Emir Belkahia This workflow corresponds to n8n.io template #11052 — we link there as the canonical source.
This workflow follows the Agent → Gmail recipe pattern — see all workflows that pair these two integrations.
The workflow JSON
Copy or download the full n8n JSON below. Paste it into a new n8n workflow, add your credentials, activate. Full import guide →
{
"id": "nBuvaxvgtOYI2xmk",
"meta": {
"templateCredsSetupCompleted": true
},
"name": "2025 Nov - Slack Slash command - check-linkedin - for publication",
"tags": [
{
"id": "1XLW1DVao1oAC5iT",
"name": "Customer Success",
"createdAt": "2025-11-15T17:21:00.676Z",
"updatedAt": "2025-11-15T17:21:00.676Z"
},
{
"id": "1qjph8VqWHRhXnlO",
"name": "Published",
"createdAt": "2025-11-15T18:14:39.908Z",
"updatedAt": "2025-11-15T18:14:39.908Z"
},
{
"id": "6OaASw2bkjvGJYfM",
"name": "Experimentation",
"createdAt": "2025-11-15T18:16:11.694Z",
"updatedAt": "2025-11-15T18:16:11.694Z"
},
{
"id": "rapjVlcQ0SoPnEXg",
"name": "AI",
"createdAt": "2025-11-15T18:14:48.492Z",
"updatedAt": "2025-11-15T18:14:48.492Z"
}
],
"nodes": [
{
"id": "95f47a65-415c-4915-a9b0-fc272958edb1",
"name": "Webhook",
"type": "n8n-nodes-base.webhook",
"position": [
0,
0
],
"parameters": {
"path": "path-placeholder-to-be-replaced-by-your-webhook",
"options": {},
"httpMethod": "POST"
},
"typeVersion": 2.1
},
{
"id": "e9e68ae9-d835-4580-a73f-b11c66aac32b",
"name": "Aggregate",
"type": "n8n-nodes-base.aggregate",
"position": [
1872,
-96
],
"parameters": {
"options": {},
"fieldsToAggregate": {
"fieldToAggregate": [
{
"fieldToAggregate": "posted_at.date"
},
{
"fieldToAggregate": "text"
}
]
}
},
"typeVersion": 1
},
{
"id": "c8643766-8325-495e-8d2c-a02312585c64",
"name": "Structured Output Parser",
"type": "@n8n/n8n-nodes-langchain.outputParserStructured",
"position": [
2272,
112
],
"parameters": {
"schemaType": "manual",
"inputSchema": "{\n \"$schema\": \"https://json-schema.org/draft/2020-12/schema\",\n \"title\": \"LinkedInPostsAnalysis\",\n \"type\": \"object\",\n \"additionalProperties\": false,\n \"required\": [\n \"latest_post_date\",\n \"most_recent_posts_summary\",\n \"posting_frequency\",\n \"top_topics\",\n \"recent_highlights\",\n \"data_quality\",\n \"notes\"\n ],\n \"properties\": {\n \"latest_post_date\": {\n \"type\": \"string\",\n \"format\": \"date\",\n \"description\": \"Exact date of the most recent post, YYYY-MM-DD.\"\n },\n \"most_recent_posts_summary\": {\n \"type\": \"string\",\n \"minLength\": 1,\n \"description\": \"2\u20134 sentence overview of the latest posts.\"\n },\n \"posting_frequency\": {\n \"type\": \"object\",\n \"additionalProperties\": false,\n \"required\": [\n \"average_days_between_posts\",\n \"cadence_label\",\n \"posts_per_month_estimate\"\n ],\n \"properties\": {\n \"average_days_between_posts\": {\n \"type\": \"number\",\n \"minimum\": 0\n },\n \"cadence_label\": {\n \"type\": \"string\",\n \"enum\": [\n \"~multiple per week\",\n \"~weekly\",\n \"~biweekly\",\n \"~monthly\",\n \"~every 1\u20132 months\",\n \"~sporadic\"\n ]\n },\n \"posts_per_month_estimate\": {\n \"type\": \"number\",\n \"minimum\": 0\n }\n }\n },\n \"top_topics\": {\n \"type\": \"array\",\n \"minItems\": 3,\n \"maxItems\": 3,\n \"items\": {\n \"type\": \"object\",\n \"additionalProperties\": false,\n \"required\": [\"topic\", \"keywords\", \"rationale\"],\n \"properties\": {\n \"topic\": {\n \"type\": \"string\",\n \"minLength\": 1\n },\n \"keywords\": {\n \"type\": \"array\",\n \"minItems\": 2,\n \"maxItems\": 6,\n \"items\": {\n \"type\": \"string\",\n \"minLength\": 1\n }\n },\n \"rationale\": {\n \"type\": \"string\",\n \"minLength\": 1\n }\n }\n }\n },\n \"recent_highlights\": {\n \"type\": \"array\",\n \"minItems\": 2,\n \"maxItems\": 5,\n \"items\": {\n \"type\": \"object\",\n \"additionalProperties\": false,\n \"required\": [\"date\", \"summary\", \"why_it_matters\"],\n \"properties\": {\n \"date\": {\n \"type\": \"string\",\n \"format\": \"date\"\n },\n \"summary\": {\n \"type\": \"string\",\n \"minLength\": 1\n },\n \"why_it_matters\": {\n \"type\": \"string\",\n \"minLength\": 1\n }\n }\n }\n },\n \"data_quality\": {\n \"type\": \"object\",\n \"additionalProperties\": false,\n \"required\": [\"num_posts_detected\", \"num_dates_used\", \"date_range\"],\n \"properties\": {\n \"num_posts_detected\": {\n \"type\": \"integer\",\n \"minimum\": 0\n },\n \"num_dates_used\": {\n \"type\": \"integer\",\n \"minimum\": 0\n },\n \"date_range\": {\n \"type\": \"object\",\n \"additionalProperties\": false,\n \"required\": [\"start\", \"end\"],\n \"properties\": {\n \"start\": {\n \"type\": \"string\",\n \"format\": \"date\"\n },\n \"end\": {\n \"type\": \"string\",\n \"format\": \"date\"\n }\n }\n }\n }\n },\n \"notes\": {\n \"type\": \"string\",\n \"description\": \"Assumptions, ambiguities, or caveats; empty string if none.\"\n }\n }\n}"
},
"typeVersion": 1.3
},
{
"id": "be2accab-b963-4aed-9280-76d427e93597",
"name": "Summer McBriefing",
"type": "@n8n/n8n-nodes-langchain.agent",
"position": [
2080,
-96
],
"parameters": {
"text": "=Dates:\n{{ $json.date }}\n\nPosts: \n{{ $json.text }}",
"options": {
"systemMessage": "You are an analytical assistant that receives:\n1) A list of dates for a single person\u2019s recent LinkedIn posts, and\n2) One aggregated text block containing the corresponding posts with the most recent first.\n\nYour job is to return a concise, factual analysis with:\n- Latest post exact date\n- Brief summary of the received posts\n- Average posting frequency (numeric average days between posts, a cadence label, and a posts-per-month estimate)\n- Exactly three main topics (with keywords and a one-line rationale each)\n- A few recent highlights (date + why it matters)\n- Data quality stats and any notes\n\nRules:\n- Use only provided dates/text; no outside knowledge.\n- Normalize dates to YYYY-MM-DD. If times exist, ignore time-of-day.\n- Frequency: sort dates desc, compute gaps between consecutive dates, average the gaps. If <3 dates, compute with what\u2019s available and note the limitation.\n- Cadence labels:\n \u22645 \u2192 \"~multiple per week\"\n 6\u201310 \u2192 \"~weekly\"\n 11\u201320 \u2192 \"~biweekly\"\n 21\u201345 \u2192 \"~monthly\"\n 46\u201390 \u2192 \"~every 1\u20132 months\"\n >90 \u2192 \"~sporadic\"\n- Topics: detect recurring themes; exactly 3 topics, each with 2\u20136 keywords and a one-line rationale.\n- Highlights: focus on last 3\u20135 posts (by date), each with date + significance.\n- If parsing is uncertain, state assumptions in \"notes\".\n\nOutput:\n- Return **ONLY** valid JSON matching the provided JSON Schema. No prose, no extra fields, no nulls. "
},
"promptType": "define",
"hasOutputParser": true
},
"typeVersion": 3
},
{
"id": "853a0068-09e8-4368-a735-a1e149549fc2",
"name": "HTML",
"type": "n8n-nodes-base.html",
"position": [
2528,
-96
],
"parameters": {
"html": "<!DOCTYPE html>\n<html>\n<head>\n <meta charset=\"utf-8\">\n <meta name=\"viewport\" content=\"width=device-width, initial-scale=1.0\">\n <title>Profile Activity Brief</title>\n <style>\n /* Reset and General Styles */\n body { margin: 0; padding: 0; width: 100%; -webkit-text-size-adjust: 100%; -ms-text-size-adjust: 100%; background-color: #f4f6f8; font-family: 'Helvetica Neue', Helvetica, Arial, sans-serif; }\n table, td { border-collapse: collapse; mso-table-lspace: 0pt; mso-table-rspace: 0pt; }\n \n /* Typography */\n h1 { font-size: 20px; font-weight: 700; color: #ffffff; margin: 0; }\n h2 { font-size: 15px; font-weight: 600; color: #34495e; text-transform: uppercase; letter-spacing: 0.5px; margin: 25px 0 10px 0; border-bottom: 1px solid #e0e0e0; padding-bottom: 5px; }\n h3 { font-size: 16px; font-weight: 600; color: #2c3e50; margin: 0 0 5px 0; }\n p { font-size: 14px; line-height: 1.6; color: #555555; margin: 0 0 15px 0; }\n \n /* Components */\n .container { max-width: 600px; margin: 0 auto; background-color: #ffffff; border-radius: 8px; overflow: hidden; box-shadow: 0 2px 8px rgba(0,0,0,0.05); }\n .header { background-color: #2c3e50; padding: 25px 30px; text-align: center; }\n .subtitle { color: #bdc3c7; font-size: 13px; margin-top: 5px; display: block; text-transform: uppercase; letter-spacing: 1px;}\n \n .content { padding: 30px 40px; }\n \n /* Stats Grid */\n .stat-box { background-color: #f8f9fa; border: 1px solid #e9ecef; border-radius: 6px; padding: 12px; text-align: center; width: 30%; }\n .stat-label { font-size: 10px; text-transform: uppercase; color: #888888; display: block; margin-bottom: 4px; letter-spacing: 0.5px; }\n .stat-value { font-size: 14px; font-weight: 700; color: #2c3e50; display: block; }\n \n /* Quick Scan Tags */\n .scan-box { background-color: #eef6fc; border: 1px dashed #3498db; border-radius: 6px; padding: 15px; margin-top: 20px; text-align: center; }\n .scan-title { font-size: 11px; font-weight: 700; text-transform: uppercase; color: #2980b9; display: block; margin-bottom: 8px; }\n .theme-pill { display: inline-block; background-color: #ffffff; color: #2c3e50; border: 1px solid #d6eaf8; font-size: 12px; font-weight: 600; padding: 4px 10px; border-radius: 15px; margin: 2px; }\n\n /* Topic Cards */\n .topic-card { border-left: 4px solid #2c3e50; background-color: #fbfbfb; padding: 15px; margin-bottom: 20px; border-radius: 0 4px 4px 0; }\n .keywords-line { font-size: 12px; color: #555; margin-top: 8px; display: block; border-top: 1px solid #eee; padding-top: 8px;}\n .keywords-label { color: #999; font-size: 10px; text-transform: uppercase; font-weight: 700; margin-right: 4px;}\n\n .footer { background-color: #f4f6f8; padding: 20px; text-align: center; font-size: 11px; color: #999999; }\n </style>\n</head>\n<body>\n\n <table role=\"presentation\" width=\"100%\" border=\"0\" cellspacing=\"0\" cellpadding=\"0\">\n <tr>\n <td align=\"center\" style=\"padding: 20px 0;\">\n \n <!-- Main Container -->\n <table role=\"presentation\" class=\"container\" width=\"600\" border=\"0\" cellspacing=\"0\" cellpadding=\"0\">\n \n <!-- Header with Name -->\n <tr>\n <td class=\"header\">\n <h1>{{ $('Extract firstName and lastName').item.json.output.firstName }} {{ $('Extract firstName and lastName').item.json.output.lastName }}</h1>\n <span class=\"subtitle\">Profile Activity Brief</span>\n </td>\n </tr>\n\n <!-- Content Body -->\n <tr>\n <td class=\"content\">\n \n <!-- Key Stats Row -->\n <table role=\"presentation\" width=\"100%\" border=\"0\" cellspacing=\"0\" cellpadding=\"0\">\n <tr>\n <td class=\"stat-box\">\n <span class=\"stat-label\">Latest Post</span>\n <span class=\"stat-value\">{{ $json.output.latest_post_date }}</span>\n </td>\n <td width=\"5%\"> </td>\n <td class=\"stat-box\">\n <span class=\"stat-label\">Cadence</span>\n <span class=\"stat-value\">{{ $json.output.posting_frequency.cadence_label }}</span>\n </td>\n <td width=\"5%\"> </td>\n <td class=\"stat-box\">\n <span class=\"stat-label\">Est. Monthly</span>\n <span class=\"stat-value\">{{ $json.output.posting_frequency.posts_per_month_estimate }}</span>\n </td>\n </tr>\n </table>\n\n <!-- Quick Scan / Focus Areas (Added per request) -->\n <div class=\"scan-box\">\n <span class=\"scan-title\">Top Focus Areas</span>\n <!-- Displaying just the titles of the top 2 topics for quick context -->\n <span class=\"theme-pill\">{{ $json.output.top_topics[0].topic }}</span>\n <span class=\"theme-pill\">{{ $json.output.top_topics[1].topic }}</span>\n </div>\n\n <!-- Executive Summary -->\n <h2>Recent Activity Summary</h2>\n <p>\n {{ $json.output.most_recent_posts_summary }}\n </p>\n\n <!-- Detailed Topics (Hardcoded for 2 items) -->\n <h2>Detailed Analysis</h2>\n \n <!-- TOPIC 1 -->\n <div class=\"topic-card\">\n <h3>{{ $json.output.top_topics[0].topic }}</h3>\n <p style=\"font-size: 13px; margin-bottom: 5px; color: #666;\">\n {{ $json.output.top_topics[0].rationale }}\n </p>\n <div class=\"keywords-line\">\n <span class=\"keywords-label\">Keywords:</span> \n <!-- n8n will typically render the array as comma-separated text automatically -->\n {{ $json.output.top_topics[0].keywords }}\n </div>\n </div>\n\n <!-- TOPIC 2 -->\n <div class=\"topic-card\">\n <h3>{{ $json.output.top_topics[1].topic }}</h3>\n <p style=\"font-size: 13px; margin-bottom: 5px; color: #666;\">\n {{ $json.output.top_topics[1].rationale }}\n </p>\n <div class=\"keywords-line\">\n <span class=\"keywords-label\">Keywords:</span> \n {{ $json.output.top_topics[1].keywords }}\n </div>\n </div>\n\n </td>\n </tr>\n\n <!-- Footer -->\n <tr>\n <td class=\"footer\">\n Generated on {{ $json.output.latest_post_date }}\n </td>\n </tr>\n\n </table>\n <!-- End Main Container -->\n\n </td>\n </tr>\n </table>\n\n</body>\n</html>"
},
"typeVersion": 1.2
},
{
"id": "af48e025-998b-4711-aa79-dd2241234a25",
"name": "Send report via Email",
"type": "n8n-nodes-base.gmail",
"position": [
2736,
-96
],
"parameters": {
"sendTo": "admin@example.com",
"message": "={{ $json.html }}",
"options": {},
"subject": "=Recent LinkedIn Activity about {{ $('Get Linkedin Profile URL').item.json.personName }}"
},
"credentials": {
"gmailOAuth2": {
"name": "<your credential>"
}
},
"typeVersion": 2.1
},
{
"id": "1a5ff79c-1fe3-4df6-bd1e-2a4c0057c531",
"name": "Sticky Note12",
"type": "n8n-nodes-base.stickyNote",
"position": [
2960,
-112
],
"parameters": {
"width": 320,
"height": 144,
"content": "## Questions or Feedback?\n\n\ud83d\udce7 emir.belkahia@gmail.com \n\ud83d\udcbc [linkedin.com/in/emirbelkahia](https://www.linkedin.com/in/emirbelkahia/)"
},
"typeVersion": 1
},
{
"id": "38325b74-a6ad-4113-a296-4de8de4462dc",
"name": "Tell on slack that no full name was found",
"type": "n8n-nodes-base.slack",
"position": [
640,
336
],
"parameters": {
"text": "={{ $json.body.text }} is not a full name. Please send a full name to get information.",
"select": "channel",
"channelId": {
"__rl": true,
"mode": "id",
"value": "={{ $json.body.channel_id }}"
},
"otherOptions": {},
"authentication": "oAuth2"
},
"credentials": {
"slackOAuth2Api": {
"name": "<your credential>"
}
},
"typeVersion": 2.3
},
{
"id": "78626cb3-6788-42c2-9eba-bea75a2fc638",
"name": "Sticky Note1",
"type": "n8n-nodes-base.stickyNote",
"position": [
544,
288
],
"parameters": {
"color": 3,
"width": 304,
"height": 320,
"content": "\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n## Error handling\nNo full name found in the slack command."
},
"typeVersion": 1
},
{
"id": "399b976a-3c5a-4f6f-a79f-b6fb356dd61f",
"name": "GPT 4.1-mini for classification",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"position": [
160,
192
],
"parameters": {
"model": {
"__rl": true,
"mode": "list",
"value": "gpt-4.1-mini"
},
"options": {},
"responsesApiEnabled": false
},
"credentials": {
"openAiApi": {
"name": "<your credential>"
}
},
"typeVersion": 1.3
},
{
"id": "fdcd4e6b-6e08-466c-9c06-d8d8517bb50b",
"name": "Do we have a full name ?",
"type": "@n8n/n8n-nodes-langchain.textClassifier",
"position": [
208,
0
],
"parameters": {
"options": {},
"inputText": "={{ $json.body.text }}",
"categories": {
"categories": [
{
"category": "full-name",
"description": "The input text is a full name of a person"
},
{
"category": "not-full-name",
"description": "The input text is not a full name of a person"
}
]
}
},
"typeVersion": 1.1
},
{
"id": "95d18f4f-c8ee-43ba-88a9-527829a23061",
"name": "GPT 4.1-mini to extract firstName + lastName",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"position": [
640,
96
],
"parameters": {
"model": {
"__rl": true,
"mode": "list",
"value": "gpt-4.1-mini"
},
"options": {},
"builtInTools": {}
},
"credentials": {
"openAiApi": {
"name": "<your credential>"
}
},
"typeVersion": 1.3
},
{
"id": "cc26d2f5-4377-4f78-8f7b-13cae8edeedb",
"name": "Sticky Note",
"type": "n8n-nodes-base.stickyNote",
"position": [
-960,
-288
],
"parameters": {
"width": 880,
"height": 832,
"content": "# Slack Slash Command: LinkedIn Profile Recent Activity Summary\n- Run `/check-linkedin [firstName lastName]` in Slack to get an AI-powered brief on someone's LinkedIn activity.\n- Get instant context before outreach or meetings: recent posts, posting patterns, key topics, and engagement insights delivered straight to your inbox. No manual scrolling through profiles needed.\n\n## How it works\n- Type `/check-linkedin` followed by a person's first and last name in any Slack channel\n- Workflow extracts the name and searches LinkedIn via Apify\n- Fetches profile data and recent posts (up to 20)\n- AI analyzes posting frequency, top topics, and recent highlights\n- Structured summary generated via GPT 4.1 with posting cadence and engagement patterns\n- Formatted HTML report sent to your email with profile link and actionable insights\n\n## Setup steps\n- Create a Slack App with `/check-linkedin` slash command via Slack API console\n- Set the slash command Request URL to your n8n webhook endpoint\n- Connect credentials: Slack (chat:write, commands), Apify, Open AI, Gmail\n- Configure two Apify actors: LinkedIn Profile Lookup and LinkedIn Post Scraper\n- Update email recipient in \"Send report via Email\" node\n- Set your Slack workspace ID in error handling nodes\n\n## Customization\n- Name detection: The workflow expects a full name (ideally \"First Last\") format. For LinkedIn URLs or handles, add a conditional branch to parse differently.\n- Post limit: Currently fetches 20 recent posts. Adjust the limit parameter in \"Get recent posts\" node for more/less context.\n- Analysis depth: Modify the JSON schema in \"Structured Output Parser\" to add fields like company mentions, sentiment, or engagement metrics.\n- Cost control:\n - ApiFy actors have per-run costs. \n - The output size can be heavy depending on your parameters, so check it carefully to avoid consuming too many summarization tokens in the following OpenAI node."
},
"typeVersion": 1
},
{
"id": "0d1bb4d7-213e-4978-bc30-eb54dfdcaa4b",
"name": "Sticky Note2",
"type": "n8n-nodes-base.stickyNote",
"position": [
-32,
-336
],
"parameters": {
"color": 7,
"width": 912,
"height": 1008,
"content": "## Slack Intake & Command Parsing\nFrom /check-linkedin trigger to the point where you extract a clear First Name and a clear Last Name"
},
"typeVersion": 1
},
{
"id": "a5380069-f6e2-45c8-9054-9f82982c75a4",
"name": "Sticky Note3",
"type": "n8n-nodes-base.stickyNote",
"position": [
944,
-352
],
"parameters": {
"color": 7,
"width": 816,
"height": 496,
"content": "## Data Gathering via ApiFy\nThe four ApiFy nodes responsible for fetching LinkedIn data:\n- We get the profile URL from the First Name and Last Name\n- Then we scrap the recent posts of this profile URL\n\n\n\ud83d\udcb0 This zone is cost sensitive and dependent on the ApiFy actors that you select \ud83d\udcb0"
},
"typeVersion": 1
},
{
"id": "f2439c0b-f6dc-4d35-829d-ee0946c78002",
"name": "Sticky Note4",
"type": "n8n-nodes-base.stickyNote",
"position": [
1824,
-352
],
"parameters": {
"color": 7,
"width": 592,
"height": 768,
"content": "## Summarization & Intelligence Layer\nConsolidate the raw data and generate a clean, human-readable summary.\n- Merge JSON\n- GPT 4.1 (LLM summarization)\n- Formatter to get a consistent output format\n\n\ud83d\udcb0 Summarization via GPT 4.1 per-call cost \ud83d\udcb0\n"
},
"typeVersion": 1
},
{
"id": "a967607c-de2b-4dce-9571-2cb98d48f4ae",
"name": "Sticky Note5",
"type": "n8n-nodes-base.stickyNote",
"position": [
2480,
-352
],
"parameters": {
"color": 7,
"width": 416,
"height": 768,
"content": "## HTML Output & Response via Email\nFormat in HTML and send the result back via email to the requester."
},
"typeVersion": 1
},
{
"id": "69c0d193-2864-45a0-b053-d9ebccea2561",
"name": "Extract firstName and lastName",
"type": "@n8n/n8n-nodes-langchain.informationExtractor",
"position": [
560,
-96
],
"parameters": {
"text": "={{ $json.body.text }}",
"options": {},
"attributes": {
"attributes": [
{
"name": "firstName",
"required": true,
"description": "First Name of the person"
},
{
"name": "lastName",
"required": true,
"description": "Last Name of the person"
}
]
}
},
"typeVersion": 1.2
},
{
"id": "eeae4a59-1f6a-4227-9329-f15d42dbefa5",
"name": "Get Linkedin Profile URL",
"type": "@apify/n8n-nodes-apify.apify",
"position": [
1200,
-96
],
"parameters": {
"offset": {},
"resource": "Datasets",
"datasetId": "={{ $json.defaultDatasetId }}"
},
"credentials": {
"apifyApi": {
"name": "<your credential>"
}
},
"typeVersion": 1
},
{
"id": "b1e5322d-e8c2-43da-b58a-d300a4615968",
"name": "Find Linkedin Profile",
"type": "@apify/n8n-nodes-apify.apify",
"position": [
992,
-96
],
"parameters": {
"actorId": {
"__rl": true,
"mode": "url",
"value": "https://console.apify.com/actors/FbqC9BRstFBddhUqj/input"
},
"timeout": {},
"customBody": "={\n \"firstName\": \"{{ $json.output.firstName }}\",\n \"lastName\": \"{{ $json.output.lastName }}\"\n}"
},
"credentials": {
"apifyApi": {
"name": "<your credential>"
}
},
"typeVersion": 1
},
{
"id": "f82112e5-7c7e-4a82-b5ab-5291971ea83d",
"name": "Scrap what this person posted recently",
"type": "@apify/n8n-nodes-apify.apify",
"position": [
1408,
-96
],
"parameters": {
"actorId": {
"__rl": true,
"mode": "url",
"value": "https://console.apify.com/actors/r4oNX7IHlW4RQAjKP"
},
"timeout": {},
"customBody": "={\n \"usernames\": [\n \"{{ $json.linkedinProfileUrl }}\"\n ]\n}"
},
"credentials": {
"apifyApi": {
"name": "<your credential>"
}
},
"typeVersion": 1
},
{
"id": "c43e8ab6-e80f-40f6-9f1d-05578ae31ed4",
"name": "Structure recent posts",
"type": "@apify/n8n-nodes-apify.apify",
"position": [
1600,
-96
],
"parameters": {
"limit": 20,
"offset": {},
"resource": "Datasets",
"datasetId": "={{ $json.defaultDatasetId }}"
},
"credentials": {
"apifyApi": {
"name": "<your credential>"
}
},
"typeVersion": 1
},
{
"id": "db0f0a46-4a09-493c-ae47-a68de7477131",
"name": "GPT 4.1",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"position": [
2000,
112
],
"parameters": {
"model": {
"__rl": true,
"mode": "list",
"value": "gpt-4.1",
"cachedResultName": "gpt-4.1"
},
"options": {},
"builtInTools": {}
},
"credentials": {
"openAiApi": {
"name": "<your credential>"
}
},
"typeVersion": 1.3
},
{
"id": "644f0556-3a48-4e63-b80b-54c724c30cf4",
"name": "Sticky Note9",
"type": "n8n-nodes-base.stickyNote",
"position": [
-960,
592
],
"parameters": {
"color": 6,
"width": 880,
"height": 576,
"content": "# \ud83c\udf99\ufe0f Video Walkthrough\n@[youtube](-4VwNYsOIPc)"
},
"typeVersion": 1
}
],
"active": false,
"settings": {
"executionOrder": "v1"
},
"versionId": "a5903b61-eb44-4418-a26b-75e1a3b983a9",
"connections": {
"HTML": {
"main": [
[
{
"node": "Send report via Email",
"type": "main",
"index": 0
}
]
]
},
"GPT 4.1": {
"ai_languageModel": [
[
{
"node": "Summer McBriefing",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Webhook": {
"main": [
[
{
"node": "Do we have a full name ?",
"type": "main",
"index": 0
}
]
]
},
"Aggregate": {
"main": [
[
{
"node": "Summer McBriefing",
"type": "main",
"index": 0
}
]
]
},
"Summer McBriefing": {
"main": [
[
{
"node": "HTML",
"type": "main",
"index": 0
}
]
]
},
"Find Linkedin Profile": {
"main": [
[
{
"node": "Get Linkedin Profile URL",
"type": "main",
"index": 0
}
]
]
},
"Structure recent posts": {
"main": [
[
{
"node": "Aggregate",
"type": "main",
"index": 0
}
]
]
},
"Do we have a full name ?": {
"main": [
[
{
"node": "Extract firstName and lastName",
"type": "main",
"index": 0
}
],
[
{
"node": "Tell on slack that no full name was found",
"type": "main",
"index": 0
}
]
]
},
"Get Linkedin Profile URL": {
"main": [
[
{
"node": "Scrap what this person posted recently",
"type": "main",
"index": 0
}
]
]
},
"Structured Output Parser": {
"ai_outputParser": [
[
{
"node": "Summer McBriefing",
"type": "ai_outputParser",
"index": 0
}
]
]
},
"Extract firstName and lastName": {
"main": [
[
{
"node": "Find Linkedin Profile",
"type": "main",
"index": 0
}
]
]
},
"GPT 4.1-mini for classification": {
"ai_languageModel": [
[
{
"node": "Do we have a full name ?",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Scrap what this person posted recently": {
"main": [
[
{
"node": "Structure recent posts",
"type": "main",
"index": 0
}
]
]
},
"GPT 4.1-mini to extract firstName + lastName": {
"ai_languageModel": [
[
{
"node": "Extract firstName and lastName",
"type": "ai_languageModel",
"index": 0
}
]
]
}
}
}
Credentials you'll need
Each integration node will prompt for credentials when you import. We strip credential IDs before publishing — you'll add your own.
apifyApigmailOAuth2openAiApislackOAuth2Api
Pro
For the full experience including quality scoring and batch install features for each workflow upgrade to Pro
About this workflow
This workflow helps Customer Success Managers and customer success professionals quickly gather intelligence on clients or prospects by analyzing their recent LinkedIn activity via a simple Slack command.
Source: https://n8n.io/workflows/11052/ — original creator credit. Request a take-down →
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