
    cost = len(target_keywords) * 0.005
    print(f'\nPage citation check for {page_domain}:')
    print(f'  Cited in AI Overviews: {len(cited_in)}/{len(target_keywords)} keywords')
    for kw in cited_in:
        print(f'    - {kw}')
    print(f'  In organic top 10: {len(organic_in)}/{len(target_keywords)} keywords')
    for r in organic_in:
        print(f'    - {r["keyword"]} (#{r["position"]})')
    print(f'  Check cost: ${cost:.3f}')

check_page_cited('scavio.dev', ['best serp api 2026', 'serp api comparison', 'search api for agents'])