Google Tendencias Semanal Snapshot Workflow

import requests, os, json
from datetime import date

H = {'x-api-key': os.environ['SCAVIO_API_KEY']}

def trend_snapshot(keyword):
    r = requests.post('https://api.scavio.dev/api/v1/search', headers=H,
        json={'platform': 'google', 'query': f'{keyword} trend 2026',
              'ai_overview': True}, timeout=10).json()
    return {
        'keyword': keyword,
        'date': str(date.today()),
        'related_searches': [s.get('query', '') for s in r.get('related_searches', [])[:8]],
        'paa': [q.get('question', '') for q in r.get('people_also_ask', [])[:5]],
        'has_ai_overview': bool(r.get('ai_overview')),
        'ai_summary': ((r.get('ai_overview') or {}).get('text', ''))[:200],
        'top_result_titles': [o.get('title', '') for o in r.get('organic', [])[:3]],
    }

keywords = ['ai agents', 'mcp protocol', 'vibe coding', 'rag pipeline', 'agentic ai']
snapshots = []
for kw in keywords:
    snap = trend_snapshot(kw)
    snapshots.append(snap)
    print(f"\n{kw}:")
    print(f"  Related: {', '.join(snap['related_searches'][:4])}")
    if snap['paa']:
        print(f"  PAA: {snap['paa'][0]}")
    if snap['ai_summary']:
        print(f"  AIO: {snap['ai_summary'][:100]}")

# Save snapshot for weekly comparison
with open(f'trend_snapshot_{date.today()}.json', 'w') as f:
    json.dump(snapshots, f, indent=2)
print(f"\nSaved {len(snapshots)} keyword snapshots")

const H = {"x-api-key": process.env.SCAVIO_API_KEY, "Content-Type": "application/json"};
const fs = await import("fs");

async function trendSnapshot(keyword) {
  const r = await fetch("https://api.scavio.dev/api/v1/search", {
    method: "POST", headers: H,
    body: JSON.stringify({platform: "google", query: `${keyword} trend 2026`, ai_overview: true})
  }).then(r => r.json());
  return {
    keyword,
    date: new Date().toISOString().split("T")[0],
    relatedSearches: (r.related_searches || []).slice(0, 8).map(s => s.query || ""),
    paa: (r.people_also_ask || []).slice(0, 5).map(q => q.question || ""),
    hasAiOverview: Boolean(r.ai_overview),
    aiSummary: ((r.ai_overview || {}).text || "").slice(0, 200),
    topResultTitles: (r.organic || []).slice(0, 3).map(o => o.title || ""),
  };
}

(async () => {
  const keywords = ["ai agents", "mcp protocol", "vibe coding", "rag pipeline", "agentic ai"];
  const snapshots = [];
  for (const kw of keywords) {
    const snap = await trendSnapshot(kw);
    snapshots.push(snap);
    console.log(`\n${kw}:`);
    console.log(`  Related: ${snap.relatedSearches.slice(0, 4).join(", ")}`);
    if (snap.paa.length) console.log(`  PAA: ${snap.paa[0]}`);
    if (snap.aiSummary) console.log(`  AIO: ${snap.aiSummary.slice(0, 100)}`);
  }
  const today = new Date().toISOString().split("T")[0];
  fs.writeFileSync(`trend_snapshot_${today}.json`, JSON.stringify(snapshots, null, 2));
  console.log(`\nSaved ${snapshots.length} keyword snapshots`);
})();