{ "name": "AI Talent Intelligence Agent", "nodes": [ { "parameters": {}, "id": "8d5a9f82-c0e6-45b2-97a4-e874a28c839a", "name": "โ–ถ๏ธ START - Run Complete Analysis", "type": "n8n-nodes-base.manualTrigger", "typeVersion": 1, "position": [ -2768, 464 ] }, { "parameters": { "url": "http://export.arxiv.org/api/query", "sendQuery": true, "queryParameters": { "parameters": [ { "name": "search_query", "value": "cat:cs.AI OR cat:cs.LG OR cat:cs.CL" }, { "name": "sortBy", "value": "submittedDate" }, { "name": "sortOrder", "value": "descending" }, { "name": "max_results", "value": "50" } ] }, "options": {} }, "id": "db5ccbae-e7e1-483e-a7ed-5a68e2a1c86a", "name": "๐Ÿ“š SOURCE 1: ArXiv Papers", "type": "n8n-nodes-base.httpRequest", "typeVersion": 4.1, "position": [ -2528, 256 ] }, { "parameters": { "method": "POST", "url": "https://google.serper.dev/news", "authentication": "genericCredentialType", "genericAuthType": "httpHeaderAuth", "sendHeaders": true, "headerParameters": { "parameters": [ { "name": "X-API-KEY", "value": "REPLACE_WITH_X_API_KEY" }, { "name": "Content-Type", "value": "application/json" } ] }, "sendBody": true, "bodyParameters": { "parameters": [ { "name": "q", "value": "\"AI researcher\" (\"hired\" OR \"joined\" OR \"appointed\") (OpenAI OR Anthropic OR Google OR Meta)" }, { "name": "num", "value": "20" } ] }, "options": {} }, "id": "10a2eb7e-58cb-4d6d-9783-03e3e5ba6ed1", "name": "๐Ÿ“ฐ SOURCE 2: News Search", "type": "n8n-nodes-base.httpRequest", "typeVersion": 4.1, "position": [ -2528, 464 ] }, { "parameters": { "jsCode": "// Parse ArXiv XML and extract structured data\nconst xmlData = $input.first().json;\n\n// For production, this would use actual XML parsing\n// Demo with realistic data structure\nconst papers = [\n {\n title: 'Constitutional AI: Harmlessness from AI Feedback',\n authors: [{name: 'Yuntao Bai', affiliation: 'Anthropic'}, {name: 'Saurav Kadavath', affiliation: 'Anthropic'}],\n date: '2023-12-15',\n citations: 450,\n category: 'AI Safety',\n abstract: 'We propose Constitutional AI...'\n },\n {\n title: 'GPT-4 Technical Report',\n authors: [{name: 'OpenAI Team', affiliation: 'OpenAI'}],\n date: '2023-03-15',\n citations: 5000,\n category: 'Large Language Models',\n abstract: 'We report the development of GPT-4...'\n },\n {\n title: 'LLaMA: Open Foundation Models',\n authors: [{name: 'Hugo Touvron', affiliation: 'Meta AI'}, {name: 'Thibaut Lavril', affiliation: 'Meta AI'}],\n date: '2023-02-27',\n citations: 2800,\n category: 'Large Language Models',\n abstract: 'We introduce LLaMA...'\n },\n {\n title: 'Gemini: Multimodal AI System',\n authors: [{name: 'Gemini Team', affiliation: 'Google DeepMind'}],\n date: '2023-12-06',\n citations: 1200,\n category: 'Multimodal AI',\n abstract: 'This report introduces Gemini...'\n },\n {\n title: 'Claude 2: Technical Improvements',\n authors: [{name: 'Anthropic Research Team', affiliation: 'Anthropic'}],\n date: '2023-07-11',\n citations: 890,\n category: 'Large Language Models',\n abstract: 'We present Claude 2...'\n }\n];\n\nreturn papers.map(p => ({\n json: {\n ...p,\n source: 'arxiv',\n discovered_at: new Date().toISOString()\n }\n}));" }, "id": "74dcaf61-82c5-44e7-ac32-43b0b641a8ca", "name": "๐Ÿ”„ Parse ArXiv Data", "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ -2272, 256 ] }, { "parameters": { "jsCode": "// Parse news data\nconst newsData = $input.first().json;\nconst articles = newsData.news || [];\n\nconst movements = articles.map(article => ({\n title: article.title,\n snippet: article.snippet,\n url: article.link,\n date: article.date,\n source: 'news',\n discovered_at: new Date().toISOString()\n}));\n\nreturn movements.map(m => ({ json: m }));" }, "id": "98c5462f-cd2c-413b-aaa3-ce684ede37ed", "name": "๐Ÿ”„ Parse News Data", "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ -2288, 448 ] }, { "parameters": { "conditions": { "options": { "caseSensitive": true, "leftValue": "", "typeValidation": "strict", "version": 1 }, "conditions": [ { "leftValue": "={{ JSON.parse($json.text).significance }}", "rightValue": 5, "operator": { "type": "number", "operation": "gt" }, "id": "5bbd2018-6b88-4869-9f2f-69584b7f40bf" } ], "combinator": "and" }, "options": {} }, "id": "071874d8-20a6-4f36-a9a5-f7e6c4d07c89", "name": "๐Ÿ” FILTER: High Significance Only", "type": "n8n-nodes-base.if", "typeVersion": 2, "position": [ -1392, 320 ] }, { "parameters": { "aggregate": "aggregateAllItemData", "options": {} }, "id": "12396e8f-e016-4e70-8bc3-d11cee9f2b51", "name": "๐Ÿ“Š AGGREGATE Statistics", "type": "n8n-nodes-base.aggregate", "typeVersion": 1, "position": [ -1088, 304 ] }, { "parameters": { "jsCode": "// Generate comprehensive intelligence report\nconst data = $input.first().json;\n\n// Extract unique companies and researchers\nconst companiesSet = new Set();\nconst researchersSet = new Set();\nconst technologiesSet = new Set();\n\nif (Array.isArray(data.all_companies)) {\n data.all_companies.flat().forEach(c => companiesSet.add(c));\n}\nif (Array.isArray(data.all_researchers)) {\n data.all_researchers.flat().forEach(r => researchersSet.add(r));\n}\n\nconst report = {\n generated_at: new Date().toISOString(),\n summary: {\n total_signals: data.all_companies?.length || 0,\n unique_companies: companiesSet.size,\n unique_researchers: researchersSet.size,\n avg_significance: Math.round((data.avg_significance || 0) * 10) / 10\n },\n companies: {\n 'OpenAI': {researchers: 8, signals: 15, trend: 'hiring_surge', score: 92},\n 'Anthropic': {researchers: 6, signals: 12, trend: 'talent_cluster', score: 88},\n 'Google DeepMind': {researchers: 12, signals: 10, trend: 'steady', score: 85},\n 'Meta AI': {researchers: 10, signals: 8, trend: 'moderate', score: 78},\n 'Microsoft Research': {researchers: 9, signals: 7, trend: 'steady', score: 76}\n },\n top_researchers: [\n {name: 'Ilya Sutskever', company: 'OpenAI', influence: 98, h_index: 118},\n {name: 'Dario Amodei', company: 'Anthropic', influence: 92, h_index: 72},\n {name: 'Demis Hassabis', company: 'Google DeepMind', influence: 96, h_index: 95},\n {name: 'Yann LeCun', company: 'Meta AI', influence: 94, h_index: 150},\n {name: 'Andrew Ng', company: 'DeepLearning.AI', influence: 95, h_index: 110}\n ],\n investment_signals: [\n {company: 'OpenAI', signal: 'STRONG_BUY', score: 92, reason: 'Exceptional talent concentration'},\n {company: 'Anthropic', signal: 'STRONG_BUY', score: 88, reason: 'Rapid talent acquisition'},\n {company: 'Google DeepMind', signal: 'BUY', score: 85, reason: 'Strong research output'},\n {company: 'Meta AI', signal: 'HOLD', score: 78, reason: 'Stable talent base'},\n {company: 'Microsoft Research', signal: 'HOLD', score: 76, reason: 'Consistent performance'}\n ],\n key_trends: [\n 'OpenAI experiencing hiring surge in Q1 2024',\n 'Anthropic forming talent clusters from ex-OpenAI researchers',\n 'Google DeepMind focusing on multimodal AI research',\n 'Meta AI investing heavily in open-source LLMs',\n 'Increased movement of researchers into AI safety roles'\n ],\n alerts: [\n {type: 'critical', message: 'OpenAI hired 3 senior researchers in last 30 days', priority: 1},\n {type: 'high', message: 'Anthropic talent score increased 15% this quarter', priority: 2},\n {type: 'medium', message: 'New AI safety research center announced', priority: 3}\n ]\n};\n\nreturn { json: report };" }, "id": "9011ec1e-2b64-439f-9cf5-02098d3ef465", "name": "๐Ÿ“‹ Generate Intelligence Report", "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ -848, 304 ] }, { "parameters": { "operation": "executeQuery", "query": "-- Save report summary\nINSERT INTO company_metrics (company_name, metric_date, total_researchers, talent_score, calculated_at)\nVALUES \n ('OpenAI', CURRENT_DATE, 8, 92, NOW()),\n ('Anthropic', CURRENT_DATE, 6, 88, NOW()),\n ('Google DeepMind', CURRENT_DATE, 12, 85, NOW()),\n ('Meta AI', CURRENT_DATE, 10, 78, NOW()),\n ('Microsoft Research', CURRENT_DATE, 9, 76, NOW())\nON CONFLICT (company_name, metric_date) \nDO UPDATE SET\n total_researchers = EXCLUDED.total_researchers,\n talent_score = EXCLUDED.talent_score,\n calculated_at = NOW()\nRETURNING company_name, talent_score;", "options": {} }, "id": "c2d8aef1-7145-43f3-b62b-533c02e111e6", "name": "๐Ÿ’พ Save to Database", "type": "n8n-nodes-base.postgres", "typeVersion": 2.4, "position": [ -560, 304 ] }, { "parameters": { "jsCode": "// Generate HTML email report\nconst report = $input.first().json;\n\nconst html = `\n\n\n\n \n\n\n

๐Ÿš€ AI Talent Intelligence Report

\n

Generated: ${new Date(report.generated_at).toLocaleString()}

\n \n
\n

๐Ÿ“Š Executive Summary

\n
\n
${report.summary.unique_companies}
\n
Companies Tracked
\n
\n
\n
${report.summary.unique_researchers}
\n
Top Researchers
\n
\n
\n
${report.summary.avg_significance}/10
\n
Avg Signal Strength
\n
\n
\n\n

๐ŸŽฏ Investment Signals

\n \n \n \n \n \n \n \n ${report.investment_signals.map(s => `\n \n \n \n \n \n \n `).join('')}\n
CompanySignalScoreReasoning
${s.company}${s.signal}${s.score}/100${s.reason}
\n\n

๐Ÿ‘ฅ Top Researchers

\n \n \n \n \n \n \n \n ${report.top_researchers.map(r => `\n \n \n \n \n \n \n `).join('')}\n
NameCompanyInfluenceH-Index
${r.name}${r.company}${r.influence}/100${r.h_index}
\n\n

๐Ÿ”ฅ Key Trends

\n \n\n

โš ๏ธ Priority Alerts

\n ${report.alerts.map(a => `\n
\n ${a.type.toUpperCase()}: ${a.message}\n
\n `).join('')}\n\n
\n

This report was automatically generated by the Mycroft AI Talent Intelligence System.

\n

Data sources: ArXiv, Google News, Internal Database | Analysis powered by OpenAI

\n
\n\n\n`;\n\nreturn {\n json: {\n subject: `AI Talent Intelligence Report - ${new Date().toLocaleDateString()}`,\n html: html,\n report_data: report\n }\n};" }, "id": "41999ed7-2473-45f7-b38b-69ffbbf3b6a9", "name": "๐Ÿ“ง Format Email Report", "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ -736, 512 ] }, { "parameters": { "fromEmail": "REPLACE_WITH_FROMEMAIL", "toEmail": "REPLACE_WITH_TOEMAIL", "subject": "={{ $json.subject }}", "html": "={{ $json.html }}", "options": {} }, "id": "69adb9ec-e84d-4401-ba44-56f2076c4ff3", "name": "๐Ÿ“ฌ Send Email Report", "type": "n8n-nodes-base.emailSend", "typeVersion": 2.1, "position": [ -496, 512 ] }, { "parameters": { "jsCode": "// Mock researcher data\nconst mockResearchers = [\n {\n name: 'Ilya Sutskever',\n current_company: 'OpenAI',\n h_index: 118,\n influence_score: 98,\n last_updated: new Date().toISOString()\n },\n {\n name: 'Dario Amodei',\n current_company: 'Anthropic',\n h_index: 72,\n influence_score: 92,\n last_updated: new Date().toISOString()\n },\n {\n name: 'Demis Hassabis',\n current_company: 'Google DeepMind',\n h_index: 95,\n influence_score: 96,\n last_updated: new Date().toISOString()\n },\n {\n name: 'Yann LeCun',\n current_company: 'Meta AI',\n h_index: 150,\n influence_score: 94,\n last_updated: new Date().toISOString()\n }\n];\n\nreturn mockResearchers.map(r => ({ json: r }));" }, "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ -2384, 672 ], "id": "ba02c351-ae04-4cac-b1b5-28381e419b34", "name": "Code" }, { "parameters": { "numberInputs": 3 }, "type": "n8n-nodes-base.merge", "typeVersion": 3.2, "position": [ -2016, 416 ], "id": "18ac0362-f0a0-4a88-bc8c-3396aa5aecac", "name": "Merge" }, { "parameters": { "options": {} }, "type": "@n8n/n8n-nodes-langchain.chatTrigger", "typeVersion": 1.1, "position": [ -1776, 80 ], "id": "24d4d54c-51e3-499e-ab17-18d6bedaa196", "name": "When chat message received" }, { "parameters": { "promptType": "define", "text": "=Analyze this AI talent intelligence data:\n\n{{ JSON.stringify($json, null, 2) }}\n\nExtract and return ONLY a JSON object with these exact keys:\n{\n \"companies\": [\"company1\", \"company2\"],\n \"researchers\": [\"name1\", \"name2\"],\n \"technologies\": [\"tech1\", \"tech2\"],\n \"sentiment\": \"positive\",\n \"significance\": 8\n}\n\nReturn ONLY valid JSON, no other text.", "batching": {} }, "type": "@n8n/n8n-nodes-langchain.chainLlm", "typeVersion": 1.7, "position": [ -1792, 320 ], "id": "4ca6e77c-9af4-4b87-8cb5-7392bed95b6e", "name": "Basic LLM Chain" }, { "parameters": { "model": "llama-3.1-8b-instant", "options": {} }, "type": "@n8n/n8n-nodes-langchain.lmChatGroq", "typeVersion": 1, "position": [ -1728, 448 ], "id": "4e1dbb6f-9da2-46e3-8749-f84992ccfa02", "name": "Groq Chat Model" }, { "id": "d3939f2c-b842-58cc-92bb-4bad56bfef1a", "name": "Publication ยท Overview and setup", "type": "n8n-nodes-base.stickyNote", "typeVersion": 1, "position": [ -3568, 0 ], "parameters": { "content": "# AI Talent Intelligence Agent\n\n## Purpose and structure\nThis folder contains the **AI Talent Intelligence Agent** workflow. Its executable nodes use `aggregate`, `chainLlm`, `chatTrigger`, `code`, `emailSend`, `httpRequest`, `if`, `lmChatGroq`, `manualTrigger`, `merge`, `postgres`. The table and connection map below are derived from the JSON, not an inferred guarantee of behavior.\n\n## Setup\nImport inactive. Configure your own credentials and replace REPLACE_WITH_* values. Review external destinations and Code nodes before running.\n\n## Entry points\nโ–ถ๏ธ START - Run Complete Analysis, When chat message received\n\n## Verification\nSanitized source candidate; not runtime-tested. This overview is generated from node metadata. Read the folder README for the connection map, credential types, and license.\n\n## Attribution\nNik Bear Brown; rights confirmed 2026-10-19\nMIT; preserve source notices.", "width": 700, "height": 800, "color": 1 } } ], "connections": { "โ–ถ๏ธ START - Run Complete Analysis": { "main": [ [ { "node": "๐Ÿ“š SOURCE 1: ArXiv Papers", "type": "main", "index": 0 }, { "node": "๐Ÿ“ฐ SOURCE 2: News Search", "type": "main", "index": 0 }, { "node": "Code", "type": "main", "index": 0 } ] ] }, "๐Ÿ“š SOURCE 1: ArXiv Papers": { "main": [ [ { "node": "๐Ÿ”„ Parse ArXiv Data", "type": "main", "index": 0 } ] ] }, "๐Ÿ“ฐ SOURCE 2: News Search": { "main": [ [ { "node": "๐Ÿ”„ Parse News Data", "type": "main", "index": 0 } ] ] }, "๐Ÿ”„ Parse ArXiv Data": { "main": [ [ { "node": "Merge", "type": "main", "index": 0 } ] ] }, "๐Ÿ”„ Parse News Data": { "main": [ [ { "node": "Merge", "type": "main", "index": 1 } ] ] }, "๐Ÿ” FILTER: High Significance Only": { "main": [ [ { "node": "๐Ÿ“Š AGGREGATE Statistics", "type": "main", "index": 0 } ] ] }, "๐Ÿ“Š AGGREGATE Statistics": { "main": [ [ { "node": "๐Ÿ“‹ Generate Intelligence Report", "type": "main", "index": 0 } ] ] }, "๐Ÿ“‹ Generate Intelligence Report": { "main": [ [ { "node": "๐Ÿ’พ Save to Database", "type": "main", "index": 0 }, { "node": "๐Ÿ“ง Format Email Report", "type": "main", "index": 0 } ] ] }, "๐Ÿ’พ Save to Database": { "main": [ [] ] }, "๐Ÿ“ง Format Email Report": { "main": [ [ { "node": "๐Ÿ“ฌ Send Email Report", "type": "main", "index": 0 } ] ] }, "Code": { "main": [ [ { "node": "Merge", "type": "main", "index": 2 } ] ] }, "Merge": { "main": [ [ { "node": "Basic LLM Chain", "type": "main", "index": 0 } ] ] }, "Groq Chat Model": { "ai_languageModel": [ [ { "node": "Basic LLM Chain", "type": "ai_languageModel", "index": 0 } ] ] }, "When chat message received": { "main": [ [ { "node": "Basic LLM Chain", "type": "main", "index": 0 } ] ] }, "Basic LLM Chain": { "main": [ [ { "node": "๐Ÿ” FILTER: High Significance Only", "type": "main", "index": 0 } ] ] } }, "active": false, "settings": { "executionOrder": "v1" } }