{ "name": "Case 76 - Hiring Manager - Job Market Intelligence Tracker", "nodes": [ { "parameters": { "rule": { "interval": [ { "field": "cronExpression", "expression": "0 9 * * 1" } ] } }, "type": "n8n-nodes-base.scheduleTrigger", "typeVersion": 1.2, "position": [ -1200, -160 ], "id": "1a6b682a-f334-4f48-a937-1bf3a47b9b35", "name": "Weekly Schedule - Monday 9 AM" }, { "parameters": { "actorId": { "__rl": true, "value": "buIWk2uOUzTmcLsuB", "mode": "list", "cachedResultName": "Linkedin Post Search Scraper (No Cookies) (harvestapi/linkedin-post-search)", "cachedResultUrl": "https://console.apify.com/actors/buIWk2uOUzTmcLsuB/input" }, "customBody": "{\n \"authorUrls\": [\n \"https://www.linkedin.com/company/google\",\n \"https://www.linkedin.com/company/microsoft\",\n \"https://www.linkedin.com/company/meta\",\n \"https://www.linkedin.com/company/amazon\",\n \"https://www.linkedin.com/company/apple\",\n \"https://www.linkedin.com/company/salesforce\",\n \"https://www.linkedin.com/company/oracle\",\n \"https://www.linkedin.com/company/ibm\",\n \"https://www.linkedin.com/company/adobe\",\n \"https://www.linkedin.com/company/netflix\"\n ],\n \"searchKeywords\": [\n \"hiring\",\n \"we're looking for\",\n \"join our team\",\n \"now hiring\",\n \"careers\",\n \"job opening\"\n ],\n \"maxPosts\": 50,\n \"postedLimit\": \"week\",\n \"scrapeComments\": false,\n \"scrapeReactions\": false\n}" }, "type": "@apify/n8n-nodes-apify.apify", "typeVersion": 1, "position": [ -1024, -160 ], "id": "5ed270b0-d7a0-4a0e-8c79-b39ea4b1f069", "name": "Scrape LinkedIn Job Posts", "credentials": { "apifyApi": { "id": "TXPU4EgOj6rkzr43", "name": "Apify account 2" } } }, { "parameters": { "resource": "Datasets", "datasetId": "={{ $json.defaultDatasetId }}" }, "type": "@apify/n8n-nodes-apify.apify", "typeVersion": 1, "position": [ -832, -160 ], "id": "394c27b0-62a8-40a1-9f89-866f81023286", "name": "Get Dataset Items", "credentials": { "apifyApi": { "id": "w5S6YBbbyUddEfQA", "name": "Apify account" } } }, { "parameters": { "modelId": { "__rl": true, "value": "gpt-4o-mini", "mode": "list", "cachedResultName": "GPT-4o-mini" }, "responses": { "values": [ { "role": "system", "content": "=You are a Job Posting Validation Expert.\n\nAnalyze LinkedIn posts to determine if they are genuine job postings or hiring announcements.\n\nReturn ONLY valid JSON in this exact format:\n{\n \"is_job_posting\": \"yes|no\",\n \"confidence\": 0.95,\n \"reason\": \"brief explanation\"\n}\n\nCriteria for \"yes\" (genuine job posting):\n✅ Announces specific open position with job title\n✅ \"We're hiring for [role]\" messaging\n✅ Lists job requirements or qualifications\n✅ Mentions apply link or application process\n✅ Contains job description details\n✅ Recruiting team posting about open roles\n✅ \"Join our team as [role]\" announcements\n✅ Career page links to specific positions\n\nCriteria for \"no\" (NOT a job posting):\n❌ General \"we're growing\" without specific role\n❌ Employee spotlight or team celebration posts\n❌ Company culture posts without hiring intent\n❌ Metaphorical use of \"hiring\" or \"looking for\"\n❌ Reposting someone else's job search\n❌ Career advice posts\n❌ Recruiting tips for other recruiters\n❌ Alumni updates mentioning jobs casually\n\nRules:\n1. confidence: 0-1 scale (0.9+ for very clear job postings)\n2. reason: 1 sentence explaining the decision\n3. Be strict - require actual hiring intent with specific role\n4. Return ONLY the JSON object, no explanations" }, { "content": "=Analyze this LinkedIn post to determine if it's a genuine job posting:\n\nAuthor: {{ $json.author.name }}\nPost Date: {{ $json.postedAt.date }}\nPost Content: {{ $json.content }}\n\nReturn only JSON." } ] }, "builtInTools": {}, "options": {} }, "type": "@n8n/n8n-nodes-langchain.openAi", "typeVersion": 2.1, "position": [ -640, -160 ], "id": "3b1a7271-a1a2-4756-8369-72d52fb76048", "name": "AI Validation Filter", "credentials": { "openAiApi": { "id": "ICwxUBbatsF2sDvy", "name": "OpenAi account" } } }, { "parameters": { "jsCode": "// UNIVERSAL AI RESPONSE PARSER - Same code for ALL cases\nconst items = [];\nconst input = $input.all();\n\nfunction extractJSON(text) {\n const jsonMatch = text.match(/\\{[\\s\\S]*\\}/);\n if (!jsonMatch) return null;\n return jsonMatch[0];\n}\n\ninput.forEach((item, index) => {\n try {\n let aiText = item.json.output[0].content[0].text || '';\n \n // Clean markdown code blocks\n aiText = aiText\n .replace(/```json/gi, '')\n .replace(/```/g, '')\n .trim();\n \n // Extract JSON object\n const jsonStr = extractJSON(aiText);\n \n if (!jsonStr) {\n throw new Error('No JSON found in AI response');\n }\n \n // Parse and return clean JSON\n const parsed = JSON.parse(jsonStr);\n items.push({ json: parsed });\n \n } catch (error) {\n console.error(`Parse error for item ${index}:`, error.message);\n // Return empty object on error - no case-specific fields\n items.push({ json: {} });\n }\n});\n\nreturn items;" }, "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ -352, -160 ], "id": "ed8a30bd-ab3b-410a-bfc1-893ff4752d40", "name": "Parse AI Validation" }, { "parameters": { "assignments": { "assignments": [ { "id": "is_job_posting", "name": "is_job_posting", "value": "={{ $json.is_job_posting }}", "type": "string" }, { "id": "confidence", "name": "confidence", "value": "={{ $json.confidence }}", "type": "number" }, { "id": "reason", "name": "reason", "value": "={{ $json.reason }}", "type": "string" } ] }, "options": {} }, "type": "n8n-nodes-base.set", "typeVersion": 3.4, "position": [ -176, -160 ], "id": "d9eec5cc-890c-4767-bb37-b00cd69f5d38", "name": "Edit Fields - Validation" }, { "parameters": { "conditions": { "options": { "caseSensitive": true, "leftValue": "", "typeValidation": "strict", "version": 1 }, "conditions": [ { "id": "condition-001", "leftValue": "={{ $json.is_job_posting }}", "rightValue": "yes", "operator": { "type": "string", "operation": "equals" } } ], "combinator": "and" }, "options": {} }, "type": "n8n-nodes-base.filter", "typeVersion": 2, "position": [ 32, -160 ], "id": "bfb4f3a6-b2bb-42fb-bac6-d6d396707b3b", "name": "Filter Only Job Posts" }, { "parameters": { "modelId": { "__rl": true, "value": "gpt-4o-mini", "mode": "list", "cachedResultName": "GPT-4o-mini" }, "responses": { "values": [ { "role": "system", "content": "=You are a Job Market Intelligence Analyst.\n\nExtract structured job posting information from LinkedIn posts.\n\nReturn ONLY valid JSON in this exact format:\n{\n \"job_title\": \"exact role title\",\n \"seniority_level\": \"Entry|Mid|Senior|Executive|Unclear\",\n \"department\": \"Engineering|Sales|Marketing|Operations|Product|Finance|HR|Customer Success|Data|Design|Other\",\n \"required_skills\": [\"skill 1\", \"skill 2\", \"skill 3\"],\n \"location_type\": \"Remote|Hybrid|On-site|Not specified\",\n \"location_city\": \"City name if mentioned, otherwise 'Multiple' or 'Not specified'\",\n \"urgency_level\": \"Immediate|Normal|Future planning\",\n \"compensation_mentioned\": \"Yes - [range]|No\",\n \"competitive_intel\": \"Brief analysis of what this hiring reveals about company strategy (max 150 chars)\"\n}\n\nExtraction Rules:\n1. job_title: Extract exact role name from post\n2. seniority_level: Infer from title/requirements (Director+ = Executive, 5+ years = Senior, 2-5 = Mid, <2 = Entry)\n3. department: Choose most accurate category\n4. required_skills: Extract top 3-5 skills mentioned\n5. location_type: Remote/Hybrid/On-site based on post\n6. location_city: Extract city if mentioned\n7. urgency_level: Based on language (\"ASAP\", \"immediate\" = Immediate)\n8. compensation_mentioned: Include range if stated\n9. competitive_intel: Analyze strategic implications (expansion? new product? scaling?)\n\nReturn ONLY the JSON object, no explanations." }, { "content": "=Extract job market intelligence from this LinkedIn post:\n\nCompany: {{ $('Get Dataset Items').item.json.author.name }}\nPost Date: {{ $('Get Dataset Items').item.json.postedAt.date }}\nPost Content: {{ $('Get Dataset Items').item.json.content }}\nEngagement: {{ $('Get Dataset Items').item.json.engagement.likes }} likes, {{ $('Get Dataset Items').item.json.engagement.comments }} comments\n\nReturn only JSON." } ] }, "builtInTools": {}, "options": {} }, "type": "@n8n/n8n-nodes-langchain.openAi", "typeVersion": 2.1, "position": [ 192, -160 ], "id": "f5cc928d-f269-41b7-bc11-664612327490", "name": "AI Extract Job Intelligence", "credentials": { "openAiApi": { "id": "ICwxUBbatsF2sDvy", "name": "OpenAi account" } } }, { "parameters": { "jsCode": "// UNIVERSAL AI RESPONSE PARSER - Same code for ALL cases\nconst items = [];\nconst input = $input.all();\n\nfunction extractJSON(text) {\n const jsonMatch = text.match(/\\{[\\s\\S]*\\}/);\n if (!jsonMatch) return null;\n return jsonMatch[0];\n}\n\ninput.forEach((item, index) => {\n try {\n let aiText = item.json.output[0].content[0].text || '';\n \n // Clean markdown code blocks\n aiText = aiText\n .replace(/```json/gi, '')\n .replace(/```/g, '')\n .trim();\n \n // Extract JSON object\n const jsonStr = extractJSON(aiText);\n \n if (!jsonStr) {\n throw new Error('No JSON found in AI response');\n }\n \n // Parse and return clean JSON\n const parsed = JSON.parse(jsonStr);\n items.push({ json: parsed });\n \n } catch (error) {\n console.error(`Parse error for item ${index}:`, error.message);\n // Return empty object on error - no case-specific fields\n items.push({ json: {} });\n }\n});\n\nreturn items;" }, "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ 512, -160 ], "id": "a083d3e3-a90a-472b-ad99-5cb4f7cd9c07", "name": "Parse AI Response" }, { "parameters": { "assignments": { "assignments": [ { "id": "timestamp", "name": "analysis_timestamp", "value": "={{ new Date().toISOString() }}", "type": "string" }, { "id": "company_name", "name": "company_name", "value": "={{ $('Get Dataset Items').item.json.author?.name || 'unknown' }}", "type": "string" }, { "id": "company_profile", "name": "company_profile", "value": "={{ $('Get Dataset Items').item.json.author?.linkedinUrl || '' }}", "type": "string" }, { "id": "job_title", "name": "job_title", "value": "={{ $json.job_title }}", "type": "string" }, { "id": "seniority", "name": "seniority_level", "value": "={{ $json.seniority_level }}", "type": "string" }, { "id": "department", "name": "department", "value": "={{ $json.department }}", "type": "string" }, { "id": "skills", "name": "required_skills", "value": "={{ $json.required_skills }}", "type": "array" }, { "id": "location_type", "name": "location_type", "value": "={{ $json.location_type }}", "type": "string" }, { "id": "location_city", "name": "location_city", "value": "={{ $json.location_city }}", "type": "string" }, { "id": "urgency", "name": "urgency_level", "value": "={{ $json.urgency_level }}", "type": "string" }, { "id": "compensation", "name": "compensation_mentioned", "value": "={{ $json.compensation_mentioned }}", "type": "string" }, { "id": "intel", "name": "competitive_intel", "value": "={{ $json.competitive_intel }}", "type": "string" }, { "id": "post_content", "name": "post_content", "value": "={{ $('Get Dataset Items').item.json.content || '' }}", "type": "string" }, { "id": "post_date", "name": "post_date", "value": "={{ $('Get Dataset Items').item.json.postedAt?.date || '' }}", "type": "string" }, { "id": "post_url", "name": "post_url", "value": "={{ $('Get Dataset Items').item.json.linkedinUrl || '' }}", "type": "string" }, { "id": "likes", "name": "likes_count", "value": "={{ $('Get Dataset Items').item.json.engagement?.likes || 0 }}", "type": "number" }, { "id": "comments", "name": "comments_count", "value": "={{ $('Get Dataset Items').item.json.engagement?.comments || 0 }}", "type": "number" }, { "id": "shares", "name": "shares_count", "value": "={{ $('Get Dataset Items').item.json.engagement?.shares || 0 }}", "type": "number" }, { "id": "total_engagement", "name": "engagement_total", "value": "={{ ($('Get Dataset Items').item.json.engagement?.likes || 0) + ($('Get Dataset Items').item.json.engagement?.comments || 0) + ($('Get Dataset Items').item.json.engagement?.shares || 0) }}", "type": "number" } ] }, "options": {} }, "type": "n8n-nodes-base.set", "typeVersion": 3.4, "position": [ 704, -160 ], "id": "ce8e7106-13c5-4c8d-aec3-4fa6dd00aa1a", "name": "Edit Fields" }, { "parameters": { "operation": "append", "documentId": { "__rl": true, "value": "1E9cdTRB6J4yKJkrpkYEXdh1wCAodieUz6laM-yi1jmk", "mode": "list", "cachedResultName": "Case 76 - Job Market Intelligence Log", "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1E9cdTRB6J4yKJkrpkYEXdh1wCAodieUz6laM-yi1jmk/edit?usp=drivesdk" }, "sheetName": { "__rl": true, "value": "gid=0", "mode": "list", "cachedResultName": "Sheet1", "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1E9cdTRB6J4yKJkrpkYEXdh1wCAodieUz6laM-yi1jmk/edit#gid=0" }, "columns": { "mappingMode": "defineBelow", "value": { "Analysis_Date": "={{ $json.analysis_timestamp }}", "Company_Name": "={{ $json.company_name }}", "Job_Title": "={{ $json.job_title }}", "Seniority_Level": "={{ $json.seniority_level }}", "Department": "={{ $json.department }}", "Required_Skills": "={{ $json.required_skills.join('; ') }}", "Location_Type": "={{ $json.location_type }}", "Location_City": "={{ $json.location_city }}", "Urgency_Level": "={{ $json.urgency_level }}", "Compensation_Mentioned": "={{ $json.compensation_mentioned }}", "Competitive_Intel": "={{ $json.competitive_intel }}", "Post_Date": "={{ $json.post_date }}", "Likes": "={{ $json.likes_count }}", "Comments": "={{ $json.comments_count }}", "Shares": "={{ $json.shares_count }}", "Total_Engagement": "={{ $json.engagement_total }}", "Post_URL": "={{ $json.post_url }}", "Post_Content": "={{ $json.post_content }}" }, "matchingColumns": [], "schema": [ { "id": "Analysis_Date", "displayName": "Analysis_Date", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true }, { "id": "Company_Name", "displayName": "Company_Name", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true }, { "id": "Job_Title", "displayName": "Job_Title", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true }, { "id": "Seniority_Level", "displayName": "Seniority_Level", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true }, { "id": "Department", "displayName": "Department", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true }, { "id": "Required_Skills", "displayName": "Required_Skills", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true }, { "id": "Location_Type", "displayName": "Location_Type", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true }, { "id": "Location_City", "displayName": "Location_City", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true }, { "id": "Urgency_Level", "displayName": "Urgency_Level", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true }, { "id": "Compensation_Mentioned", "displayName": "Compensation_Mentioned", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true }, { "id": "Competitive_Intel", "displayName": "Competitive_Intel", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true }, { "id": "Post_Date", "displayName": "Post_Date", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true }, { "id": "Likes", "displayName": "Likes", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true }, { "id": "Comments", "displayName": "Comments", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true }, { "id": "Shares", "displayName": "Shares", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true }, { "id": "Total_Engagement", "displayName": "Total_Engagement", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true }, { "id": "Post_URL", "displayName": "Post_URL", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true }, { "id": "Post_Content", "displayName": "Post_Content", "required": false, "defaultMatch": false, "display": true, "type": "string", "canBeUsedToMatch": true } ], "attemptToConvertTypes": false, "convertFieldsToString": false }, "options": {} }, "type": "n8n-nodes-base.googleSheets", "typeVersion": 4.7, "position": [ 896, -160 ], "id": "e73544bd-2f3d-45d6-8991-edaf3d1a721d", "name": "Log to Google Sheet", "credentials": { "googleSheetsOAuth2Api": { "id": "LOs2dbk9lby0NfDM", "name": "Google Sheets account" } } }, { "parameters": { "jsCode": "// Aggregate all items from Google Sheets into email-ready summary\nconst allItems = $input.all();\n\n// Count by department\nconst departmentCounts = {};\nallItems.forEach(item => {\n const dept = item.json.Department || 'Other';\n departmentCounts[dept] = (departmentCounts[dept] || 0) + 1;\n});\n\nconst departmentBreakdown = Object.entries(departmentCounts)\n .sort((a, b) => b[1] - a[1]);\n\n// Count by seniority\nconst seniorityCounts = {};\nallItems.forEach(item => {\n const seniority = item.json.Seniority_Level || 'Unclear';\n seniorityCounts[seniority] = (seniorityCounts[seniority] || 0) + 1;\n});\n\n// Count by location type\nconst locationCounts = {};\nallItems.forEach(item => {\n const locationType = item.json.Location_Type || 'Not specified';\n locationCounts[locationType] = (locationCounts[locationType] || 0) + 1;\n});\n\n// Top skills mentioned\nconst skillCounts = {};\nallItems.forEach(item => {\n const skillsString = item.json.Required_Skills || '';\n if (skillsString) {\n const skills = skillsString.split(';').map(s => s.trim()).filter(s => s);\n skills.forEach(skill => {\n skillCounts[skill] = (skillCounts[skill] || 0) + 1;\n });\n }\n});\n\nconst topSkills = Object.entries(skillCounts)\n .sort((a, b) => b[1] - a[1])\n .slice(0, 10)\n .map(([skill, count]) => ({ skill, mentions: count }));\n\n// Top hiring companies\nconst companyCounts = {};\nallItems.forEach(item => {\n const company = item.json.Company_Name || 'Unknown';\n companyCounts[company] = (companyCounts[company] || 0) + 1;\n});\n\nconst topCompanies = Object.entries(companyCounts)\n .sort((a, b) => b[1] - a[1])\n .slice(0, 10)\n .map(([company, count]) => ({ company, jobs: count }));\n\n// Compensation analysis\nconst compensationMentioned = allItems.filter(item => \n item.json.Compensation_Mentioned && \n item.json.Compensation_Mentioned.toLowerCase().includes('yes')\n).length;\n\nconst compensationPercentage = Math.round((compensationMentioned / allItems.length) * 100);\n\n// Urgent hiring count\nconst urgentJobs = allItems.filter(item => \n item.json.Urgency_Level === 'Immediate'\n).length;\n\n// Build HTML table rows\nconst tableRows = allItems.map(item => {\n const data = item.json;\n \n return `\n \n ${data.Company_Name || 'N/A'}\n ${data.Job_Title || 'N/A'}\n ${data.Department || 'N/A'}\n ${data.Seniority_Level || 'N/A'}\n ${data.Location_Type || 'N/A'}\n ${data.Urgency_Level || 'N/A'}\n View\n \n `;\n}).join('');\n\n// Return single aggregated item\nreturn {\n json: {\n week_start: new Date(Date.now() - 7*24*60*60*1000).toISOString().split('T')[0],\n week_end: new Date().toISOString().split('T')[0],\n total_jobs_analyzed: allItems.length,\n department_breakdown: departmentBreakdown,\n seniority_breakdown: Object.entries(seniorityCounts),\n location_breakdown: Object.entries(locationCounts),\n top_skills: topSkills,\n top_companies: topCompanies,\n compensation_percentage: compensationPercentage,\n urgent_jobs_count: urgentJobs,\n table_rows: tableRows,\n all_jobs: allItems.map(item => item.json)\n }\n};" }, "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ 1088, -160 ], "id": "77f7ab8f-e0f9-40a1-b145-23bb568e241a", "name": "Aggregate Weekly Summary" }, { "parameters": { "sendTo": "hiring-team@yourcompany.com", "subject": "=📊 Weekly Job Market Intelligence Report: {{ $json.week_start }} to {{ $json.week_end }}", "message": "=WEEKLY JOB MARKET INTELLIGENCE REPORT\n================================================\nReport Period: {{ $json.week_start }} to {{ $json.week_end }}\n\nOVERVIEW:\nTotal Job Postings Analyzed: {{ $json.total_jobs_analyzed }}\nUrgent Hiring Signals: {{ $json.urgent_jobs_count }}\nCompensation Mentioned: {{ $json.compensation_percentage }}% of postings\n\nTOP HIRING DEPARTMENTS:\n{{ $json.department_breakdown.slice(0, 5).map(([dept, count]) => dept + ': ' + count + ' positions').join('\\n') }}\n\nSENIORITY BREAKDOWN:\n{{ $json.seniority_breakdown.map(([level, count]) => level + ': ' + count).join('\\n') }}\n\nLOCATION TYPE DISTRIBUTION:\n{{ $json.location_breakdown.map(([type, count]) => type + ': ' + count).join('\\n') }}\n\nTOP 10 IN-DEMAND SKILLS:\n{{ $json.top_skills.map((skill, i) => (i+1) + '. ' + skill.skill + ' (' + skill.mentions + ' mentions)').join('\\n') }}\n\nTOP 10 HIRING COMPANIES:\n{{ $json.top_companies.map((company, i) => (i+1) + '. ' + company.company + ' (' + company.jobs + ' positions)').join('\\n') }}\n\nFull job details in Google Sheets.\n\nGenerated: {{ new Date().toLocaleDateString() }}", "options": {} }, "type": "n8n-nodes-base.gmail", "typeVersion": 2.1, "position": [ 1280, -160 ], "id": "cdc6aae6-4a0f-4e73-9bca-be9d3b474b3c", "name": "Send Weekly Summary Email", "webhookId": "4d2ba76c-a033-40d1-9d69-bcad351e74f4", "credentials": { "gmailOAuth2": { "id": "cyqCGWcggZNMcSOv", "name": "Gmail account" } } } ], "pinData": {}, "connections": { "Weekly Schedule - Monday 9 AM": { "main": [ [ { "node": "Scrape LinkedIn Job Posts", "type": "main", "index": 0 } ] ] }, "Scrape LinkedIn Job Posts": { "main": [ [ { "node": "Get Dataset Items", "type": "main", "index": 0 } ] ] }, "Get Dataset Items": { "main": [ [ { "node": "AI Validation Filter", "type": "main", "index": 0 } ] ] }, "AI Validation Filter": { "main": [ [ { "node": "Parse AI Validation", "type": "main", "index": 0 } ] ] }, "Parse AI Validation": { "main": [ [ { "node": "Edit Fields - Validation", "type": "main", "index": 0 } ] ] }, "Edit Fields - Validation": { "main": [ [ { "node": "Filter Only Job Posts", "type": "main", "index": 0 } ] ] }, "Filter Only Job Posts": { "main": [ [ { "node": "AI Extract Job Intelligence", "type": "main", "index": 0 } ] ] }, "AI Extract Job Intelligence": { "main": [ [ { "node": "Parse AI Response", "type": "main", "index": 0 } ] ] }, "Parse AI Response": { "main": [ [ { "node": "Edit Fields", "type": "main", "index": 0 } ] ] }, "Edit Fields": { "main": [ [ { "node": "Log to Google Sheet", "type": "main", "index": 0 } ] ] }, "Log to Google Sheet": { "main": [ [ { "node": "Aggregate Weekly Summary", "type": "main", "index": 0 } ] ] }, "Aggregate Weekly Summary": { "main": [ [ { "node": "Send Weekly Summary Email", "type": "main", "index": 0 } ] ] } }, "active": false, "settings": { "executionOrder": "v1" }, "versionId": "e9a6d40a-cbe2-49fe-bd4e-926c8afd3e42", "meta": { "instanceId": "3a43da28588548e21903e71cf1dc3ddd65c24bf0c62e7e4b77542ffe87ad79c6" }, "id": "nJbUXIXdNzaQhzLD", "tags": [] }