This workflow follows the Gmail Trigger → Google Sheets recipe pattern — see all workflows that pair these two integrations.
The workflow JSON
Copy or download the full n8n JSON below. Paste it into a new n8n workflow, add your credentials, activate. Full import guide →
{
"id": "Pl7ZdR3PNRcgfzMF",
"name": "[0] Gmail Trigger \u2192 Classify \u2192 Route to Pipeline (FIXED)",
"description": null,
"active": true,
"isArchived": false,
"nodes": [
{
"parameters": {
"pollTimes": {
"item": [
{
"mode": "everyMinute"
}
]
},
"simple": false,
"filters": {
"readStatus": "unread"
},
"options": {}
},
"id": "a1dc6e81-0362-471a-b2dd-8d2ca9c9de83",
"name": "Watch for Emails",
"type": "n8n-nodes-base.gmailTrigger",
"typeVersion": 1,
"position": [
-656,
172
],
"credentials": {
"gmailOAuth2": {
"name": "<your credential>"
}
},
"notes": "CRITICAL SETTINGS:\n1. Simplify = OFF (needed for threadId and labelIds)\n2. Poll every 5 minutes (adjust based on responsiveness needs)\n3. Read Status = Unread only\n\nThis triggers on new unread emails and passes full metadata."
},
{
"parameters": {
"jsCode": "// Email Pre-Filter v1.2 - FIXED to work with Extract Full Email Body node\n// 4-layer filtering: Domain, Headers, Patterns, Gmail Categories\n// Catches 60-80% of non-customer emails BEFORE AI classification\n\nconst items = $input.all();\nconst results = [];\n\n// ============ CONFIGURATION ============\nconst COMPANY_DOMAINS = [\n 'hattieb.com',\n 'hattiebshotchicken.com',\n 'aibuildlab.com'\n];\n\nconst AUTO_REPLY_SENDERS = [\n /noreply@/i,\n /no-reply@/i,\n /notifications?@/i,\n /alerts?@/i,\n /mailer-daemon@/i,\n /postmaster@/i,\n /donotreply@/i\n];\n\nconst AUTO_REPLY_SUBJECTS = [\n /out of office/i,\n /automatic reply/i,\n /auto-reply/i,\n /auto reply/i,\n /vacation.*reply/i,\n /away from (my )?office/i,\n /delivery status notification/i,\n /undeliverable/i,\n /mail delivery failed/i\n];\n\nconst SKIP_GMAIL_CATEGORIES = [\n 'CATEGORY_PROMOTIONS',\n 'CATEGORY_SOCIAL',\n 'SPAM'\n];\n// =========================================\n\nfor (const item of items) {\n const email = item.json;\n \n // Extract email fields - handle BOTH new Extract node output AND old Gmail structure\n let from, subject, fullBody, emailId, threadId, labelIds, date;\n \n if (email.fullEmailBody) {\n // NEW structure from \"Extract Full Email Body\" node\n from = email.from || '';\n subject = email.subject || '';\n fullBody = email.fullEmailBody;\n emailId = email.id || email.messageId;\n threadId = email.threadId;\n labelIds = email.labelIds || [];\n date = email.date;\n } else {\n // OLD structure from Gmail Trigger (fallback)\n from = email.from?.text || email.from?.value?.[0]?.address || email.From || '';\n subject = email.subject || email.Subject || '';\n fullBody = email.text || email.textPlain || email.body || email.snippet || '';\n emailId = email.id || email.messageId;\n threadId = email.threadId;\n labelIds = email.labelIds || [];\n date = email.internalDate || email.date;\n }\n \n const fromLower = from.toLowerCase();\n \n // Parse headers\n let headers = {};\n if (email.payload && email.payload.headers) {\n email.payload.headers.forEach(h => {\n headers[h.name.toLowerCase()] = h.value;\n });\n } else if (email.headers) {\n headers = email.headers;\n }\n \n // ============ LAYER 1: OWN DOMAIN (Loop Prevention) ============\n for (const domain of COMPANY_DOMAINS) {\n if (fromLower.includes('@' + domain.toLowerCase())) {\n results.push({\n json: {\n skip: true,\n reason: 'own_domain',\n classification_override: 'internal',\n confidence: 1.0,\n message: `Email from own domain (${domain}) - loop prevention`,\n email_id: emailId,\n thread_id: threadId,\n from: from,\n subject: subject\n }\n });\n continue;\n }\n }\n if (results.length > 0 && results[results.length - 1].json.skip) continue;\n \n // ============ LAYER 2: AUTO-REPLY HEADERS ============\n const autoReplyHeaders = [\n 'x-auto-response-suppress',\n 'auto-submitted',\n 'x-autoreply',\n 'x-autorespond'\n ];\n \n for (const headerName of autoReplyHeaders) {\n const headerValue = headers[headerName];\n if (headerValue && headerValue.toLowerCase() !== 'no') {\n results.push({\n json: {\n skip: true,\n reason: 'auto_reply_header',\n classification_override: 'automated',\n confidence: 1.0,\n message: `Auto-reply header detected: ${headerName}`,\n email_id: emailId,\n thread_id: threadId,\n from: from,\n subject: subject\n }\n });\n break;\n }\n }\n if (results.length > 0 && results[results.length - 1].json.skip) continue;\n \n // Check Precedence header\n const precedence = headers['precedence'];\n if (precedence && /bulk|junk|list/i.test(precedence)) {\n results.push({\n json: {\n skip: true,\n reason: 'bulk_mail',\n classification_override: 'automated',\n confidence: 0.95,\n message: `Bulk mail header: Precedence: ${precedence}`,\n email_id: emailId,\n thread_id: threadId,\n from: from,\n subject: subject\n }\n });\n continue;\n }\n \n // ============ LAYER 3: PATTERN MATCHING ============\n for (const pattern of AUTO_REPLY_SENDERS) {\n if (pattern.test(fromLower)) {\n results.push({\n json: {\n skip: true,\n reason: 'auto_reply_sender',\n classification_override: 'automated',\n confidence: 0.95,\n message: `Known auto-reply sender pattern: ${from}`,\n email_id: emailId,\n thread_id: threadId,\n from: from,\n subject: subject\n }\n });\n break;\n }\n }\n if (results.length > 0 && results[results.length - 1].json.skip) continue;\n \n for (const pattern of AUTO_REPLY_SUBJECTS) {\n if (pattern.test(subject)) {\n results.push({\n json: {\n skip: true,\n reason: 'auto_reply_subject',\n classification_override: 'automated',\n confidence: 0.90,\n message: `Subject matches auto-reply pattern`,\n email_id: emailId,\n thread_id: threadId,\n from: from,\n subject: subject\n }\n });\n break;\n }\n }\n if (results.length > 0 && results[results.length - 1].json.skip) continue;\n \n // ============ LAYER 4: GMAIL CATEGORIES ============\n for (const category of SKIP_GMAIL_CATEGORIES) {\n if (labelIds.includes(category)) {\n results.push({\n json: {\n skip: true,\n reason: 'gmail_category',\n classification_override: category === 'SPAM' ? 'spam' : 'automated',\n confidence: 0.90,\n message: `Gmail category: ${category}`,\n email_id: emailId,\n thread_id: threadId,\n from: from,\n subject: subject\n }\n });\n break;\n }\n }\n if (results.length > 0 && results[results.length - 1].json.skip) continue;\n \n // ============ PASSED ALL FILTERS ============\n results.push({\n json: {\n skip: false,\n reason: null,\n email_data: {\n id: emailId,\n thread_id: threadId,\n from: from,\n subject: subject,\n snippet: fullBody.substring(0, 500),\n body: fullBody,\n labelIds: labelIds,\n date: date\n }\n }\n });\n}\n\nreturn results;"
},
"id": "a803feb2-73da-4bd1-9125-231f1e243201",
"name": "Free Filter (Pre-Check)",
"type": "n8n-nodes-base.code",
"typeVersion": 2,
"position": [
16,
172
],
"notes": "4-layer pre-filter catches 60-80% of emails for FREE:\n\n1. Own Domain - Prevents infinite reply loops (CRITICAL)\n2. Auto-Reply Headers - X-Auto-Response-Suppress, etc.\n3. Pattern Matching - noreply@, Out of Office, etc.\n4. Gmail Categories - Promotions, Social, Spam\n\nv1.1: FIXED email body extraction to get full content, not truncated snippet\n\nEDIT THE COMPANY_DOMAINS ARRAY with your domain(s)."
},
{
"parameters": {
"conditions": {
"options": {
"caseSensitive": true,
"leftValue": "",
"typeValidation": "strict"
},
"conditions": [
{
"id": "condition-skip",
"leftValue": "={{ $json.skip }}",
"rightValue": true,
"operator": {
"type": "boolean",
"operation": "equals"
}
}
],
"combinator": "and"
},
"options": {}
},
"id": "a4ff004d-dde7-4d25-a9a3-048b32a097f3",
"name": "Pre-Filtered?",
"type": "n8n-nodes-base.if",
"typeVersion": 2,
"position": [
240,
172
],
"notes": "Routes emails based on pre-filter result:\n- TRUE (skip=true): Email was filtered, log and end\n- FALSE (skip=false): Continue to AI classification"
},
{
"parameters": {
"operation": "append",
"documentId": {
"__rl": true,
"mode": "id",
"value": "1xTng5h4vCWzFRtEvs05FX1lwguB6Mob-2G_LTgicn4I"
},
"sheetName": {
"__rl": true,
"value": 2063146029,
"mode": "list",
"cachedResultName": "Pre-Filter Log",
"cachedResultUrl": "https://docs.google.com/spreadsheets/d/1xTng5h4vCWzFRtEvs05FX1lwguB6Mob-2G_LTgicn4I/edit#gid=2063146029"
},
"columns": {
"mappingMode": "defineBelow",
"value": {
"timestamp": "={{ $now.toISO() }}",
"email_id": "={{ $json.email_id }}",
"from": "={{ $json.from }}",
"subject": "={{ $json.subject }}",
"reason": "={{ $json.reason }}",
"classification": "={{ $json.classification_override }}",
"confidence": "={{ $json.confidence }}",
"message": "={{ $json.message }}"
},
"matchingColumns": [],
"schema": []
},
"options": {}
},
"id": "a51aed4b-c39e-4d0b-a070-61da6e170144",
"name": "Log Skipped Email",
"type": "n8n-nodes-base.googleSheets",
"typeVersion": 4.5,
"position": [
528,
0
],
"credentials": {
"googleSheetsOAuth2Api": {
"name": "<your credential>"
}
},
"notes": "Logs pre-filtered emails to Google Sheets."
},
{
"parameters": {
"inputText": "={{ 'Subject: ' + $json.email_data.subject + '\\n\\nFrom: ' + $json.email_data.from + '\\n\\nBody: ' + ($json.email_data.snippet || $json.email_data.body).substring(0, 1000) }}",
"categories": {
"categories": [
{
"category": "customer_service",
"description": "A real customer or potential customer needing help, information, or support. Includes: product questions, order issues, account problems, complaints, feature requests, or general inquiries. WHEN IN DOUBT, USE THIS CATEGORY."
},
{
"category": "spam",
"description": "Promotional content, marketing emails, unsolicited offers, or junk mail."
},
{
"category": "internal",
"description": "Communications from within the company or related to internal operations."
},
{
"category": "automated",
"description": "System-generated emails that don't require human response."
},
{
"category": "other",
"description": "Content that doesn't clearly fit the above categories. Use sparingly."
}
]
},
"options": {}
},
"id": "a7e1117d-772c-4747-a36c-84f227c2fcc2",
"name": "AI Classification",
"type": "@n8n/n8n-nodes-langchain.textClassifier",
"typeVersion": 1,
"position": [
464,
344
],
"notes": "Classifies email into 5 categories using AI."
},
{
"parameters": {
"assignments": {
"assignments": [
{
"id": "class-result",
"name": "classification",
"value": "customer_service",
"type": "string"
},
{
"id": "class-confidence",
"name": "confidence",
"value": 0.9,
"type": "number"
},
{
"id": "original-email",
"name": "email_data",
"value": "={{ $('Free Filter (Pre-Check)').item.json.email_data }}",
"type": "object"
}
]
},
"options": {}
},
"id": "a0c81aa2-5715-4df7-8b13-05ffcc478cca",
"name": "Format Classification",
"type": "n8n-nodes-base.set",
"typeVersion": 3.4,
"position": [
816,
344
],
"notes": "Formats classification result for logging and routing."
},
{
"parameters": {
"operation": "append",
"documentId": {
"__rl": true,
"mode": "id",
"value": "1xTng5h4vCWzFRtEvs05FX1lwguB6Mob-2G_LTgicn4I"
},
"sheetName": {
"__rl": true,
"value": 871095556,
"mode": "list",
"cachedResultName": "Classification Log"
},
"columns": {
"mappingMode": "defineBelow",
"value": {
"timestamp": "={{ $now.toISO() }}",
"email_id": "={{ $json.email_data.id }}",
"thread_id": "={{ $json.email_data.thread_id }}",
"from": "={{ $json.email_data.from }}",
"subject": "={{ $json.email_data.subject }}",
"classification": "={{ $json.classification }}",
"confidence": "={{ $json.confidence }}",
"model": "gemini-2.5-flash",
"pre_filter": "passed"
},
"matchingColumns": [],
"schema": []
},
"options": {}
},
"id": "a406b8ae-6fe2-4aaf-a854-0c1773285ded",
"name": "Log Classification",
"type": "n8n-nodes-base.googleSheets",
"typeVersion": 4.5,
"position": [
1040,
344
],
"credentials": {
"googleSheetsOAuth2Api": {
"name": "<your credential>"
}
},
"notes": "Logs AI classification results to Google Sheets."
},
{
"parameters": {
"conditions": {
"options": {
"caseSensitive": true,
"leftValue": "",
"typeValidation": "strict"
},
"conditions": [
{
"id": "condition-customer",
"leftValue": "={{ $json.classification }}",
"rightValue": "customer_service",
"operator": {
"type": "string",
"operation": "equals"
}
}
],
"combinator": "and"
},
"options": {}
},
"id": "a86bb039-3e2c-4783-badd-eeb33a2f6528",
"name": "Customer Email?",
"type": "n8n-nodes-base.if",
"typeVersion": 2,
"position": [
1264,
344
],
"notes": "Routes based on classification."
},
{
"parameters": {
"assignments": {
"assignments": [
{
"id": "output-status",
"name": "status",
"value": "CUSTOMER_EMAIL",
"type": "string"
},
{
"id": "output-next",
"name": "next_step",
"value": "CinnaMon sentiment analysis",
"type": "string"
},
{
"id": "output-email",
"name": "email_data",
"value": "={{ $('Format Classification').item.json.email_data }}",
"type": "object"
},
{
"id": "output-classification",
"name": "filter_result",
"value": "={{ { classification: $json.classification, confidence: $json.confidence } }}",
"type": "object"
}
]
},
"options": {}
},
"id": "a87687e0-7f44-4271-952b-9972f343bf0f",
"name": "Continue to CinnaMon",
"type": "n8n-nodes-base.set",
"typeVersion": 3.4,
"position": [
1488,
248
],
"notes": "Customer email identified. Output ready for CinnaMon agent."
},
{
"parameters": {
"assignments": {
"assignments": [
{
"id": "archive-status",
"name": "status",
"value": "FILTERED",
"type": "string"
},
{
"id": "archive-reason",
"name": "reason",
"value": "={{ 'Classified as: ' + $json.classification }}",
"type": "string"
},
{
"id": "archive-email",
"name": "email_id",
"value": "={{ $json.email_data.id }}",
"type": "string"
}
]
},
"options": {}
},
"id": "a911c8c4-d6c8-4597-b26a-69cafc6a551b",
"name": "End (Not Customer)",
"type": "n8n-nodes-base.set",
"typeVersion": 3.4,
"position": [
1488,
440
],
"notes": "Non-customer email. Workflow ends here."
},
{
"parameters": {
"workflowId": {
"__rl": true,
"value": "C2KIpNrNjr5TPMq6",
"mode": "id"
},
"workflowInputs": {
"mappingMode": "defineBelow",
"value": {
"email_id": "={{ $json.email_data.id }}",
"thread_id": "={{ $json.email_data.thread_id }}",
"from": "={{ $json.email_data.from }}",
"subject": "={{ $json.email_data.subject }}",
"body": "={{ $json.email_data.body }}",
"timestamp": "={{ $json.email_data.date }}",
"classification": "={{ $json.filter_result.classification }}"
},
"matchingColumns": [],
"schema": []
},
"options": {}
},
"id": "aexecute-w1-pipeline",
"name": "Execute W1 Pipeline",
"type": "n8n-nodes-base.executeWorkflow",
"typeVersion": 1.3,
"position": [
1712,
248
],
"notes": "Triggers W1 Email Processing Pipeline with customer email data."
},
{
"parameters": {
"options": {
"temperature": 0.1
}
},
"id": "a36cd1b0-d187-46c4-a82e-b4b76c46626a",
"name": "Gemini Flash 2.5",
"type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
"typeVersion": 1,
"position": [
536,
664
],
"credentials": {
"googlePalmApi": {
"name": "<your credential>"
}
},
"notes": "Gemini Flash 2.5-Lite for cost-effective classification."
},
{
"parameters": {
"url": "=https://gmail.googleapis.com/gmail/v1/users/me/messages/{{ $json.id }}",
"authentication": "predefinedCredentialType",
"nodeCredentialType": "gmailOAuth2",
"sendQuery": true,
"queryParameters": {
"parameters": [
{
"name": "format",
"value": "full"
}
]
},
"options": {}
},
"id": "aget-full-email-http",
"name": "Get Full Email via API",
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 4.1,
"position": [
-432,
172
],
"credentials": {
"gmailOAuth2": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"jsCode": "// Extract and decode full email body from Gmail API response\nconst message = $input.first().json;\n\nfunction extractEmailBody(message) {\n const id = message?.id || '';\n const threadId = message?.threadId || '';\n const labelIds = message?.labelIds || [];\n \n if (!message || !message.payload) {\n return { \n id,\n threadId,\n labelIds,\n fullEmailBody: message?.snippet || \"No email content found\",\n subject: '',\n from: '',\n date: ''\n };\n }\n \n function findPlainText(parts) {\n for (const part of parts) {\n if (part.mimeType === 'text/plain' && part.body?.data) {\n return part.body.data;\n }\n if (part.parts) {\n const found = findPlainText(part.parts);\n if (found) return found;\n }\n }\n return null;\n }\n \n let encodedBody = null;\n \n if (message.payload.body?.data) {\n encodedBody = message.payload.body.data;\n } else if (message.payload.parts) {\n encodedBody = findPlainText(message.payload.parts);\n }\n \n const headers = message.payload.headers || [];\n const subject = headers.find(h => h.name === 'Subject')?.value || '';\n const from = headers.find(h => h.name === 'From')?.value || '';\n const date = headers.find(h => h.name === 'Date')?.value || '';\n \n if (!encodedBody) {\n return {\n id,\n threadId,\n labelIds,\n fullEmailBody: message.snippet || \"Could not extract email body\",\n subject,\n from,\n date\n };\n }\n \n const base64url = encodedBody.replace(/-/g, '+').replace(/_/g, '/');\n const padding = 4 - (base64url.length % 4);\n const base64 = padding !== 4 ? base64url + '='.repeat(padding) : base64url;\n \n try {\n const decoded = Buffer.from(base64, 'base64').toString('utf8');\n return { id, threadId, labelIds, fullEmailBody: decoded, subject, from, date };\n } catch (error) {\n return { \n id,\n threadId,\n labelIds,\n fullEmailBody: `Error decoding: ${error.message}`,\n subject,\n from,\n date\n };\n }\n}\n\nreturn extractEmailBody(message);"
},
"id": "aextract-email-body",
"name": "Extract Full Email Body",
"type": "n8n-nodes-base.code",
"typeVersion": 2,
"position": [
-208,
172
]
}
],
"connections": {
"Watch for Emails": {
"main": [
[
{
"node": "Get Full Email via API",
"type": "main",
"index": 0
}
]
]
},
"Free Filter (Pre-Check)": {
"main": [
[
{
"node": "Pre-Filtered?",
"type": "main",
"index": 0
}
]
]
},
"Pre-Filtered?": {
"main": [
[
{
"node": "Log Skipped Email",
"type": "main",
"index": 0
}
],
[
{
"node": "AI Classification",
"type": "main",
"index": 0
}
]
]
},
"AI Classification": {
"main": [
[
{
"node": "Format Classification",
"type": "main",
"index": 0
}
]
]
},
"Format Classification": {
"main": [
[
{
"node": "Log Classification",
"type": "main",
"index": 0
}
]
]
},
"Log Classification": {
"main": [
[
{
"node": "Customer Email?",
"type": "main",
"index": 0
}
]
]
},
"Customer Email?": {
"main": [
[
{
"node": "Continue to CinnaMon",
"type": "main",
"index": 0
}
],
[
{
"node": "End (Not Customer)",
"type": "main",
"index": 0
}
]
]
},
"Continue to CinnaMon": {
"main": [
[
{
"node": "Execute W1 Pipeline",
"type": "main",
"index": 0
}
]
]
},
"Gemini Flash 2.5": {
"ai_languageModel": [
[
{
"node": "AI Classification",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Get Full Email via API": {
"main": [
[
{
"node": "Extract Full Email Body",
"type": "main",
"index": 0
}
]
]
},
"Extract Full Email Body": {
"main": [
[
{
"node": "Free Filter (Pre-Check)",
"type": "main",
"index": 0
}
]
]
}
},
"settings": {
"executionOrder": "v1",
"callerPolicy": "workflowsFromSameOwner",
"availableInMCP": false
},
"meta": null
}
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.
gmailOAuth2googlePalmApigoogleSheetsOAuth2Api
Pro
For the full experience including quality scoring and batch install features for each workflow upgrade to Pro
About this workflow
[0] Gmail Trigger → Classify → Route to Pipeline (FIXED). Uses gmailTrigger, googleSheets, textClassifier, lmChatGoogleGemini. Event-driven trigger; 14 nodes.
Source: https://github.com/8Dvibes/mindvalley-ai-mastery-students/blob/main/workflows/00-Filter-Email-Classification.json — original creator credit. Request a take-down →
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