[Base de datos objetivo] → [Agente: research + enriquecimiento] 
→ [Agente: generación de mensajes personalizados] 
→ [Canal: email/WhatsApp/LinkedIn] 
→ [Webhook: capture respuestas] 
→ [Agente: cualificación + feedback a CRM]

{
  #43a047">"tools": [
    {
      #43a047">"name": "lookup_company",
      #43a047">"description": "Busca datos de empresa en Apollo API o Clearbit",
      #43a047">"params": ["company_name", "country"]
    },
    {
      #43a047">"name": "find_decision_maker",
      #43a047">"description": "Encuentra decision-makers por rol (CEO, CFO, CMO) en la empresa",
      #43a047">"params": ["company_id", "role"]
    },
    {
      #43a047">"name": "get_company_news",
      #43a047">"description": "Obtiene últimas noticias de la empresa (funding, expansión, cambios)",
      #43a047">"params": ["company_name"]
    },
    {
      #43a047">"name": "validate_email",
      #43a047">"description": "Verifica si un email es válido y activo",
      #43a047">"params": ["email"]
    },
    {
      #43a047">"name": "generate_personalized_message",
      #43a047">"description": "Crea un mensaje de prospección personalizado",
      #43a047">"params": ["company_data", "decision_maker_data", "product_benefit"]
    },
    {
      #43a047">"name": "send_via_email",
      #43a047">"description": "Envía email via SendGrid",
      #43a047">"params": ["to_email", "subject", "html_body", "tracking_id"]
    },
    {
      #43a047">"name": "classify_response",
      #43a047">"description": "Clasifica respuesta en MQL/SQL/rechazado",
      #43a047">"params": ["response_text", "company_id"]
    }
  ]
}

CREATE TABLE prospect_companies (
  id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
  name VARCHAR(255),
  country VARCHAR(50),
  industry VARCHAR(100),
  size VARCHAR(50),
  created_at TIMESTAMP DEFAULT NOW(),
  status ENUM('pending', 'researching', 'contacted', 'responded', 'qualified', 'rejected')
);

INSERT INTO prospect_companies (name, country, industry, size) VALUES
  ('TechVentures Inc', 'Colombia', 'SaaS', 'Series B'),
  ('RetailMart LATAM', 'México', 'Retail', '500-1000'),
  ('FinServe Solutions', 'Perú', 'FinTech', '100-500');

async function prospectCompany(companyId) {
  // 1. Lookup: obtén datos básicos
  const company = await tools.lookup_company(company.name, company.country);
  
  // 2. Find decision-makers
  const decisionMakers = await tools.find_decision_maker(company.id, 'CEO');
  
  // 3. Get news para contexto
  const news = await tools.get_company_news(company.name);
  
  // 4. Validate emails
  for (let maker of decisionMakers) {
    maker.email_valid = await tools.validate_email(maker.email);
  }
  
  // 5. Generate personalized message
  const message = await tools.generate_personalized_message({
    company: company,
    decision_maker: decisionMakers[0],
    news: news,
    your_benefit: #43a047">"Reducimos tiempo de prospección en 80%"
  });
  
  return { company, decisionMakers, message };
}

async function sendOutreach(message, decisionMaker, companyId) {
  const tracking_id = #43a047">`prospect_${companyId}_${Date.now()}`;
  
  await tools.send_via_email({
    to_email: decisionMaker.email,
    subject: message.subject,
    html_body: message.body + #43a047">`<!-- tracking: ${tracking_id} -->`,
    tracking_id: tracking_id
  });
  
  // Registra en BD
  await db.query(
    #43a047">`INSERT INTO prospect_outreach (company_id, email, tracking_id, sent_at, status) 
     VALUES ($1, $2, $3, NOW(), 'sent')`,
    [companyId, decisionMaker.email, tracking_id]
  );
}

app.post('/webhook/email-reply', async (req, res) => {
  const { tracking_id, reply_text, responder_email } = req.body;
  
  // Cualifica automáticamente
  const classification = await tools.classify_response(reply_text, companyId);
  
  // Actualiza BD
  await db.query(
    #43a047">`UPDATE prospect_outreach SET status = $1, response = $2, classified_at = NOW() 
     WHERE tracking_id = $3`,
    [classification.type, reply_text, tracking_id]
  );
  
  // Si es MQL/SQL, notifica a ventas
  if (['MQL', 'SQL'].includes(classification.type)) {
    await notifySlack(#43a047">`Nuevo ${classification.type}: ${responder_email}`);
  }
  
  res.json({ ok: true });
});

SELECT 
  DATE_TRUNC('day', sent_at) AS date,
  COUNT(*) AS total_sent,
  COUNT(CASE WHEN status IN ('MQL', 'SQL') THEN 1 END) AS qualified,
  ROUND(100.0 * COUNT(CASE WHEN status IN ('MQL', 'SQL') THEN 1 END) / COUNT(*), 2) AS qualify_rate
FROM prospect_outreach
GROUP BY DATE_TRUNC('day', sent_at)
ORDER BY date DESC;

┌─────────────────────────────────────────────────────────────────┐
│ Agente IA (Claude/GPT-4) con acceso a herramientas específicas │
│ Objetivo: automatizar investigación + personalización + envío  │
├─────────────────────────────────────────────────────────────────┤
│                                                                 │
│  [Control Flow]                                                │
│  1. Itera sobre prospect_companies (status = 'pending')       │
│  2. Ejecuta lookup_company + find_decision_maker              │
│  3. Enriquece con news y validación de contactos             │
│  4. Genera mensaje personalizado via LLM                      │
│  5. Envía via SendGrid/SMS/WhatsApp con tracking_id          │
│  6. Registra outreach en BD                                   │
│  7. Espera webhook de respuesta                               │
│  8. Cualifica y notifica a ventas si MQL/SQL                 │
│                                                                 │
└─────────────────────────────────────────────────────────────────┘