This workflow follows the HTTP Request → Postgres 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 →
{
"updatedAt": "2026-04-04T14:22:24.369Z",
"createdAt": "2026-04-02T17:11:49.013Z",
"id": "c22XxluRJOWGj4RW",
"name": "WF6-PREP: Interview Prep Brief Generator",
"description": null,
"active": true,
"isArchived": false,
"nodes": [
{
"parameters": {
"rule": {
"interval": [
{
"field": "minutes",
"minutesInterval": 30
}
]
}
},
"id": "schedule-trigger",
"name": "Every 30 Minutes",
"type": "n8n-nodes-base.scheduleTrigger",
"typeVersion": 1.2,
"position": [
0,
0
]
},
{
"parameters": {
"operation": "executeQuery",
"query": "SELECT i.id AS interview_id, i.company_name, i.role_title, i.interview_track, i.interview_format, i.interview_stage, i.interview_date, i.interview_start_time, i.interview_end_time, i.interview_duration_minutes, i.location_type, i.physical_address, i.video_platform, i.video_link, i.interviewer_names, i.interviewer_titles, i.what_to_prepare, i.what_to_bring, i.dress_code, i.additional_instructions, i.application_id, i.detection_confidence FROM interviews i WHERE tenant_id = '{{ $('Loop Over Tenants').item.json.tenant_id }}' AND i.status IN ('calendared', 'parsed', 'pending_confirmation') AND i.interview_date >= CURRENT_DATE AND i.prep_failed = false AND NOT EXISTS (SELECT 1 FROM prep_briefs pb WHERE pb.interview_id = i.id) ORDER BY i.interview_date ASC, i.interview_start_time ASC LIMIT 5;",
"options": {}
},
"id": "find-interviews",
"name": "Find Interviews Needing Prep",
"type": "n8n-nodes-base.postgres",
"typeVersion": 2.5,
"position": [
620,
0
],
"credentials": {
"postgres": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"conditions": {
"options": {
"caseSensitive": true,
"leftValue": "",
"typeValidation": "strict"
},
"conditions": [
{
"id": "has-results",
"leftValue": "={{ $json.interview_id }}",
"rightValue": "",
"operator": {
"type": "string",
"operation": "isNotEmpty"
}
}
],
"combinator": "and"
},
"options": {}
},
"id": "check-results",
"name": "Has Interviews?",
"type": "n8n-nodes-base.if",
"typeVersion": 2.2,
"position": [
840,
0
]
},
{
"parameters": {
"operation": "executeQuery",
"query": "SELECT cr.research_data, cr.research_completeness, cr.researched_at FROM company_research cr WHERE cr.company_name_normalised = LOWER(REGEXP_REPLACE('{{ $json.company_name }}', '\\s+(Ltd|PLC|LLP|Limited|Inc)\\.?$', '', 'i')) AND cr.expires_at > NOW() LIMIT 1;",
"options": {}
},
"id": "get-company-research",
"name": "Get Company Research",
"type": "n8n-nodes-base.postgres",
"typeVersion": 2.5,
"position": [
1060,
0
],
"credentials": {
"postgres": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"operation": "executeQuery",
"query": "SELECT sr.salary_min, sr.salary_max, sr.salary_median, sr.salary_currency, sr.academic_grade, sr.spine_point_min, sr.spine_point_max, sr.typical_bonus_percentage, sr.typical_pension_percentage, sr.benefits_notes FROM salary_research sr WHERE sr.role_title_normalised = LOWER('{{ $json.role_title }}') AND sr.expires_at > NOW() ORDER BY sr.researched_at DESC LIMIT 1;",
"options": {}
},
"id": "get-salary-research",
"name": "Get Salary Research",
"type": "n8n-nodes-base.postgres",
"typeVersion": 2.5,
"position": [
1060,
220
],
"credentials": {
"postgres": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"jsCode": "// Assemble the prompt context for Claude Sonnet\nconst interview = $('Has Interviews?').first().json;\nconst companyData = $('Get Company Research').first().json;\nconst salaryData = $('Get Salary Research').first().json;\n\nconst companyResearch = companyData.research_data \n ? `COMPANY RESEARCH:\\n${JSON.stringify(companyData.research_data, null, 2)}\\nResearch completeness: ${companyData.research_completeness || 'none'}`\n : 'COMPANY RESEARCH: No cached research available. Use publicly known information about this company.';\n\nconst salaryInfo = salaryData.salary_min\n ? `SALARY INTELLIGENCE:\\n- Range: ${salaryData.salary_currency || 'GBP'} ${salaryData.salary_min} - ${salaryData.salary_max}\\n- Median: ${salaryData.salary_currency || 'GBP'} ${salaryData.salary_median}\\n- Typical bonus: ${salaryData.typical_bonus_percentage || 'N/A'}%\\n- Typical pension: ${salaryData.typical_pension_percentage || 'N/A'}%\\n- Benefits notes: ${salaryData.benefits_notes || 'N/A'}`\n : 'SALARY INTELLIGENCE: No cached salary data. Provide general UK market guidance for this role level.';\n\nconst interviewerInfo = interview.interviewer_names && interview.interviewer_names.length > 0\n ? `INTERVIEWERS: ${interview.interviewer_names.join(', ')}${interview.interviewer_titles ? ' (' + interview.interviewer_titles.join(', ') + ')' : ''}`\n : 'INTERVIEWERS: Not specified';\n\nconst prompt = `Generate a comprehensive interview preparation brief for the following interview.\n\nCANDIDATE PROFILE:\n- PhD + MBA professional with 18 years of HR/L&D experience\n- Currently targeting UK L&D Manager to Head of L&D roles (corporate) and Lecturer/Senior Lecturer positions (academic)\n- Target salary: GBP 70,000-80,000 (corporate) or appropriate academic grade\n- Location: Maidenhead, UK\n- Key strengths: stakeholder management, programme design & delivery, ROI measurement, change management, digital learning strategy\n- 90% callback-to-offer rate\n\nINTERVIEW DETAILS:\n- Company: ${interview.company_name}\n- Role: ${interview.role_title}\n- Track: ${interview.interview_track}\n- Format: ${interview.interview_format}\n- Stage: ${interview.interview_stage || 'Not specified'}\n- Date: ${interview.interview_date}\n- Time: ${interview.interview_start_time || 'TBC'} - ${interview.interview_end_time || 'TBC'}\n- Duration: ${interview.interview_duration_minutes || 60} minutes\n- Location type: ${interview.location_type || 'Not specified'}\n- Physical address: ${interview.physical_address || 'N/A'}\n- Video platform: ${interview.video_platform || 'N/A'}\n${interviewerInfo}\n- What to prepare: ${interview.what_to_prepare || 'Not specified'}\n- What to bring: ${interview.what_to_bring || 'Not specified'}\n- Dress code: ${interview.dress_code || 'Not specified'}\n- Additional instructions: ${interview.additional_instructions || 'None'}\n\n${companyResearch}\n\n${salaryInfo}\n\nPlease generate a structured preparation brief with these sections:\n\n1. **COMPANY OVERVIEW** - Key facts, culture, recent news, strategic direction\n2. **ROLE ANALYSIS** - Key requirements, likely priorities, challenges the hiring manager faces\n3. **YOUR FIT** - How the candidate's experience maps to role requirements, key selling points\n4. **LIKELY QUESTIONS** (${interview.interview_track === 'academic' ? 'academic format: teaching philosophy, research alignment, REF impact' : 'UK competency-based STAR format'}) - 8-10 questions with suggested STAR response angles\n5. **QUESTIONS TO ASK** - 5-7 intelligent questions that demonstrate understanding and genuine interest\n6. **SALARY & NEGOTIATION INTELLIGENCE** - Market rates, negotiation leverage points, benefits to discuss\n7. **LOGISTICS & FORMAT TIPS** - Format-specific advice, technology checks, timing\n8. **FINAL CHECKLIST** - Day-before and day-of checklist items\n\nBe specific to this company and role. Avoid generic advice. Reference UK employment practices and norms.`;\n\nreturn {\n interview_id: interview.interview_id,\n company_name: interview.company_name,\n role_title: interview.role_title,\n interview_date: interview.interview_date,\n interview_track: interview.interview_track,\n prompt: prompt\n};"
},
"id": "assemble-prompt",
"name": "Assemble Prompt",
"type": "n8n-nodes-base.code",
"typeVersion": 2,
"position": [
1280,
0
]
},
{
"parameters": {
"method": "POST",
"url": "https://api.anthropic.com/v1/messages",
"sendHeaders": true,
"headerParameters": {
"parameters": [
{
"name": "x-api-key",
"value": "={{ $credentials.anthropicApi.apiKey }}"
},
{
"name": "anthropic-version",
"value": "2023-06-01"
},
{
"name": "content-type",
"value": "application/json"
}
]
},
"sendBody": true,
"specifyBody": "json",
"jsonBody": "={\n \"model\": \"claude-sonnet-4-20250514\",\n \"max_tokens\": 8000,\n \"temperature\": 0.3,\n \"system\": \"You are an expert career coach and interview preparation specialist with deep knowledge of UK corporate L&D and UK higher education hiring practices. Generate thorough, specific, actionable preparation briefs.\",\n \"messages\": [\n {\n \"role\": \"user\",\n \"content\": {{ JSON.stringify($json.prompt) }}\n }\n ]\n}",
"options": {
"timeout": 120000
}
},
"id": "claude-sonnet",
"name": "Claude Sonnet: Generate Brief",
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 4.2,
"position": [
1500,
0
],
"credentials": {
"httpCustomAuth": {
"name": "<your credential>"
}
},
"onError": "continueRegularOutput"
},
{
"parameters": {
"jsCode": "const input = $('Assemble Prompt').first().json;\nconst response = $('Claude Sonnet: Generate Brief').first().json;\n\n// Check for API error\nif (response.error || !response.content || !response.content[0]) {\n return {\n interview_id: input.interview_id,\n company_name: input.company_name,\n role_title: input.role_title,\n success: false,\n error: response.error?.message || 'No content in Claude response'\n };\n}\n\nconst briefText = response.content[0].text;\nconst usage = response.usage || {};\n\n// Extract sections using regex\nconst sections = {};\nconst sectionPatterns = [\n { key: 'company_overview', pattern: /\\*\\*(?:1\\.\\s*)?COMPANY OVERVIEW\\*\\*([\\s\\S]*?)(?=\\n\\*\\*(?:2\\.|ROLE)|$)/i },\n { key: 'role_analysis', pattern: /\\*\\*(?:2\\.\\s*)?ROLE ANALYSIS\\*\\*([\\s\\S]*?)(?=\\n\\*\\*(?:3\\.|YOUR)|$)/i },\n { key: 'candidate_fit', pattern: /\\*\\*(?:3\\.\\s*)?YOUR FIT\\*\\*([\\s\\S]*?)(?=\\n\\*\\*(?:4\\.|LIKELY)|$)/i },\n { key: 'likely_questions', pattern: /\\*\\*(?:4\\.\\s*)?LIKELY QUESTIONS\\*\\*([\\s\\S]*?)(?=\\n\\*\\*(?:5\\.|QUESTIONS TO)|$)/i },\n { key: 'questions_to_ask', pattern: /\\*\\*(?:5\\.\\s*)?QUESTIONS TO ASK\\*\\*([\\s\\S]*?)(?=\\n\\*\\*(?:6\\.|SALARY)|$)/i },\n { key: 'salary_intelligence', pattern: /\\*\\*(?:6\\.\\s*)?SALARY.*?INTELLIGENCE\\*\\*([\\s\\S]*?)(?=\\n\\*\\*(?:7\\.|LOGISTICS)|$)/i },\n { key: 'logistics_and_format', pattern: /\\*\\*(?:7\\.\\s*)?LOGISTICS.*?\\*\\*([\\s\\S]*?)(?=\\n\\*\\*(?:8\\.|FINAL)|$)/i },\n { key: 'final_checklist', pattern: /\\*\\*(?:8\\.\\s*)?FINAL CHECKLIST\\*\\*([\\s\\S]*?)$/i }\n];\n\nfor (const sp of sectionPatterns) {\n const match = briefText.match(sp.pattern);\n sections[sp.key] = match ? match[1].trim() : null;\n}\n\n// Calculate cost (Sonnet pricing: $3/MTok input, $15/MTok output)\nconst inputTokens = usage.input_tokens || 0;\nconst outputTokens = usage.output_tokens || 0;\nconst costUsd = (inputTokens * 3 / 1000000) + (outputTokens * 15 / 1000000);\n\nreturn {\n interview_id: input.interview_id,\n company_name: input.company_name,\n role_title: input.role_title,\n interview_date: input.interview_date,\n interview_track: input.interview_track,\n full_brief_text: briefText,\n sections: sections,\n model_used: 'claude-sonnet-4-20250514',\n prompt_tokens: inputTokens,\n completion_tokens: outputTokens,\n generation_cost_usd: costUsd,\n success: true\n};"
},
"id": "parse-brief",
"name": "Parse Brief Sections",
"type": "n8n-nodes-base.code",
"typeVersion": 2,
"position": [
1720,
0
]
},
{
"parameters": {
"conditions": {
"options": {
"caseSensitive": true,
"leftValue": "",
"typeValidation": "strict"
},
"conditions": [
{
"id": "check-success",
"leftValue": "={{ $json.success }}",
"rightValue": true,
"operator": {
"type": "boolean",
"operation": "true"
}
}
],
"combinator": "and"
},
"options": {}
},
"id": "check-success",
"name": "Brief Generated?",
"type": "n8n-nodes-base.if",
"typeVersion": 2.2,
"position": [
1940,
0
]
},
{
"parameters": {
"operation": "executeQuery",
"query": "INSERT INTO prep_briefs (tenant_id, interview_id, company_overview, role_analysis, candidate_fit, likely_questions, questions_to_ask, salary_intelligence, logistics_and_format, final_checklist, full_brief_text, brief_format, model_used, prompt_tokens, completion_tokens, generation_cost_usd, generation_attempts) VALUES ('{{ $('Loop Over Tenants').item.json.tenant_id }}', '{{ $json.interview_id }}', {{ $json.sections.company_overview ? \"'\" + $json.sections.company_overview.replace(/'/g, \"''\") + \"'\" : 'NULL' }}, {{ $json.sections.role_analysis ? \"'\" + $json.sections.role_analysis.replace(/'/g, \"''\") + \"'\" : 'NULL' }}, {{ $json.sections.candidate_fit ? \"'\" + $json.sections.candidate_fit.replace(/'/g, \"''\") + \"'\" : 'NULL' }}, {{ $json.sections.likely_questions ? \"'\" + JSON.stringify($json.sections.likely_questions).replace(/'/g, \"''\") + \"'::jsonb\" : 'NULL' }}, {{ $json.sections.questions_to_ask ? \"'\" + JSON.stringify($json.sections.questions_to_ask).replace(/'/g, \"''\") + \"'::jsonb\" : 'NULL' }}, {{ $json.sections.salary_intelligence ? \"'\" + $json.sections.salary_intelligence.replace(/'/g, \"''\") + \"'\" : 'NULL' }}, {{ $json.sections.logistics_and_format ? \"'\" + $json.sections.logistics_and_format.replace(/'/g, \"''\") + \"'\" : 'NULL' }}, {{ $json.sections.final_checklist ? \"'\" + $json.sections.final_checklist.replace(/'/g, \"''\") + \"'\" : 'NULL' }}, '{{ $json.full_brief_text.replace(/'/g, \"''\") }}', 'markdown', '{{ $json.model_used }}', {{ $json.prompt_tokens }}, {{ $json.completion_tokens }}, {{ $json.generation_cost_usd }}, 1) RETURNING id;",
"options": {}
},
"id": "save-brief",
"name": "Save Brief to DB",
"type": "n8n-nodes-base.postgres",
"typeVersion": 2.5,
"position": [
2160,
-100
],
"credentials": {
"postgres": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"method": "POST",
"url": "https://api.resend.com/emails",
"sendHeaders": true,
"headerParameters": {
"parameters": [
{
"name": "Authorization",
"value": "Bearer re_PMdG3JAg_Er4o7VYY74tek5WzMqmqBJ15"
},
{
"name": "Content-type",
"value": "application/json"
}
]
},
"sendBody": true,
"specifyBody": "json",
"jsonBody": "={\n \"from\": \"Selvi Job App <jobs@apiloom.io>\",\n \"to\": [\"{{ $('Loop Over Tenants').item.json.notification_email }}\"],\n \"subject\": \"Prep Ready: {{ $('Parse Brief Sections').first().json.company_name }} - {{ $('Parse Brief Sections').first().json.role_title }} ({{ $('Parse Brief Sections').first().json.interview_date }})\",\n \"html\": \"<h2>Interview Preparation Brief</h2><h3>{{ $('Parse Brief Sections').first().json.company_name }} — {{ $('Parse Brief Sections').first().json.role_title }}</h3><p><strong>Date:</strong> {{ $('Parse Brief Sections').first().json.interview_date }} | <strong>Track:</strong> {{ $('Parse Brief Sections').first().json.interview_track }}</p><hr>\" + {{ JSON.stringify($('Parse Brief Sections').first().json.full_brief_text.replace(/\\n/g, '<br>')) }} + \"<hr><p><em>Selvi Job App — Module 6: Interview Preparation</em></p>\"\n}",
"options": {
"timeout": 30000
}
},
"id": "email-brief",
"name": "Email Brief to Candidate",
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 4.2,
"position": [
2380,
-100
]
},
{
"parameters": {
"operation": "executeQuery",
"query": "UPDATE interviews SET status = 'prep_ready', updated_at = NOW() WHERE tenant_id = '{{ $('Loop Over Tenants').item.json.tenant_id }}' AND id = '{{ $('Parse Brief Sections').first().json.interview_id }}' AND status NOT IN ('completed', 'cancelled_by_employer', 'cancelled_by_candidate');",
"options": {}
},
"id": "update-status-ready",
"name": "Update Interview Status",
"type": "n8n-nodes-base.postgres",
"typeVersion": 2.5,
"position": [
2600,
-100
],
"credentials": {
"postgres": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"operation": "executeQuery",
"query": "UPDATE prep_briefs SET delivered_at = NOW() WHERE interview_id = '{{ $('Parse Brief Sections').first().json.interview_id }}' AND delivered_at IS NULL;",
"options": {}
},
"id": "mark-delivered",
"name": "Mark Brief Delivered",
"type": "n8n-nodes-base.postgres",
"typeVersion": 2.5,
"position": [
2600,
100
],
"credentials": {
"postgres": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"operation": "executeQuery",
"query": "UPDATE interviews SET prep_failed = true, prep_failed_at = NOW(), prep_failed_reason = '{{ $json.error ? $json.error.substring(0, 500).replace(/'/g, \"''\") : \"Unknown error\" }}' WHERE tenant_id = '{{ $('Loop Over Tenants').item.json.tenant_id }}' AND id = '{{ $json.interview_id }}';",
"options": {}
},
"id": "mark-prep-failed",
"name": "Mark Prep Failed",
"type": "n8n-nodes-base.postgres",
"typeVersion": 2.5,
"position": [
2160,
200
],
"credentials": {
"postgres": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"method": "POST",
"url": "https://api.resend.com/emails",
"sendHeaders": true,
"headerParameters": {
"parameters": [
{
"name": "Authorization",
"value": "Bearer re_PMdG3JAg_Er4o7VYY74tek5WzMqmqBJ15"
},
{
"name": "Content-type",
"value": "application/json"
}
]
},
"sendBody": true,
"specifyBody": "json",
"jsonBody": "={\n \"from\": \"Selvi Job App <jobs@apiloom.io>\",\n \"to\": [\"{{ $('Loop Over Tenants').item.json.notification_email }}\"],\n \"subject\": \"Prep Brief Failed: {{ $json.company_name }} - {{ $json.role_title }}\",\n \"html\": \"<h3>Prep Brief Generation Failed</h3><p>The interview preparation brief for <strong>{{ $json.company_name }} - {{ $json.role_title }}</strong> could not be generated.</p><p><strong>Error:</strong> {{ $json.error || 'Unknown error' }}</p><p>Manual preparation recommended.</p><hr><p><em>Selvi Job App — Module 6</em></p>\"\n}",
"options": {}
},
"id": "email-failure",
"name": "Email Failure Notice",
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 4.2,
"position": [
2380,
200
]
},
{
"parameters": {
"operation": "executeQuery",
"query": "SELECT id AS tenant_id, name AS tenant_name, notification_email, candidate_profile, search_config, email_config FROM tenants WHERE is_active = true",
"options": {}
},
"id": "fetch_tenants",
"name": "Fetch Active Tenants",
"type": "n8n-nodes-base.postgres",
"typeVersion": 2.5,
"position": [
250,
0
],
"credentials": {
"postgres": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"batchSize": 1,
"options": {}
},
"id": "loop_tenants",
"name": "Loop Over Tenants",
"type": "n8n-nodes-base.splitInBatches",
"typeVersion": 3,
"position": [
500,
0
]
}
],
"connections": {
"Every 30 Minutes": {
"main": [
[
{
"node": "Fetch Active Tenants",
"type": "main",
"index": 0
}
]
]
},
"Find Interviews Needing Prep": {
"main": [
[
{
"node": "Has Interviews?",
"type": "main",
"index": 0
}
]
]
},
"Has Interviews?": {
"main": [
[
{
"node": "Get Company Research",
"type": "main",
"index": 0
},
{
"node": "Get Salary Research",
"type": "main",
"index": 0
}
],
[]
]
},
"Get Company Research": {
"main": [
[
{
"node": "Assemble Prompt",
"type": "main",
"index": 0
}
]
]
},
"Get Salary Research": {
"main": [
[
{
"node": "Loop Over Tenants",
"type": "main",
"index": 0
}
]
]
},
"Assemble Prompt": {
"main": [
[
{
"node": "Claude Sonnet: Generate Brief",
"type": "main",
"index": 0
}
]
]
},
"Claude Sonnet: Generate Brief": {
"main": [
[
{
"node": "Parse Brief Sections",
"type": "main",
"index": 0
}
]
]
},
"Parse Brief Sections": {
"main": [
[
{
"node": "Brief Generated?",
"type": "main",
"index": 0
}
]
]
},
"Brief Generated?": {
"main": [
[
{
"node": "Save Brief to DB",
"type": "main",
"index": 0
}
],
[
{
"node": "Mark Prep Failed",
"type": "main",
"index": 0
}
]
]
},
"Save Brief to DB": {
"main": [
[
{
"node": "Email Brief to Candidate",
"type": "main",
"index": 0
}
]
]
},
"Email Brief to Candidate": {
"main": [
[
{
"node": "Update Interview Status",
"type": "main",
"index": 0
},
{
"node": "Mark Brief Delivered",
"type": "main",
"index": 0
}
]
]
},
"Mark Prep Failed": {
"main": [
[
{
"node": "Email Failure Notice",
"type": "main",
"index": 0
}
]
]
},
"Fetch Active Tenants": {
"main": [
[
{
"node": "Loop Over Tenants",
"type": "main",
"index": 0
}
]
]
},
"Loop Over Tenants": {
"main": [
[],
[
{
"node": "Find Interviews Needing Prep",
"type": "main",
"index": 0
}
]
]
},
"Update Interview Status": {
"main": [
[
{
"node": "Loop Over Tenants",
"type": "main",
"index": 0
}
]
]
},
"Mark Brief Delivered": {
"main": [
[
{
"node": "Loop Over Tenants",
"type": "main",
"index": 0
}
]
]
},
"Email Failure Notice": {
"main": [
[
{
"node": "Loop Over Tenants",
"type": "main",
"index": 0
}
]
]
}
},
"settings": {
"executionOrder": "v1",
"callerPolicy": "workflowsFromSameOwner",
"availableInMCP": true
},
"staticData": {
"node:Every 30 Minutes": {
"recurrenceRules": []
}
},
"meta": null,
"versionId": "337ef900-8216-4420-8ab3-0060298770a5",
"activeVersionId": "337ef900-8216-4420-8ab3-0060298770a5",
"versionCounter": 7,
"triggerCount": 1,
"shared": [
{
"updatedAt": "2026-04-02T17:11:49.013Z",
"createdAt": "2026-04-02T17:11:49.013Z",
"role": "workflow:owner",
"workflowId": "c22XxluRJOWGj4RW",
"projectId": "IrY2W58JPTTW41XY",
"project": {
"updatedAt": "2026-03-29T09:57:50.698Z",
"createdAt": "2026-03-29T09:50:40.962Z",
"id": "IrY2W58JPTTW41XY",
"name": "Venkatesan Ramachandran <venkat.fts@gmail.com>",
"type": "personal",
"icon": null,
"description": null,
"creatorId": "509e77ae-43b3-42df-bd9d-6e2a7aa26079"
}
}
],
"tags": [],
"activeVersion": {
"updatedAt": "2026-04-02T17:11:49.023Z",
"createdAt": "2026-04-02T17:11:49.023Z",
"versionId": "337ef900-8216-4420-8ab3-0060298770a5",
"workflowId": "c22XxluRJOWGj4RW",
"nodes": [
{
"parameters": {
"rule": {
"interval": [
{
"field": "minutes",
"minutesInterval": 30
}
]
}
},
"id": "schedule-trigger",
"name": "Every 30 Minutes",
"type": "n8n-nodes-base.scheduleTrigger",
"typeVersion": 1.2,
"position": [
0,
0
]
},
{
"parameters": {
"operation": "executeQuery",
"query": "SELECT i.id AS interview_id, i.company_name, i.role_title, i.interview_track, i.interview_format, i.interview_stage, i.interview_date, i.interview_start_time, i.interview_end_time, i.interview_duration_minutes, i.location_type, i.physical_address, i.video_platform, i.video_link, i.interviewer_names, i.interviewer_titles, i.what_to_prepare, i.what_to_bring, i.dress_code, i.additional_instructions, i.application_id, i.detection_confidence FROM interviews i WHERE i.status IN ('calendared', 'parsed', 'pending_confirmation') AND i.interview_date >= CURRENT_DATE AND i.prep_failed = false AND NOT EXISTS (SELECT 1 FROM prep_briefs pb WHERE pb.interview_id = i.id) ORDER BY i.interview_date ASC, i.interview_start_time ASC LIMIT 5;",
"options": {}
},
"id": "find-interviews",
"name": "Find Interviews Needing Prep",
"type": "n8n-nodes-base.postgres",
"typeVersion": 2.5,
"position": [
220,
0
],
"credentials": {
"postgres": {
"id": "uAbCv6KI1KdUiMtX",
"name": "Selvi Jobs DB"
}
}
},
{
"parameters": {
"conditions": {
"options": {
"caseSensitive": true,
"leftValue": "",
"typeValidation": "strict"
},
"conditions": [
{
"id": "has-results",
"leftValue": "={{ $json.interview_id }}",
"rightValue": "",
"operator": {
"type": "string",
"operation": "isNotEmpty"
}
}
],
"combinator": "and"
},
"options": {}
},
"id": "check-results",
"name": "Has Interviews?",
"type": "n8n-nodes-base.if",
"typeVersion": 2.2,
"position": [
440,
0
]
},
{
"parameters": {
"operation": "executeQuery",
"query": "SELECT cr.research_data, cr.research_completeness, cr.researched_at FROM company_research cr WHERE cr.company_name_normalised = LOWER(REGEXP_REPLACE('{{ $json.company_name }}', '\\s+(Ltd|PLC|LLP|Limited|Inc)\\.?$', '', 'i')) AND cr.expires_at > NOW() LIMIT 1;",
"options": {}
},
"id": "get-company-research",
"name": "Get Company Research",
"type": "n8n-nodes-base.postgres",
"typeVersion": 2.5,
"position": [
660,
0
],
"credentials": {
"postgres": {
"id": "uAbCv6KI1KdUiMtX",
"name": "Selvi Jobs DB"
}
}
},
{
"parameters": {
"operation": "executeQuery",
"query": "SELECT sr.salary_min, sr.salary_max, sr.salary_median, sr.salary_currency, sr.academic_grade, sr.spine_point_min, sr.spine_point_max, sr.typical_bonus_percentage, sr.typical_pension_percentage, sr.benefits_notes FROM salary_research sr WHERE sr.role_title_normalised = LOWER('{{ $json.role_title }}') AND sr.expires_at > NOW() ORDER BY sr.researched_at DESC LIMIT 1;",
"options": {}
},
"id": "get-salary-research",
"name": "Get Salary Research",
"type": "n8n-nodes-base.postgres",
"typeVersion": 2.5,
"position": [
660,
220
],
"credentials": {
"postgres": {
"id": "uAbCv6KI1KdUiMtX",
"name": "Selvi Jobs DB"
}
}
},
{
"parameters": {
"jsCode": "// Assemble the prompt context for Claude Sonnet\nconst interview = $('Has Interviews?').first().json;\nconst companyData = $('Get Company Research').first().json;\nconst salaryData = $('Get Salary Research').first().json;\n\nconst companyResearch = companyData.research_data \n ? `COMPANY RESEARCH:\\n${JSON.stringify(companyData.research_data, null, 2)}\\nResearch completeness: ${companyData.research_completeness || 'none'}`\n : 'COMPANY RESEARCH: No cached research available. Use publicly known information about this company.';\n\nconst salaryInfo = salaryData.salary_min\n ? `SALARY INTELLIGENCE:\\n- Range: ${salaryData.salary_currency || 'GBP'} ${salaryData.salary_min} - ${salaryData.salary_max}\\n- Median: ${salaryData.salary_currency || 'GBP'} ${salaryData.salary_median}\\n- Typical bonus: ${salaryData.typical_bonus_percentage || 'N/A'}%\\n- Typical pension: ${salaryData.typical_pension_percentage || 'N/A'}%\\n- Benefits notes: ${salaryData.benefits_notes || 'N/A'}`\n : 'SALARY INTELLIGENCE: No cached salary data. Provide general UK market guidance for this role level.';\n\nconst interviewerInfo = interview.interviewer_names && interview.interviewer_names.length > 0\n ? `INTERVIEWERS: ${interview.interviewer_names.join(', ')}${interview.interviewer_titles ? ' (' + interview.interviewer_titles.join(', ') + ')' : ''}`\n : 'INTERVIEWERS: Not specified';\n\nconst prompt = `Generate a comprehensive interview preparation brief for the following interview.\n\nCANDIDATE PROFILE:\n- PhD + MBA professional with 18 years of HR/L&D experience\n- Currently targeting UK L&D Manager to Head of L&D roles (corporate) and Lecturer/Senior Lecturer positions (academic)\n- Target salary: GBP 70,000-80,000 (corporate) or appropriate academic grade\n- Location: Maidenhead, UK\n- Key strengths: stakeholder management, programme design & delivery, ROI measurement, change management, digital learning strategy\n- 90% callback-to-offer rate\n\nINTERVIEW DETAILS:\n- Company: ${interview.company_name}\n- Role: ${interview.role_title}\n- Track: ${interview.interview_track}\n- Format: ${interview.interview_format}\n- Stage: ${interview.interview_stage || 'Not specified'}\n- Date: ${interview.interview_date}\n- Time: ${interview.interview_start_time || 'TBC'} - ${interview.interview_end_time || 'TBC'}\n- Duration: ${interview.interview_duration_minutes || 60} minutes\n- Location type: ${interview.location_type || 'Not specified'}\n- Physical address: ${interview.physical_address || 'N/A'}\n- Video platform: ${interview.video_platform || 'N/A'}\n${interviewerInfo}\n- What to prepare: ${interview.what_to_prepare || 'Not specified'}\n- What to bring: ${interview.what_to_bring || 'Not specified'}\n- Dress code: ${interview.dress_code || 'Not specified'}\n- Additional instructions: ${interview.additional_instructions || 'None'}\n\n${companyResearch}\n\n${salaryInfo}\n\nPlease generate a structured preparation brief with these sections:\n\n1. **COMPANY OVERVIEW** - Key facts, culture, recent news, strategic direction\n2. **ROLE ANALYSIS** - Key requirements, likely priorities, challenges the hiring manager faces\n3. **YOUR FIT** - How the candidate's experience maps to role requirements, key selling points\n4. **LIKELY QUESTIONS** (${interview.interview_track === 'academic' ? 'academic format: teaching philosophy, research alignment, REF impact' : 'UK competency-based STAR format'}) - 8-10 questions with suggested STAR response angles\n5. **QUESTIONS TO ASK** - 5-7 intelligent questions that demonstrate understanding and genuine interest\n6. **SALARY & NEGOTIATION INTELLIGENCE** - Market rates, negotiation leverage points, benefits to discuss\n7. **LOGISTICS & FORMAT TIPS** - Format-specific advice, technology checks, timing\n8. **FINAL CHECKLIST** - Day-before and day-of checklist items\n\nBe specific to this company and role. Avoid generic advice. Reference UK employment practices and norms.`;\n\nreturn {\n interview_id: interview.interview_id,\n company_name: interview.company_name,\n role_title: interview.role_title,\n interview_date: interview.interview_date,\n interview_track: interview.interview_track,\n prompt: prompt\n};"
},
"id": "assemble-prompt",
"name": "Assemble Prompt",
"type": "n8n-nodes-base.code",
"typeVersion": 2,
"position": [
880,
0
]
},
{
"parameters": {
"method": "POST",
"url": "https://api.anthropic.com/v1/messages",
"sendHeaders": true,
"headerParameters": {
"parameters": [
{
"name": "x-api-key",
"value": "={{ $credentials.anthropicApi.apiKey }}"
},
{
"name": "anthropic-version",
"value": "2023-06-01"
},
{
"name": "content-type",
"value": "application/json"
}
]
},
"sendBody": true,
"specifyBody": "json",
"jsonBody": "={\n \"model\": \"claude-sonnet-4-20250514\",\n \"max_tokens\": 8000,\n \"temperature\": 0.3,\n \"system\": \"You are an expert career coach and interview preparation specialist with deep knowledge of UK corporate L&D and UK higher education hiring practices. Generate thorough, specific, actionable preparation briefs.\",\n \"messages\": [\n {\n \"role\": \"user\",\n \"content\": {{ JSON.stringify($json.prompt) }}\n }\n ]\n}",
"options": {
"timeout": 120000
}
},
"id": "claude-sonnet",
"name": "Claude Sonnet: Generate Brief",
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 4.2,
"position": [
1100,
0
],
"credentials": {
"httpCustomAuth": {
"id": "niaedqDRwvoilXyi",
"name": "Anthropic API"
}
},
"onError": "continueRegularOutput"
},
{
"parameters": {
"jsCode": "const input = $('Assemble Prompt').first().json;\nconst response = $('Claude Sonnet: Generate Brief').first().json;\n\n// Check for API error\nif (response.error || !response.content || !response.content[0]) {\n return {\n interview_id: input.interview_id,\n company_name: input.company_name,\n role_title: input.role_title,\n success: false,\n error: response.error?.message || 'No content in Claude response'\n };\n}\n\nconst briefText = response.content[0].text;\nconst usage = response.usage || {};\n\n// Extract sections using regex\nconst sections = {};\nconst sectionPatterns = [\n { key: 'company_overview', pattern: /\\*\\*(?:1\\.\\s*)?COMPANY OVERVIEW\\*\\*([\\s\\S]*?)(?=\\n\\*\\*(?:2\\.|ROLE)|$)/i },\n { key: 'role_analysis', pattern: /\\*\\*(?:2\\.\\s*)?ROLE ANALYSIS\\*\\*([\\s\\S]*?)(?=\\n\\*\\*(?:3\\.|YOUR)|$)/i },\n { key: 'candidate_fit', pattern: /\\*\\*(?:3\\.\\s*)?YOUR FIT\\*\\*([\\s\\S]*?)(?=\\n\\*\\*(?:4\\.|LIKELY)|$)/i },\n { key: 'likely_questions', pattern: /\\*\\*(?:4\\.\\s*)?LIKELY QUESTIONS\\*\\*([\\s\\S]*?)(?=\\n\\*\\*(?:5\\.|QUESTIONS TO)|$)/i },\n { key: 'questions_to_ask', pattern: /\\*\\*(?:5\\.\\s*)?QUESTIONS TO ASK\\*\\*([\\s\\S]*?)(?=\\n\\*\\*(?:6\\.|SALARY)|$)/i },\n { key: 'salary_intelligence', pattern: /\\*\\*(?:6\\.\\s*)?SALARY.*?INTELLIGENCE\\*\\*([\\s\\S]*?)(?=\\n\\*\\*(?:7\\.|LOGISTICS)|$)/i },\n { key: 'logistics_and_format', pattern: /\\*\\*(?:7\\.\\s*)?LOGISTICS.*?\\*\\*([\\s\\S]*?)(?=\\n\\*\\*(?:8\\.|FINAL)|$)/i },\n { key: 'final_checklist', pattern: /\\*\\*(?:8\\.\\s*)?FINAL CHECKLIST\\*\\*([\\s\\S]*?)$/i }\n];\n\nfor (const sp of sectionPatterns) {\n const match = briefText.match(sp.pattern);\n sections[sp.key] = match ? match[1].trim() : null;\n}\n\n// Calculate cost (Sonnet pricing: $3/MTok input, $15/MTok output)\nconst inputTokens = usage.input_tokens || 0;\nconst outputTokens = usage.output_tokens || 0;\nconst costUsd = (inputTokens * 3 / 1000000) + (outputTokens * 15 / 1000000);\n\nreturn {\n interview_id: input.interview_id,\n company_name: input.company_name,\n role_title: input.role_title,\n interview_date: input.interview_date,\n interview_track: input.interview_track,\n full_brief_text: briefText,\n sections: sections,\n model_used: 'claude-sonnet-4-20250514',\n prompt_tokens: inputTokens,\n completion_tokens: outputTokens,\n generation_cost_usd: costUsd,\n success: true\n};"
},
"id": "parse-brief",
"name": "Parse Brief Sections",
"type": "n8n-nodes-base.code",
"typeVersion": 2,
"position": [
1320,
0
]
},
{
"parameters": {
"conditions": {
"options": {
"caseSensitive": true,
"leftValue": "",
"typeValidation": "strict"
},
"conditions": [
{
"id": "check-success",
"leftValue": "={{ $json.success }}",
"rightValue": true,
"operator": {
"type": "boolean",
"operation": "true"
}
}
],
"combinator": "and"
},
"options": {}
},
"id": "check-success",
"name": "Brief Generated?",
"type": "n8n-nodes-base.if",
"typeVersion": 2.2,
"position": [
1540,
0
]
},
{
"parameters": {
"operation": "executeQuery",
"query": "INSERT INTO prep_briefs (interview_id, company_overview, role_analysis, candidate_fit, likely_questions, questions_to_ask, salary_intelligence, logistics_and_format, final_checklist, full_brief_text, brief_format, model_used, prompt_tokens, completion_tokens, generation_cost_usd, generation_attempts) VALUES ('{{ $json.interview_id }}', {{ $json.sections.company_overview ? \"'\" + $json.sections.company_overview.replace(/'/g, \"''\") + \"'\" : 'NULL' }}, {{ $json.sections.role_analysis ? \"'\" + $json.sections.role_analysis.replace(/'/g, \"''\") + \"'\" : 'NULL' }}, {{ $json.sections.candidate_fit ? \"'\" + $json.sections.candidate_fit.replace(/'/g, \"''\") + \"'\" : 'NULL' }}, {{ $json.sections.likely_questions ? \"'\" + JSON.stringify($json.sections.likely_questions).replace(/'/g, \"''\") + \"'::jsonb\" : 'NULL' }}, {{ $json.sections.questions_to_ask ? \"'\" + JSON.stringify($json.sections.questions_to_ask).replace(/'/g, \"''\") + \"'::jsonb\" : 'NULL' }}, {{ $json.sections.salary_intelligence ? \"'\" + $json.sections.salary_intelligence.replace(/'/g, \"''\") + \"'\" : 'NULL' }}, {{ $json.sections.logistics_and_format ? \"'\" + $json.sections.logistics_and_format.replace(/'/g, \"''\") + \"'\" : 'NULL' }}, {{ $json.sections.final_checklist ? \"'\" + $json.sections.final_checklist.replace(/'/g, \"''\") + \"'\" : 'NULL' }}, '{{ $json.full_brief_text.replace(/'/g, \"''\") }}', 'markdown', '{{ $json.model_used }}', {{ $json.prompt_tokens }}, {{ $json.completion_tokens }}, {{ $json.generation_cost_usd }}, 1) RETURNING id;",
"options": {}
},
"id": "save-brief",
"name": "Save Brief to DB",
"type": "n8n-nodes-base.postgres",
"typeVersion": 2.5,
"position": [
1760,
-100
],
"credentials": {
"postgres": {
"id": "uAbCv6KI1KdUiMtX",
"name": "Selvi Jobs DB"
}
}
},
{
"parameters": {
"method": "POST",
"url": "https://api.resend.com/emails",
"sendHeaders": true,
"headerParameters": {
"parameters": [
{
"name": "Authorization",
"value": "Bearer re_PMdG3JAg_Er4o7VYY74tek5WzMqmqBJ15"
},
{
"name": "Content-type",
"value": "application/json"
}
]
},
"sendBody": true,
"specifyBody": "json",
"jsonBody": "={\n \"from\": \"Selvi Job App <jobs@apiloom.io>\",\n \"to\": [\"chellamma.uk@gmail.com\"],\n \"subject\": \"Prep Ready: {{ $('Parse Brief Sections').first().json.company_name }} - {{ $('Parse Brief Sections').first().json.role_title }} ({{ $('Parse Brief Sections').first().json.interview_date }})\",\n \"html\": \"<h2>Interview Preparation Brief</h2><h3>{{ $('Parse Brief Sections').first().json.company_name }} — {{ $('Parse Brief Sections').first().json.role_title }}</h3><p><strong>Date:</strong> {{ $('Parse Brief Sections').first().json.interview_date }} | <strong>Track:</strong> {{ $('Parse Brief Sections').first().json.interview_track }}</p><hr>\" + {{ JSON.stringify($('Parse Brief Sections').first().json.full_brief_text.replace(/\\n/g, '<br>')) }} + \"<hr><p><em>Selvi Job App — Module 6: Interview Preparation</em></p>\"\n}",
"options": {
"timeout": 30000
}
},
"id": "email-brief",
"name": "Email Brief to Candidate",
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 4.2,
"position": [
1980,
-100
]
},
{
"parameters": {
"operation": "executeQuery",
"query": "UPDATE interviews SET status = 'prep_ready', updated_at = NOW() WHERE id = '{{ $('Parse Brief Sections').first().json.interview_id }}' AND status NOT IN ('completed', 'cancelled_by_employer', 'cancelled_by_candidate');",
"options": {}
},
"id": "update-status-ready",
"name": "Update Interview Status",
"type": "n8n-nodes-base.postgres",
"typeVersion": 2.5,
"position": [
2200,
-100
],
"credentials": {
"postgres": {
"id": "uAbCv6KI1KdUiMtX",
"name": "Selvi Jobs DB"
}
}
},
{
"parameters": {
"operation": "executeQuery",
"query": "UPDATE prep_briefs SET delivered_at = NOW() WHERE interview_id = '{{ $('Parse Brief Sections').first().json.interview_id }}' AND delivered_at IS NULL;",
"options": {}
},
"id": "mark-delivered",
"name": "Mark Brief Delivered",
"type": "n8n-nodes-base.postgres",
"typeVersion": 2.5,
"position": [
2200,
100
],
"credentials": {
"postgres": {
"id": "uAbCv6KI1KdUiMtX",
"name": "Selvi Jobs DB"
}
}
},
{
"parameters": {
"operation": "executeQuery",
"query": "UPDATE interviews SET prep_failed = true, prep_failed_at = NOW(), prep_failed_reason = '{{ $json.error ? $json.error.substring(0, 500).replace(/'/g, \"''\") : \"Unknown error\" }}' WHERE id = '{{ $json.interview_id }}';",
"options": {}
},
"id": "mark-prep-failed",
"name": "Mark Prep Failed",
"type": "n8n-nodes-base.postgres",
"typeVersion": 2.5,
"position": [
1760,
200
],
"credentials": {
"postgres": {
"id": "uAbCv6KI1KdUiMtX",
"name": "Selvi Jobs DB"
}
}
},
{
"parameters": {
"method": "POST",
"url": "https://api.resend.com/emails",
"sendHeaders": true,
"headerParameters": {
"parameters": [
{
"name": "Authorization",
"value": "Bearer re_PMdG3JAg_Er4o7VYY74tek5WzMqmqBJ15"
},
{
"name": "Content-type",
"value": "application/json"
}
]
},
"sendBody": true,
"specifyBody": "json",
"jsonBody": "={\n \"from\": \"Selvi Job App <jobs@apiloom.io>\",\n \"to\": [\"chellamma.uk@gmail.com\"],\n \"subject\": \"Prep Brief Failed: {{ $json.company_name }} - {{ $json.role_title }}\",\n \"html\": \"<h3>Prep Brief Generation Failed</h3><p>The interview preparation brief for <strong>{{ $json.company_name }} - {{ $json.role_title }}</strong> could not be generated.</p><p><strong>Error:</strong> {{ $json.error || 'Unknown error' }}</p><p>Manual preparation recommended.</p><hr><p><em>Selvi Job App — Module 6</em></p>\"\n}",
"options": {}
},
"id": "email-failure",
"name": "Email Failure Notice",
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 4.2,
"position": [
1980,
200
]
}
],
"connections": {
"Every 30 Minutes": {
"main": [
[
{
"node": "Find Interviews Needing Prep",
"type": "main",
"index": 0
}
]
]
},
"Find Interviews Needing Prep": {
"main": [
[
{
"node": "Has Interviews?",
"type": "main",
"index": 0
}
]
]
},
"Has Interviews?": {
"main": [
[
{
"node": "Get Company Research",
"type": "main",
"index": 0
},
{
"node": "Get Salary Research",
"type": "main",
"index": 0
}
],
[]
]
},
"Get Company Research": {
"main": [
[
{
"node": "Assemble Prompt",
"type": "main",
"index": 0
}
]
]
},
"Get Salary Research": {
"main": []
},
"Assemble Prompt": {
"main": [
[
{
"node": "Claude Sonnet: Generate Brief",
"type": "main",
"index": 0
}
]
]
},
"Claude Sonnet: Generate Brief": {
"main": [
[
{
"node": "Parse Brief Sections",
"type": "main",
"index": 0
}
]
]
},
"Parse Brief Sections": {
"main": [
[
{
"node": "Brief Generated?",
"type": "main",
"index": 0
}
]
]
},
"Brief Generated?": {
"main": [
[
{
"node": "Save Brief to DB",
"type": "main",
"index": 0
}
],
[
{
"node": "Mark Prep Failed",
"type": "main",
"index": 0
}
]
]
},
"Save Brief to DB": {
"main": [
[
{
"node": "Email Brief to Candidate",
"type": "main",
"index": 0
}
]
]
},
"Email Brief to Candidate": {
"main": [
[
{
"node": "Update Interview Status",
"type": "main",
"index": 0
},
{
"node": "Mark Brief Delivered",
"type": "main",
"index": 0
}
]
]
},
"Mark Prep Failed": {
"main": [
[
{
"node": "Email Failure Notice",
"type": "main",
"index": 0
}
]
]
}
},
"authors": "Venkatesan Ramachandran",
"name": null,
"description": null,
"autosaved": false,
"workflowPublishHistory": [
{
"createdAt": "2026-04-02T17:14:24.875Z",
"id": 26,
"workflowId": "c22XxluRJOWGj4RW",
"versionId": "337ef900-8216-4420-8ab3-0060298770a5",
"event": "activated",
"userId": "509e77ae-43b3-42df-bd9d-6e2a7aa26079"
},
{
"createdAt": "2026-04-04T14:22:24.414Z",
"id": 84,
"workflowId": "c22XxluRJOWGj4RW",
"versionId": "337ef900-8216-4420-8ab3-0060298770a5",
"event": "deactivated",
"userId": "509e77ae-43b3-42df-bd9d-6e2a7aa26079"
},
{
"createdAt": "2026-04-04T14:22:24.439Z",
"id": 85,
"workflowId": "c22XxluRJOWGj4RW",
"versionId": "337ef900-8216-4420-8ab3-0060298770a5",
"event": "activated",
"userId": "509e77ae-43b3-42df-bd9d-6e2a7aa26079"
}
]
}
}
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.
httpCustomAuthpostgres
Pro
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About this workflow
WF6-PREP: Interview Prep Brief Generator. Uses postgres, httpRequest. Scheduled trigger; 17 nodes.
Source: https://github.com/cto-venkat/selvi-job-app/blob/499ca24d9c9382b5f5561a096360564965fb4b8e/workflows/wf6-prep-mt.json — original creator credit. Request a take-down →
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