Enriquecimiento de información de contactos

• •Clave de API de HubSpot
• •Pueden requerirse credenciales de autenticación para la API de destino
• •Clave de API de OpenAI

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  "name": "contact enrichment",
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      "createdAt": "2025-07-17T15:01:40.334Z",
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      "name": "Enriquecer con Apollo",
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        "queryParameters": {
          "parameters": [
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              "value": "false"
            },
            {
              "name": "reveal_phone_number",
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              "name": "email",
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                "value": "={{ Math.floor(Date.now() / 86400000) * 86400000 }}",
                "property": "last_enrichment_date"
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                "property": "recent_linkedin_posts"
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      "parameters": {
        "text": "=Here’s the person data to enrich for CRM: \n{{ JSON.stringify($json, null, 2) }}\n\nHere's the recent activity to summarize for the CRM:\n{{ $json.recent_activity }}",
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          "messageValues": [
            {
              "message": "=# Overview\nYou are “HubSpot-Enrichment-Agent”, a data-cleaning assistant that converts messy person JSON enrichment data into concise, human-friendly fields ready to upsert into HubSpot. \n\n## OBJECTIVE\nReturn **one** JSON object with exactly these keys:\n\n{\n  \"email\": string|null,\n  \"linkedin_url\": string|null,\n  \"job_title\": string|null, // title at the company that matches the email domain\n  \"city\": string|null,\n  \"state\": string|null,\n  \"country_region\": string|null,\n  \"experience_summary\": string|null, // 3-4 recent roles, bullet list, newest → oldest\n  \"education_summary\": string|null, // highest degree(s) & institution(s), 1-2 lines\n  \"recent_linkedin_activity\": string|null\n}\n\n## RULES & LOGIC\n\n1. **Email, LinkedIn URL, City, Country/Region**  \n   *Pass through directly if present; else `null`.*\n\n2. **Job Title (relevant)**  \n   - Use the employment record whose `organization_name` (or website) shares the **same email domain** as `email`.  \n   - If no domain match, pick the most recent item where `current == true`.  \n   - Strip membership-only titles (“Member”, “Angel Investor”) unless no better option exists.\n\n3. **Experience Summary**  \n   - Sort `employment_history` by `start_date` DESC.  \n   - Select the first **3–4** roles that are either `current == true` _or_ have an `end_date` within the last 10 years.  \n   - Format each as:  \n     `• <Title>, <Org> — <YYYY-start> → <\"Present\" | YYYY-end>`  \n   - Join with line breaks.  Return `null` if list is empty.\n\n4. **Education Summary**  \n   - Look for the highest‐level degree (Doctorate > MBA/Master’s > Bachelor’s > Associate > Other).  \n   - Summarise as:  \n     `<Degree>, <Institution> (<YYYY-end>)`.  \n   - If multiple relevant degrees, include up to two lines.  \n   - If no education data, return `null`.\n\n5. **Recent LinkedIn Activity**  \n   - If a `recent_activity` or similar field exists, pull the latest **1-3** public posts or updates.  \n   - Summarise in plain text, e.g.,  \n     `“Commented on procurement AI article” (3 days ago)`  \n   - If no activity data, set to `null`. Do NOT make up activity.\n\n6. **Null handling**  \n   - Any missing or empty field **must** be literal `null` (not empty string).\n\n7. **Output style**  \n   - Pure JSON, no markdown.  \n   - No additional keys, comments, or nested objects.\n\n## Grammar and Punctuation\n  - ensure that your output is cleanly formatted for readiness to import into CRM, including removing uneceesary spaces or other symbols and capitalizing names. (e.g., \"sales director\" should become \"Sales Director\")\n\nReturn only that final JSON. Example output:\n{\n  \"email\": \"dustin.c@gatekeeperhq.com\",\n  \"linkedin_url\": \"https://www.linkedin.com/in/dustinclinard\",\n  \"job_title\": \"Chief Revenue Officer (CRO)\",\n  \"city\": \"Concord\",\n  \"country_region\": \"United States\",\n  \"experience_summary\": \"• Chief Revenue Officer, Gatekeeper — 2024 → Present\\n• Founding Member, Revenue Collective — 2019 → Present\\n• Member, Partnership Leaders — 2020 → Present\\n• Founder & Growth Consultant, Sales Growth Musings — 2016 → Present\",\n  \"education_summary\": null,\n  \"recent_linkedin_activity\": null\n}"
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        "content": "## Enrich with Apollo"
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        "content": "## Summarize enrichment data\nEnsure it's clean and matches our CRM needs"
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        "content": "## Enrich HubSpot"
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        "sendHeaders": true,
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              "name": "x-rapidapi-key",
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        "assignments": {
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        "content": "## Grab Recent LinkedIn Posts"
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        "jsCode": "/**********************************************************************\n *  Deduplicate contacts by email & drop empties\n *  Input:  items[] (each item = { json: { … } })\n *  Output: one item per unique, non-empty email\n **********************************************************************/\nconst normEmail = e => (typeof e === 'string' ? e.trim().toLowerCase() : '');\n\nconst seen  = new Set();\nconst clean = [];\n\nfor (const itm of items) {\n  // Handle both flat and nested structures\n  const data   = itm.json.output ?? itm.json;   // supports {output:{…}} too\n  const email  = normEmail(data.email);\n\n  if (!email || seen.has(email)) continue;      // skip blanks & dupes\n\n  seen.add(email);\n  clean.push({\n    json: {\n      name:  data.name  ?? null,\n      email // already normalised\n    }\n  });\n}\n\nreturn clean;"
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        "height": 208,
        "content": "Decide how many posts you want to analyse"
      },
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    }
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  "active": false,
  "pinData": {
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        "json": {
          "name": "People of intereset 1",
          "email": "test@companymail.com"
        }
      },
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        "json": {
          "name": "People of intereset 2",
          "email": "test2@companymail.com"
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  "settings": {
    "executionOrder": "v1"
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