This workflow follows the Airtable → HTTP Request 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 →
{
"name": "JobSignal - Workflow 3 - Tailor",
"nodes": [
{
"parameters": {},
"id": "3e7f816c-8bcd-40d7-910f-7b9ed609b5db",
"name": "Manual Trigger",
"type": "n8n-nodes-base.manualTrigger",
"typeVersion": 1,
"position": [
2544,
64
]
},
{
"parameters": {
"rule": {
"interval": [
{
"triggerAtHour": 9,
"triggerAtMinute": 30
}
]
}
},
"id": "4bc2f1ad-49af-44cf-9efe-a9d38db43d1d",
"name": "Schedule Trigger",
"type": "n8n-nodes-base.scheduleTrigger",
"typeVersion": 1.2,
"position": [
2544,
272
]
},
{
"parameters": {
"operation": "search",
"base": {
"__rl": true,
"value": "appE808oZ5gTSQzUY",
"mode": "list",
"cachedResultName": "Job Signal Engine",
"cachedResultUrl": "https://airtable.com/appE808oZ5gTSQzUY"
},
"table": {
"__rl": true,
"value": "tblqvCvqMIczRGjLi",
"mode": "list",
"cachedResultName": "Pipeline",
"cachedResultUrl": "https://airtable.com/appE808oZ5gTSQzUY/tblqvCvqMIczRGjLi"
},
"filterByFormula": "==AND({Status}='Evaluated',{Fit Tier}='High',{Tailored CV Text}='')",
"options": {}
},
"id": "5c001130-b04f-4a3a-a95c-fe386bee3145",
"name": "Get High Fit Jobs",
"type": "n8n-nodes-base.airtable",
"typeVersion": 2.1,
"position": [
2784,
64
],
"credentials": {
"airtableTokenApi": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"operation": "search",
"base": {
"__rl": true,
"value": "appE808oZ5gTSQzUY",
"mode": "list",
"cachedResultName": "Job Signal Engine",
"cachedResultUrl": "https://airtable.com/appE808oZ5gTSQzUY"
},
"table": {
"__rl": true,
"value": "tbl4hqn6sfFVbLuzd",
"mode": "list",
"cachedResultName": "Profile",
"cachedResultUrl": "https://airtable.com/appE808oZ5gTSQzUY/tbl4hqn6sfFVbLuzd"
},
"options": {}
},
"id": "4c8867b6-5026-4e37-9f47-e0531021e8df",
"name": "Get Profile",
"type": "n8n-nodes-base.airtable",
"typeVersion": 2.1,
"position": [
3024,
64
],
"executeOnce": true,
"credentials": {
"airtableTokenApi": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"jsCode": "// Build the CV tailoring prompt from Profile data and job details\n\nconst profile = $('Get Profile').first().json;\nconst jobs = $('Get High Fit Jobs').all();\n\n// Get CV markdown from Profile \u2014 handle both flat and nested field shapes\nconst cvMarkdown = profile.fields \n ? (profile.fields['CV Markdown'] || profile.fields['Professional Summary'] || '')\n : (profile['CV Markdown'] || profile['Professional Summary'] || '');\n\nif (!cvMarkdown) {\n throw new Error('CV Markdown is empty in Profile table. Please add your CV markdown to the Profile.');\n}\n\nconst systemPrompt = `You are an expert CV writer specializing in ATS-optimized resumes for technical professionals.\n\nRULES:\n- Keep ALL factual information accurate \u2014 do NOT invent experience, companies, dates, or metrics\n- Rewrite the Professional Summary (first paragraph after contact info) to mirror the JD's language and priorities\n- Reorder and re-emphasize bullet points to highlight matched skills\n- De-emphasize (don't remove) experience unrelated to this role\n- Incorporate the tailoring notes provided\n- Keep the EXACT SAME markdown structure as the original CV:\n - First line: Full name in caps\n - Second line: Contact info separated by pipes\n - Third paragraph: Professional summary\n - ALL-CAPS section headers (TECHNICAL SKILLS, etc.)\n - Skills in \"Category: items\" format\n - Bullet points with \u2022 character\n - Job titles with | separators for company/location/dates\n - Project names as standalone bold descriptive lines\n- Output clean text. No markdown formatting (no **, no ##, no ---). No commentary, no preamble.\n- The output must be a single-page CV. Do not add content that would push it beyond one page.\nCRITICAL: Do NOT use <thought> tags or any thinking/reasoning before your response. Start your response directly with the tailored CV content. No preamble, no explanation.`;\n\nreturn jobs.map(job => {\n const fields = job.json.fields || job.json;\n const recordId = job.json.id || job.json.recordId;\n \n return {\n json: {\n _systemPrompt: systemPrompt,\n _cvMarkdown: cvMarkdown,\n _jobDescription: fields['Job Description'] || '',\n _matchedSkills: fields['Matched Skills'] || '',\n _cvTailoringNotes: fields['CV Tailoring Notes'] || '',\n _jobTitle: fields['Job Title'] || '',\n _company: fields['Company'] || '',\n _recordId: recordId\n }\n };\n});"
},
"id": "cacc327d-2f6c-4e9c-8197-2f3302087f00",
"name": "Build Tailoring Prompt",
"type": "n8n-nodes-base.code",
"typeVersion": 2,
"position": [
3264,
64
]
},
{
"parameters": {
"options": {}
},
"id": "5b369f58-6cd5-4953-9759-473ae069f2bc",
"name": "Loop Over Jobs",
"type": "n8n-nodes-base.splitInBatches",
"typeVersion": 3,
"position": [
3488,
64
]
},
{
"parameters": {
"modelId": {
"__rl": true,
"value": "gpt-5-mini",
"mode": "list",
"cachedResultName": "GPT-5-MINI"
},
"messages": {
"values": [
{
"content": "={{ $json._systemPrompt }}",
"role": "system"
},
{
"content": "=Tailor this CV for the target job.\n\nMATCHED SKILLS: {{ $json._matchedSkills }}\n\nTAILORING NOTES: {{ $json._cvTailoringNotes }}\n\nTARGET JOB: {{ $json._jobTitle }} at {{ $json._company }}\n\nJOB DESCRIPTION:\n{{ $json._jobDescription }}\n\nCANDIDATE CV TO TAILOR:\n{{ $json._cvMarkdown }}"
}
]
},
"simplify": false,
"options": {}
},
"id": "d5d0565d-bee1-4065-b334-e9376435d291",
"name": "Tailor CV (GPT-5 mini)",
"type": "@n8n/n8n-nodes-langchain.openAi",
"typeVersion": 1.6,
"position": [
3696,
64
],
"retryOnFail": true,
"maxTries": 3,
"waitBetweenTries": 5000,
"credentials": {
"openAiApi": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"jsCode": "// Parse the tailored CV from AI response and prepare for rendering + Airtable update\nconst aiResponse = $input.first().json;\n\n// Extract content \u2014 handle both simplified and full response shapes\nlet tailoredCV;\nif (aiResponse.choices && aiResponse.choices[0] && aiResponse.choices[0].message) {\n tailoredCV = aiResponse.choices[0].message.content;\n} else if (aiResponse.message && aiResponse.message.content) {\n tailoredCV = aiResponse.message.content;\n} else if (aiResponse.content) {\n tailoredCV = aiResponse.content;\n} else if (aiResponse.text) {\n tailoredCV = aiResponse.text;\n} else {\n tailoredCV = typeof aiResponse === 'string' ? aiResponse : JSON.stringify(aiResponse);\n}\n\n// Strip <thought> tags and everything inside them\nif (typeof tailoredCV === 'string' && tailoredCV.includes('<thought>')) {\n const thoughtEnd = tailoredCV.indexOf('</thought>');\n if (thoughtEnd !== -1) {\n tailoredCV = tailoredCV.substring(thoughtEnd + '</thought>'.length).trim();\n } else {\n // No closing tag \u2014 find first line that looks like CV content\n const lines = tailoredCV.split('\\n');\n const cvStart = lines.findIndex(l => l.trim().length > 0 && !l.trim().startsWith('<thought>') && !l.includes('* '));\n if (cvStart !== -1) {\n tailoredCV = lines.slice(cvStart).join('\\n').trim();\n }\n }\n}\n\nif (!tailoredCV || tailoredCV.length < 100) {\n throw new Error('Tailored CV response too short or empty: ' + (tailoredCV || '').slice(0, 200));\n}\n\n// Calculate cost from actual token usage\nconst INPUT_COST_PER_TOKEN = 0.25 / 1_000_000;\nconst OUTPUT_COST_PER_TOKEN = 2.00 / 1_000_000;\nlet cost = 0;\nconst usage = aiResponse.usage \n || (aiResponse.message && aiResponse.message.usage)\n || null;\nif (usage && usage.prompt_tokens && usage.completion_tokens) {\n cost = (usage.prompt_tokens * INPUT_COST_PER_TOKEN) \n + (usage.completion_tokens * OUTPUT_COST_PER_TOKEN);\n cost = Math.round(cost * 1_000_000) / 1_000_000;\n}\n\n// Get job context from the loop\nconst loopItem = $('Loop Over Jobs').item.json;\nconst safeCompany = loopItem._company.replace(/[^a-zA-Z0-9]/g, '_').toLowerCase();\nconst filename = `cv_${safeCompany}_${Date.now()}`;\n\nreturn [{\n json: {\n recordId: loopItem._recordId,\n tailoredCV: tailoredCV,\n company: loopItem._company,\n jobTitle: loopItem._jobTitle,\n cost: cost,\n filename: filename\n }\n}];"
},
"id": "2e5aa5d5-48f4-43b4-9f99-d22d07dbe01d",
"name": "Parse Tailored CV",
"type": "n8n-nodes-base.code",
"typeVersion": 2,
"position": [
4064,
64
]
},
{
"parameters": {
"method": "POST",
"url": "http://cv-renderer:3456/render",
"sendBody": true,
"specifyBody": "json",
"jsonBody": "={{ JSON.stringify({ markdown: $json.tailoredCV, filename: $json.filename }) }}",
"options": {
"timeout": 30000
}
},
"id": "80e3498c-9bc3-4d9b-bdbd-323a7b534889",
"name": "Render DOCX",
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 4.2,
"position": [
4320,
64
],
"retryOnFail": true,
"maxTries": 2,
"waitBetweenTries": 5000
},
{
"parameters": {
"operation": "update",
"base": {
"__rl": true,
"value": "appE808oZ5gTSQzUY",
"mode": "id"
},
"table": {
"__rl": true,
"value": "tblqvCvqMIczRGjLi",
"mode": "list",
"cachedResultName": "Pipeline",
"cachedResultUrl": "https://airtable.com/appE808oZ5gTSQzUY/tblqvCvqMIczRGjLi"
},
"columns": {
"mappingMode": "defineBelow",
"value": {
"id": "={{ $('Parse Tailored CV').item.json.recordId }}",
"Tailored CV Text": "={{ $('Parse Tailored CV').item.json.tailoredCV }}",
"CV Tailoring Cost": "={{ $('Parse Tailored CV').item.json.cost }}"
},
"matchingColumns": [
"id"
],
"schema": [
{
"id": "id",
"displayName": "id",
"required": false,
"defaultMatch": true,
"display": true,
"type": "string",
"readOnly": true,
"removed": false
},
{
"id": "Job ID",
"displayName": "Job ID",
"required": false,
"defaultMatch": false,
"canBeUsedToMatch": true,
"display": true,
"type": "string",
"readOnly": false,
"removed": true
},
{
"id": "Job Title",
"displayName": "Job Title",
"required": false,
"defaultMatch": false,
"canBeUsedToMatch": true,
"display": true,
"type": "string",
"readOnly": false,
"removed": true
},
{
"id": "Company",
"displayName": "Company",
"required": false,
"defaultMatch": false,
"canBeUsedToMatch": true,
"display": true,
"type": "string",
"readOnly": false,
"removed": true
},
{
"id": "Location",
"displayName": "Location",
"required": false,
"defaultMatch": false,
"canBeUsedToMatch": true,
"display": true,
"type": "string",
"readOnly": false,
"removed": true
},
{
"id": "Apply Link",
"displayName": "Apply Link",
"required": false,
"defaultMatch": false,
"canBeUsedToMatch": true,
"display": true,
"type": "string",
"readOnly": false,
"removed": true
},
{
"id": "Job Description",
"displayName": "Job Description",
"required": false,
"defaultMatch": false,
"canBeUsedToMatch": true,
"display": true,
"type": "string",
"readOnly": false,
"removed": true
},
{
"id": "Source",
"displayName": "Source",
"required": false,
"defaultMatch": false,
"canBeUsedToMatch": true,
"display": true,
"type": "options",
"options": [
{
"name": "LinkedIn",
"value": "LinkedIn"
},
{
"name": "Indeed",
"value": "Indeed"
},
{
"name": "Glassdoor",
"value": "Glassdoor"
},
{
"name": "Google Jobs",
"value": "Google Jobs"
},
{
"name": "ZipRecruiter",
"value": "ZipRecruiter"
},
{
"name": "Greenhouse",
"value": "Greenhouse"
},
{
"name": "Ashby",
"value": "Ashby"
},
{
"name": "Lever",
"value": "Lever"
},
{
"name": "Manual",
"value": "Manual"
}
],
"readOnly": false,
"removed": true
},
{
"id": "Source Query",
"displayName": "Source Query",
"required": false,
"defaultMatch": false,
"canBeUsedToMatch": true,
"display": true,
"type": "string",
"readOnly": false,
"removed": true
},
{
"id": "Source Tag",
"displayName": "Source Tag",
"required": false,
"defaultMatch": false,
"canBeUsedToMatch": true,
"display": true,
"type": "string",
"readOnly": false,
"removed": true
},
{
"id": "Discovery Date",
"displayName": "Discovery Date",
"required": false,
"defaultMatch": false,
"canBeUsedToMatch": true,
"display": true,
"type": "dateTime",
"readOnly": false,
"removed": true
},
{
"id": "Status",
"displayName": "Status",
"required": false,
"defaultMatch": false,
"canBeUsedToMatch": true,
"display": true,
"type": "options",
"options": [
{
"name": "New",
"value": "New"
},
{
"name": "Evaluated",
"value": "Evaluated"
},
{
"name": "Shortlisted",
"value": "Shortlisted"
},
{
"name": "Applied",
"value": "Applied"
},
{
"name": "Interview",
"value": "Interview"
},
{
"name": "Offer",
"value": "Offer"
},
{
"name": "Rejected",
"value": "Rejected"
},
{
"name": "Archived",
"value": "Archived"
}
],
"readOnly": false,
"removed": true
},
{
"id": "Fit Score",
"displayName": "Fit Score",
"required": false,
"defaultMatch": false,
"canBeUsedToMatch": true,
"display": true,
"type": "number",
"readOnly": false,
"removed": true
},
{
"id": "Fit Tier",
"displayName": "Fit Tier",
"required": false,
"defaultMatch": false,
"canBeUsedToMatch": true,
"display": true,
"type": "options",
"options": [
{
"name": "High",
"value": "High"
},
{
"name": "Medium",
"value": "Medium"
},
{
"name": "Low",
"value": "Low"
}
],
"readOnly": false,
"removed": true
},
{
"id": "Match Reasoning",
"displayName": "Match Reasoning",
"required": false,
"defaultMatch": false,
"canBeUsedToMatch": true,
"display": true,
"type": "string",
"readOnly": false,
"removed": true
},
{
"id": "Matched Skills",
"displayName": "Matched Skills",
"required": false,
"defaultMatch": false,
"canBeUsedToMatch": true,
"display": true,
"type": "string",
"readOnly": false,
"removed": true
},
{
"id": "Missing Skills",
"displayName": "Missing Skills",
"required": false,
"defaultMatch": false,
"canBeUsedToMatch": true,
"display": true,
"type": "string",
"readOnly": false,
"removed": true
},
{
"id": "CV Tailoring Notes",
"displayName": "CV Tailoring Notes",
"required": false,
"defaultMatch": false,
"canBeUsedToMatch": true,
"display": true,
"type": "string",
"readOnly": false,
"removed": true
},
{
"id": "Salary Info",
"displayName": "Salary Info",
"required": false,
"defaultMatch": false,
"canBeUsedToMatch": true,
"display": true,
"type": "string",
"readOnly": false,
"removed": true
},
{
"id": "AI Evaluation Cost",
"displayName": "AI Evaluation Cost",
"required": false,
"defaultMatch": false,
"canBeUsedToMatch": true,
"display": true,
"type": "number",
"readOnly": false,
"removed": true
},
{
"id": "Applied Date",
"displayName": "Applied Date",
"required": false,
"defaultMatch": false,
"canBeUsedToMatch": true,
"display": true,
"type": "dateTime",
"readOnly": false,
"removed": true
},
{
"id": "Response Date",
"displayName": "Response Date",
"required": false,
"defaultMatch": false,
"canBeUsedToMatch": true,
"display": true,
"type": "dateTime",
"readOnly": false,
"removed": true
},
{
"id": "Outcome Notes",
"displayName": "Outcome Notes",
"required": false,
"defaultMatch": false,
"canBeUsedToMatch": true,
"display": true,
"type": "string",
"readOnly": false,
"removed": true
},
{
"id": "Tailored CV Text",
"displayName": "Tailored CV Text",
"required": false,
"defaultMatch": false,
"canBeUsedToMatch": true,
"display": true,
"type": "string",
"readOnly": false,
"removed": false
},
{
"id": "CV Tailoring Cost",
"displayName": "CV Tailoring Cost",
"required": false,
"defaultMatch": false,
"canBeUsedToMatch": true,
"display": true,
"type": "number",
"readOnly": false,
"removed": false
},
{
"id": "Tailored CV",
"displayName": "Tailored CV",
"required": false,
"defaultMatch": false,
"canBeUsedToMatch": true,
"display": true,
"type": "array",
"readOnly": false,
"removed": true
}
],
"attemptToConvertTypes": false,
"convertFieldsToString": false
},
"options": {
"typecast": true
}
},
"id": "c586b7a9-cc82-44cc-b960-8cbed788007d",
"name": "Update Pipeline Record",
"type": "n8n-nodes-base.airtable",
"typeVersion": 2.1,
"position": [
4832,
64
],
"credentials": {
"airtableTokenApi": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"amount": 2
},
"id": "09bcf944-1897-48f0-8c03-e67a8bc4d3c8",
"name": "Wait 2s",
"type": "n8n-nodes-base.wait",
"typeVersion": 1.1,
"position": [
5104,
64
]
},
{
"parameters": {
"method": "POST",
"url": "=https://content.airtable.com/v0/appE808oZ5gTSQzUY/{{ $('Parse Tailored CV').item.json.recordId }}/fldGRlQQUy9RLvbKB/uploadAttachment",
"authentication": "genericCredentialType",
"genericAuthType": "httpHeaderAuth",
"sendHeaders": true,
"headerParameters": {
"parameters": [
{
"name": "Content-Type",
"value": "application/json"
}
]
},
"sendBody": true,
"specifyBody": "json",
"jsonBody": "={\n \"contentType\": \"application/vnd.openxmlformats-officedocument.wordprocessingml.document\",\n \"file\": \"{{ $('Render DOCX').item.json.docx_base64 }}\",\n \"filename\": \"{{ $('Render DOCX').item.json.filename }}\"\n}",
"options": {}
},
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 4.4,
"position": [
4576,
64
],
"id": "17db6d45-27c8-4ca0-8303-1ccb3b931df0",
"name": "HTTP Request",
"credentials": {
"httpHeaderAuth": {
"name": "<your credential>"
}
}
}
],
"connections": {
"Manual Trigger": {
"main": [
[
{
"node": "Get High Fit Jobs",
"type": "main",
"index": 0
}
]
]
},
"Schedule Trigger": {
"main": [
[
{
"node": "Get High Fit Jobs",
"type": "main",
"index": 0
}
]
]
},
"Get High Fit Jobs": {
"main": [
[
{
"node": "Get Profile",
"type": "main",
"index": 0
}
]
]
},
"Get Profile": {
"main": [
[
{
"node": "Build Tailoring Prompt",
"type": "main",
"index": 0
}
]
]
},
"Build Tailoring Prompt": {
"main": [
[
{
"node": "Loop Over Jobs",
"type": "main",
"index": 0
}
]
]
},
"Loop Over Jobs": {
"main": [
[],
[
{
"node": "Tailor CV (GPT-5 mini)",
"type": "main",
"index": 0
}
]
]
},
"Tailor CV (GPT-5 mini)": {
"main": [
[
{
"node": "Parse Tailored CV",
"type": "main",
"index": 0
}
]
]
},
"Parse Tailored CV": {
"main": [
[
{
"node": "Render DOCX",
"type": "main",
"index": 0
}
]
]
},
"Render DOCX": {
"main": [
[
{
"node": "HTTP Request",
"type": "main",
"index": 0
}
]
]
},
"Update Pipeline Record": {
"main": [
[
{
"node": "Wait 2s",
"type": "main",
"index": 0
}
]
]
},
"Wait 2s": {
"main": [
[
{
"node": "Loop Over Jobs",
"type": "main",
"index": 0
}
]
]
},
"HTTP Request": {
"main": [
[
{
"node": "Update Pipeline Record",
"type": "main",
"index": 0
}
]
]
}
},
"active": true,
"settings": {
"executionOrder": "v1",
"binaryMode": "separate",
"availableInMCP": false
},
"versionId": "dd7fdcd3-8bbc-4d66-ab77-0611c06dc300",
"id": "tIAQYpmCnXUhT1dg",
"tags": []
}
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.
airtableTokenApihttpHeaderAuthopenAiApi
Pro
For the full experience including quality scoring and batch install features for each workflow upgrade to Pro
About this workflow
JobSignal - Workflow 3 - Tailor. Uses airtable, openAi, httpRequest. Event-driven trigger; 12 nodes.
Source: https://github.com/RZ-Logic/jobsignal-engine/blob/1d198c8e5bc71962c7906703eb797b4d23be425e/workflows/03-tailor.json — original creator credit. Request a take-down →
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Google Drive Trigger, Google Drive, OpenAI +3
How it works • Automates multi-platform social media posting (Instagram, YouTube, TikTok, etc.) using AI-generated content • Integrates Airtable, n8n, and Blotato for full content scheduling and publi
HTTP Request, Airtable, OpenAI +1