Agent Circle This workflow corresponds to n8n.io template #6086 — we link there as the canonical source.
This workflow follows the Google Sheets → 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 →
{
"id": "IJ4YYLsaOiD1z9Oz",
"meta": {
"templateCredsSetupCompleted": true
},
"name": "YouTube - Audience Comment Analyzer",
"tags": [
{
"id": "CEVEeZJa4qgPvdpK",
"name": "youtube",
"createdAt": "2025-05-27T02:29:43.874Z",
"updatedAt": "2025-05-27T02:29:43.874Z"
}
],
"nodes": [
{
"id": "ecd26999-0115-4739-b02c-65801a35eb51",
"name": "Split Out",
"type": "n8n-nodes-base.splitOut",
"position": [
900,
220
],
"parameters": {
"options": {},
"fieldToSplitOut": "body.items"
},
"typeVersion": 1,
"alwaysOutputData": true
},
{
"id": "1c93def0-47b9-498c-84bb-18b945cc5ecf",
"name": "OpenAI Chat Model",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"position": [
1500,
180
],
"parameters": {
"model": {
"__rl": true,
"mode": "list",
"value": "gpt-4o-mini"
},
"options": {}
},
"credentials": {
"openAiApi": {
"name": "<your credential>"
}
},
"typeVersion": 1.2
},
{
"id": "40976cd9-49d0-44eb-9ef9-55d7a864df54",
"name": "When clicking \u2018Test workflow\u2019",
"type": "n8n-nodes-base.manualTrigger",
"position": [
-360,
220
],
"parameters": {},
"typeVersion": 1
},
{
"id": "69c74c11-d4a5-4b27-9058-60ad46f9421c",
"name": "HTTP Request - Get Comments",
"type": "n8n-nodes-base.httpRequest",
"position": [
520,
220
],
"parameters": {
"url": "https://www.googleapis.com/youtube/v3/commentThreads",
"options": {
"response": {
"response": {
"fullResponse": true,
"responseFormat": "json"
}
},
"pagination": {
"pagination": {
"parameters": {
"parameters": [
{
"name": "pageToken",
"value": "={{ $response.body.nextPageToken }}"
}
]
},
"completeExpression": "={{ !$response.body.nextPageToken}}",
"paginationCompleteWhen": "other"
}
}
},
"sendQuery": true,
"authentication": "predefinedCredentialType",
"queryParameters": {
"parameters": [
{
"name": "part",
"value": "snippet"
},
{
"name": "videoId",
"value": "={{ $json.video_url.match(/(?:v=|\\/)([0-9A-Za-z_-]{11})/)[1] || ''}}"
},
{
"name": "limit",
"value": "100"
}
]
},
"nodeCredentialType": "youTubeOAuth2Api"
},
"credentials": {
"youTubeOAuth2Api": {
"name": "<your credential>"
}
},
"typeVersion": 4.2
},
{
"id": "7148ceec-b9c2-41ab-9e23-092b28d7bdc4",
"name": "Loop Over Items",
"type": "n8n-nodes-base.splitInBatches",
"position": [
320,
220
],
"parameters": {
"options": {}
},
"typeVersion": 3
},
{
"id": "40dba5d2-e175-443d-a417-45bdec5e84ec",
"name": "Sticky Note",
"type": "n8n-nodes-base.stickyNote",
"position": [
-1180,
-320
],
"parameters": {
"width": 660,
"height": 1820,
"content": "## [n8n Automation] YouTube Comments Analyzer - Try It Out!\n\n**This n8n workflow demonstrates how to use this AI Agent to extract, process, and analyze YouTube video comments to understand your audience beyond the view count.**\n\nUse cases are many: Whether you're **a YouTube creator** exploring feedback, **a social media manager** fine-tuning engagement strategy, **a brand team** monitoring campaign sentiment, or **a marketing agency** conducting audits \u2013 this tool brings audience voice to the forefront with structured insights.\n\n## How It Works\n- The workflow starts when you manually click **Test Workflow** or **Execute Workflow** in n8n.\n- It collects all the rows marked as **Ready** in **Column A** in the **Video URLs** tab of your connected Google Sheet.\n- The tool checks if the URLs are not empty first, then it loops through each valid video URL and sends a **GET** request to the **YouTube API** to fetch its comments.\n- It checks the response from the YouTube API. If the call is successful, the comment data is extracted and split into individual entries. \n- The tool then checks whether the video URL has any comment.\n- If no comment is found, the video URL\u2019s status in **Column A** in the **Video URLs** tab is updated to **Finished** right away.\n- If comments are available, they are passed to the **AI Agent - Analyze Sentiment Of Every Comment** using **the Google Gemini chat model**, where each comment is analyzed and classified by sentiment: **Positive**, **Neutral**, or **Negative**. \n- Next, the analysis results are saved to the **Results** tab in your connected Google Sheet. \n- Finally, the original video URL\u2019s status in **Column A** in the **Video URLs** tab is updated to **Finished**, ensuring it won\u2019t be reprocessed in the loop.\n\n## How To Set Up\n- Download the working package and import it into your n8n interface.\n- Duplicate the [**YouTube Comment Analyzer**](https://docs.google.com/spreadsheets/d/18-3CmJPbC73MycmNiSWotdsyGBAAzqESf33vktwnYmM/edit?gid=426418282#gid=426418282) Google Sheet template to your Google Sheets account.\n- Set up necessary credentials for tools access and usability:\n + For **Google Sheets** access, ensure each node is properly connected to the correct tab in your connected Google Sheet template: \n Node **Get Video URLs** \u2192 connected to the **Video URLs** tab\n Node **Insert Comment Data & Analysis** \u2192 connected to the **Results** tab\n Node **Update Video Status** \u2192 connected to the **Video URLs** tab\n + For **YouTube** access, connect to its API in the following node:\n Node **HTTP Request - Get Comments**\n + For **Google Gemini** access, connect to its API in the following node:\n Node **Google Gemini Chat Model**\n- Enter video URLs in **Column B** in the **Video URLs** tab in your connected Google Sheet and mark their status in **Column A** as **Ready**.\n- Click **Test Workflow** or **Execute Workflow** to run the process.\n- Check the results in the **Results** tab of the connected Google Sheet template to view all collected comments along with their sentiment analysis.\n\n## Requirements\n- Basic setup in Google Cloud Console (OAuth or API Key method enabled) with enabled access to YouTube and Google Sheets.\n- API access to **Google Gemini** for sentiment analysis.\n## How To Customize\n- By default, the workflow is manually triggered in N8N. However, you can automate the process by adding a **Google Sheets trigger** that monitors new entries in your connected Google Sheet template and starts the workflow automatically.\n- In the **AI Agent - Analyze Sentiment Of Every Comment** node, you can also change the AI chat model. By default, it uses **Google Gemini**, but you can easily replace it with any other compatible provider such as Deepseek, Grok, etc.\n- You can customize the sentiment categories and instruction prompt for the AI Agent in the **AI Agent \u2013 Analyze Sentiment Of Every Comment** node following your needs. Then, the Agent can return sentiment results that align more closely with your intended use case.\n- Also, feel free to integrate additional nodes (like Telegram or Email) to notify you and your team whenever updates and analysis succeed or fail.\n\n## Need Help?\nIf you\u2019d like this workflow customized, or if you\u2019re looking to build a tailored AI Agent for your own business - please feel free to reach out to [**Agent Circle**](https://www.agentcircle.ai/). We\u2019re always here to support and help you to bring automation ideas to life.\n\nJoin our community on different platforms for assistance, inspiration and tips from others.\n\nWebsite: https://www.agentcircle.ai/\nEtsy: https://www.etsy.com/shop/AgentCircle\nGumroad: http://agentcircle.gumroad.com/\nDiscord Global: https://discord.gg/d8SkCzKwnP\nFB Page Global: https://www.facebook.com/agentcircle/\nFB Group Global: https://www.facebook.com/groups/aiagentcircle/\nX: https://x.com/agent_circle\nYouTube: https://www.youtube.com/@agentcircle\nLinkedIn: https://www.linkedin.com/company/agentcircle\n\n\n"
},
"typeVersion": 1
},
{
"id": "44b7e7f9-dab4-41d2-b0fd-c985da58480c",
"name": "Google Gemini Chat Model",
"type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
"position": [
1320,
180
],
"parameters": {
"options": {},
"modelName": "models/gemini-2.0-flash"
},
"credentials": {
"googlePalmApi": {
"name": "<your credential>"
}
},
"typeVersion": 1
},
{
"id": "e4aef7cf-bb41-49b6-b73a-f065d0534dc3",
"name": "Check If Video URL is Not Empty",
"type": "n8n-nodes-base.if",
"position": [
100,
220
],
"parameters": {
"options": {},
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "loose"
},
"combinator": "and",
"conditions": [
{
"id": "92084960-e023-4cd6-a5c0-ddd43275cc33",
"operator": {
"type": "string",
"operation": "notEmpty",
"singleValue": true
},
"leftValue": "={{ $json.video_url }}",
"rightValue": "={{ $now.toISO() }}"
}
]
},
"looseTypeValidation": true
},
"typeVersion": 2.2
},
{
"id": "cffd5351-827e-4d85-84dd-892ae135aa12",
"name": "Check If - Success Response",
"type": "n8n-nodes-base.if",
"position": [
700,
220
],
"parameters": {
"options": {},
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "bce76f94-5904-4fdb-b172-adc1134855f9",
"operator": {
"type": "number",
"operation": "equals"
},
"leftValue": "={{ $json.statusCode }}",
"rightValue": 200
}
]
}
},
"typeVersion": 2.2
},
{
"id": "445564ea-a3f1-45cb-b887-85bbcf43dd7c",
"name": "Check If - Comment Exists",
"type": "n8n-nodes-base.if",
"position": [
1120,
220
],
"parameters": {
"options": {},
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "e4d47098-097d-4fd7-9703-638858f9565a",
"operator": {
"type": "string",
"operation": "exists",
"singleValue": true
},
"leftValue": "={{ $json.snippet.videoId }}",
"rightValue": ""
}
]
}
},
"typeVersion": 2.2
},
{
"id": "c4971a87-2a5e-428a-8e8f-b82afb4f403d",
"name": "Update Video Status",
"type": "n8n-nodes-base.googleSheets",
"position": [
1720,
460
],
"parameters": {
"columns": {
"value": {
"status": "Finished",
"row_number": "={{ $('Get Video URLs').item.json.row_number }}",
"last_fetched_time": "={{ $now.toISO().toString().slice(0, 19).replace('T', ' ') }}"
},
"schema": [
{
"id": "status",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "status",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "video_url",
"type": "string",
"display": true,
"removed": true,
"required": false,
"displayName": "video_url",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "last_fetched_time",
"type": "string",
"display": true,
"required": false,
"displayName": "last_fetched_time",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "row_number",
"type": "string",
"display": true,
"removed": false,
"readOnly": true,
"required": false,
"displayName": "row_number",
"defaultMatch": false,
"canBeUsedToMatch": true
}
],
"mappingMode": "defineBelow",
"matchingColumns": [
"row_number"
],
"attemptToConvertTypes": false,
"convertFieldsToString": false
},
"options": {},
"operation": "update",
"sheetName": {
"__rl": true,
"mode": "list",
"value": 426418282,
"cachedResultUrl": "https://docs.google.com/spreadsheets/d/18-3CmJPbC73MycmNiSWotdsyGBAAzqESf33vktwnYmM/edit#gid=426418282",
"cachedResultName": "Video URLs"
},
"documentId": {
"__rl": true,
"mode": "list",
"value": "18-3CmJPbC73MycmNiSWotdsyGBAAzqESf33vktwnYmM",
"cachedResultUrl": "https://docs.google.com/spreadsheets/d/18-3CmJPbC73MycmNiSWotdsyGBAAzqESf33vktwnYmM/edit?usp=drivesdk",
"cachedResultName": "YouTube - Audience Feedback Sentiment Analyzer"
}
},
"credentials": {
"googleSheetsOAuth2Api": {
"name": "<your credential>"
}
},
"executeOnce": true,
"typeVersion": 4.5
},
{
"id": "9dffad3c-5940-4623-b6dc-b704a3866e53",
"name": "Get Video URLs",
"type": "n8n-nodes-base.googleSheets",
"position": [
-140,
220
],
"parameters": {
"options": {},
"filtersUI": {
"values": [
{
"lookupValue": "=Ready",
"lookupColumn": "status"
}
]
},
"sheetName": {
"__rl": true,
"mode": "list",
"value": 426418282,
"cachedResultUrl": "https://docs.google.com/spreadsheets/d/18-3CmJPbC73MycmNiSWotdsyGBAAzqESf33vktwnYmM/edit#gid=426418282",
"cachedResultName": "Video URLs"
},
"documentId": {
"__rl": true,
"mode": "list",
"value": "18-3CmJPbC73MycmNiSWotdsyGBAAzqESf33vktwnYmM",
"cachedResultUrl": "https://docs.google.com/spreadsheets/d/18-3CmJPbC73MycmNiSWotdsyGBAAzqESf33vktwnYmM/edit?usp=drivesdk",
"cachedResultName": "YouTube - Audience Feedback Sentiment Analyzer"
}
},
"credentials": {
"googleSheetsOAuth2Api": {
"name": "<your credential>"
}
},
"typeVersion": 4.5
},
{
"id": "6b1f966b-342a-4f37-80e4-179e207ec421",
"name": "Insert Comment Data & Analysis",
"type": "n8n-nodes-base.googleSheets",
"position": [
1740,
120
],
"parameters": {
"columns": {
"value": {
"likes": "={{ $json.snippet.topLevelComment.snippet.likeCount }}",
"reply": "={{ $json.snippet.totalReplyCount }}",
"comment": "={{ $json.snippet.topLevelComment.snippet.textOriginal }}",
"sentiment": "={{ $json.sentimentAnalysis.category }}",
"video_url": "=https://www.youtube.com/watch?v={{ $json.snippet.videoId }}",
"comment_id": "={{ $json.snippet.topLevelComment.id }}",
"author_name": "={{ $json.snippet.topLevelComment.snippet.authorDisplayName }}",
"published_at": "={{ $json.snippet.topLevelComment.snippet.publishedAt.toString().slice(0, 19).replace('T', ' ') }}"
},
"schema": [
{
"id": "video_url",
"type": "string",
"display": true,
"required": false,
"displayName": "video_url",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "comment_id",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "comment_id",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "comment",
"type": "string",
"display": true,
"required": false,
"displayName": "comment",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "author_name",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "author_name",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "likes",
"type": "string",
"display": true,
"required": false,
"displayName": "likes",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "reply",
"type": "string",
"display": true,
"required": false,
"displayName": "reply",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "sentiment",
"type": "string",
"display": true,
"required": false,
"displayName": "sentiment",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "published_at",
"type": "string",
"display": true,
"required": false,
"displayName": "published_at",
"defaultMatch": false,
"canBeUsedToMatch": true
}
],
"mappingMode": "defineBelow",
"matchingColumns": [
"comment_id"
],
"attemptToConvertTypes": false,
"convertFieldsToString": false
},
"options": {},
"operation": "appendOrUpdate",
"sheetName": {
"__rl": true,
"mode": "list",
"value": "gid=0",
"cachedResultUrl": "https://docs.google.com/spreadsheets/d/18-3CmJPbC73MycmNiSWotdsyGBAAzqESf33vktwnYmM/edit#gid=0",
"cachedResultName": "Results "
},
"documentId": {
"__rl": true,
"mode": "list",
"value": "18-3CmJPbC73MycmNiSWotdsyGBAAzqESf33vktwnYmM",
"cachedResultUrl": "https://docs.google.com/spreadsheets/d/18-3CmJPbC73MycmNiSWotdsyGBAAzqESf33vktwnYmM/edit?usp=drivesdk",
"cachedResultName": "YouTube - Audience Feedback Sentiment Analyzer"
}
},
"credentials": {
"googleSheetsOAuth2Api": {
"name": "<your credential>"
}
},
"typeVersion": 4.5
},
{
"id": "0596acb0-ba5a-43cd-8957-ceefd7297d76",
"name": "AI Agent - Analyze Sentiment Of Every Comment",
"type": "@n8n/n8n-nodes-langchain.sentimentAnalysis",
"position": [
1340,
0
],
"parameters": {
"options": {
"categories": "Positive, Neutral, Negative",
"systemPromptTemplate": "You are a highly intelligent and precise sentiment analysis system. \nWhen given any input text, determine its overall sentiment and classify it into one of the following categories: {categories}. \nUse the provided formatting instructions. Respond with exactly one JSON object and nothing else."
},
"inputText": "={{ $json.snippet.topLevelComment.snippet.textOriginal }}"
},
"typeVersion": 1
},
{
"id": "38fabc2b-b369-436f-ac41-3e0cad36498b",
"name": "Sticky Note1",
"type": "n8n-nodes-base.stickyNote",
"position": [
-420,
-240
],
"parameters": {
"color": 4,
"width": 420,
"height": 940,
"content": "## 1. Read Ready Video URLs\n- The workflow begins by pulling all the rows marked as **Ready** in **Column A** from the **Video URLs** tab of your connected Google Sheet. These are the entries queued for processing."
},
"typeVersion": 1
},
{
"id": "bee35409-3dd4-4e03-aa76-12007a785384",
"name": "Sticky Note3",
"type": "n8n-nodes-base.stickyNote",
"position": [
1080,
-240
],
"parameters": {
"color": 4,
"width": 880,
"height": 940,
"content": "## 3. Analyze Comment Sentiment, Update Results And Video Status\n- The tool then checks whether the video URL has any comment.\n- If no comment is found, the video URL\u2019s status in **Column A** in the **Video URLs** tab is updated to **Finished** right away.\n- If comments are available, they are passed to **the Google Gemini chat model**, where each comment is analyzed and labeled as: **Positive**, **Neutral**, or **Negative**. \n- Next, the analysis results are saved to the **Results** tab in your connected Google Sheet. \n- Finally, the original video URL\u2019s status in **Column A** in the **Video URLs** tab is updated to **Finished**, ensuring it won\u2019t be reprocessed in the loop."
},
"typeVersion": 1
},
{
"id": "73644694-fd5c-4962-8412-6249766024c1",
"name": "Sticky Note2",
"type": "n8n-nodes-base.stickyNote",
"position": [
40,
-240
],
"parameters": {
"color": 4,
"width": 1020,
"height": 940,
"content": "## 2. Fetch Comments Via YouTube API\n- The tool checks if the URLs are not empty first, then it loops through each valid video URL and sends a **GET** request to the **YouTube API** to fetch its comments.\n- It checks the response from the YouTube API. If the call is successful, the comment data is extracted and split into individual entries. "
},
"typeVersion": 1
}
],
"active": false,
"settings": {
"executionOrder": "v1"
},
"versionId": "1763a723-5e69-4d7d-ac35-664c14ddf023",
"connections": {
"Split Out": {
"main": [
[
{
"node": "Check If - Comment Exists",
"type": "main",
"index": 0
}
]
]
},
"Get Video URLs": {
"main": [
[
{
"node": "Check If Video URL is Not Empty",
"type": "main",
"index": 0
}
]
]
},
"Loop Over Items": {
"main": [
[],
[
{
"node": "HTTP Request - Get Comments",
"type": "main",
"index": 0
}
]
]
},
"OpenAI Chat Model": {
"ai_languageModel": [
[]
]
},
"Update Video Status": {
"main": [
[
{
"node": "Loop Over Items",
"type": "main",
"index": 0
}
]
]
},
"Google Gemini Chat Model": {
"ai_languageModel": [
[
{
"node": "AI Agent - Analyze Sentiment Of Every Comment",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Check If - Comment Exists": {
"main": [
[
{
"node": "AI Agent - Analyze Sentiment Of Every Comment",
"type": "main",
"index": 0
}
],
[
{
"node": "Update Video Status",
"type": "main",
"index": 0
}
]
]
},
"Check If - Success Response": {
"main": [
[
{
"node": "Split Out",
"type": "main",
"index": 0
}
]
]
},
"HTTP Request - Get Comments": {
"main": [
[
{
"node": "Check If - Success Response",
"type": "main",
"index": 0
}
]
]
},
"Insert Comment Data & Analysis": {
"main": [
[
{
"node": "Update Video Status",
"type": "main",
"index": 0
}
]
]
},
"Check If Video URL is Not Empty": {
"main": [
[
{
"node": "Loop Over Items",
"type": "main",
"index": 0
}
]
]
},
"When clicking \u2018Test workflow\u2019": {
"main": [
[
{
"node": "Get Video URLs",
"type": "main",
"index": 0
}
]
]
},
"AI Agent - Analyze Sentiment Of Every Comment": {
"main": [
[
{
"node": "Insert Comment Data & Analysis",
"type": "main",
"index": 0
}
],
[
{
"node": "Insert Comment Data & Analysis",
"type": "main",
"index": 0
}
],
[
{
"node": "Insert Comment Data & Analysis",
"type": "main",
"index": 0
}
]
]
}
}
}
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.
googlePalmApigoogleSheetsOAuth2ApiopenAiApiyouTubeOAuth2Api
Pro
For the full experience including quality scoring and batch install features for each workflow upgrade to Pro
About this workflow
Use cases are many: Whether you're a YouTube creator exploring feedback, a social media manager fine-tuning engagement strategy, a brand team monitoring campaign sentiment, or a marketing agency conducting audits – this tool brings audience voice to the forefront with structured…
Source: https://n8n.io/workflows/6086/ — original creator credit. Request a take-down →
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Workflows that share integrations, category, or trigger type with this one. All free to copy and import.
This workflow automates the process of scraping Trustpilot reviews, extracting key details, analyzing sentiment, and saving the results to Google Sheets. It uses OpenAI for sentiment analysis and HTML
Information Extractor, HTTP Request, Google Sheets +2
Influencers, marketers, and data teams who need instant insights into audience sentiment—without manual exports or scattered tools. Manual exports from YouTube Studio Time-consuming sentiment tagging
OpenAI Chat, Google Sheets, HTTP Request +1
Episode 18 Scary Stories TikTok final. Uses httpRequest, lmChatOpenAi, lmChatOllama, lmChatDeepSeek. Event-driven trigger; 83 nodes.
HTTP Request, OpenAI Chat, Ollama Chat +12
Transform your Gmail sent folder into a comprehensive, enriched contact database automatically. This workflow processes hundreds or thousands of sent emails, extracting and enriching contact informati
HTTP Request, @Brave/N8N Nodes Brave Search, Gmail +3
This template can be used to automatically label your incoming Gmail messages with AI and to build a knowledge graph from the emails tagged with a specific label to brainstorm new ideas based on them.
Gmail Trigger, OpenAI Chat, Gmail +4