{ "name": "YouTube Autonomous Content Factory - Commercial Edition", "nodes": [ { "parameters": { "httpMethod": "POST", "path": "youtube-content-factory", "responseMode": "responseNode", "options": {} }, "id": "cc6e191e-d1be-42de-8413-a082c4efc714", "name": "Webhook - Custom Topic Trigger", "type": "n8n-nodes-base.webhook", "typeVersion": 2.1, "position": [ -544, 16 ], "webhookId": "yt-commercial-factory-001" }, { "parameters": {}, "id": "e45367d0-d1f5-4065-a7c6-7549638c3568", "name": "Manual Demo Trigger", "type": "n8n-nodes-base.manualTrigger", "typeVersion": 1, "position": [ -544, 208 ] }, { "parameters": { "rule": { "interval": [ { "field": "weeks", "triggerAtDay": [ 1, 3, 5 ], "triggerAtHour": 9 } ] } }, "id": "39e79d74-3cc7-4437-837b-fd6503a00bcd", "name": "Automated Schedule (Mon/Wed/Fri)", "type": "n8n-nodes-base.scheduleTrigger", "typeVersion": 1.2, "position": [ -544, 384 ] }, { "parameters": { "jsCode": "\nconst input = $input.first()?.json || {};\nconst body = input.body || input;\n\n// Mode selection: 'reddit' (scrapes top posts) or 'custom' (uses user topic)\nconst mode = body.mode || 'reddit';\nconst subreddit = body.subreddit || 'n8n'; // e.g. 'n8n', 'Automate', 'technology', 'TrueCrime', 'financialindependence'\nconst customNiche = body.niche || 'AI Automation & Applied Engineering';\nconst customTopic = body.topic || '';\nconst targetAudience = body.target_audience || 'Entrepreneurs, developers, and agency builders';\nconst targetDuration = body.target_duration_minutes || 8;\nconst voiceId = body.voice_id || 'cgSgspJ2msm6clMCkdW9'; // Jessica / Custom Voice\nconst elevenLabsKey = body.elevenlabs_api_key || 'sk_7081d73bd184e13003bd6340518621aae220a8d1bd64f5ba';\nconst creatomateApiKey = body.creatomate_api_key || '';\n\nconst projectId = 'yt_pipe_' + Date.now();\n\nreturn [{\n json: {\n project_id: projectId,\n mode: mode,\n subreddit: subreddit,\n custom_niche: customNiche,\n custom_topic: customTopic,\n target_audience: targetAudience,\n target_duration_minutes: targetDuration,\n voice_id: voiceId,\n elevenlabs_api_key: elevenLabsKey,\n creatomate_api_key: creatomateApiKey,\n created_at: new Date().toISOString()\n }\n}];\n" }, "id": "82d9f427-3133-4401-9017-e339dbf50fab", "name": "Pipeline Config & Router", "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ -272, 208 ] }, { "parameters": { "conditions": { "options": { "caseSensitive": true, "leftValue": "", "typeValidation": "strict", "version": 2 }, "conditions": [ { "leftValue": "={{ $json.mode }}", "operator": { "type": "string", "operation": "equals" }, "rightValue": "reddit" } ], "combinator": "and" }, "options": {} }, "id": "52b3ed19-c254-4615-92fa-ea81d0cba7bd", "name": "Is Reddit Mode?", "type": "n8n-nodes-base.if", "typeVersion": 2.3, "position": [ -16, 208 ] }, { "parameters": { "url": "=https://www.reddit.com/r/{{ $json.subreddit }}/top.json?t=week&limit=5", "options": { "redirect": { "redirect": {} } } }, "id": "02240cec-8ad9-4c05-aef6-e99512ba0e99", "name": "Fetch Top Reddit Posts (Free Public API)", "type": "n8n-nodes-base.httpRequest", "typeVersion": 4.2, "position": [ 224, 96 ], "onError": "continueRegularOutput" }, { "parameters": { "jsCode": "\nconst config = $('Pipeline Config & Router').first().json;\nconst rawResp = $input.first()?.json || {};\n\nlet postList = [];\ntry {\n const children = rawResp.data?.children || [];\n postList = children\n .map(c => c.data)\n .filter(p => !p.stickied && !p.over_18 && (p.selftext || p.title))\n .map(p => ({\n title: p.title,\n text: p.selftext ? p.selftext.slice(0, 1500) : '',\n score: p.score,\n comments_count: p.num_comments,\n permalink: 'https://reddit.com' + p.permalink\n }));\n} catch (e) {\n postList = [];\n}\n\nconst topPost = postList[0] || {\n title: \"Why our client's AI agent crashed after handling 500 calls\",\n text: \"We built an autonomous customer service agent in n8n. Everything worked fine in testing, but in production memory state drifted and API rate limits caused webhook timeouts...\",\n score: 342,\n comments_count: 89,\n permalink: \"https://reddit.com/r/n8n/sample\"\n};\n\nreturn [{\n json: {\n ...config,\n source_type: \"Reddit /r/\" + config.subreddit,\n source_data: topPost,\n topic_query: topPost.title + \" | \" + topPost.text\n }\n}];\n" }, "id": "d695ecee-0965-492d-8759-406cfd9553b9", "name": "Parse & Extract Top Post", "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ 464, 96 ] }, { "parameters": { "jsCode": "\nconst config = $('Pipeline Config & Router').first().json;\nreturn [{\n json: {\n ...config,\n source_type: \"Custom Topic Input\",\n source_data: { title: config.custom_topic || config.custom_niche },\n topic_query: config.custom_topic || (\"Trending developments and high-interest challenges in \" + config.custom_niche)\n }\n}];\n" }, "id": "6d5e480a-86f3-4ea3-9bb0-27394107b644", "name": "Parse Custom Input", "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ 320, 352 ] }, { "parameters": { "promptType": "define", "text": "=You are Agent 1 (Trend Intelligence & Hook Strategist).\n\nAnalyze this viral content candidate:\nSource: {{ $json.source_type }}\nTopic/Story Input: {{ $json.topic_query }}\nTarget Audience: {{ $json.target_audience }}\n\nFormulate the definitive YouTube video concept:\n1. Contrarian Angle: What makes this surprising or counter-intuitive?\n2. Core Retention Thesis: The central argument that keeps viewers hooked.\n3. 3 Open Curiosity Loops that will be answered throughout the video.\n\nReturn strict JSON matching this schema:\n{\n \"chosen_topic\": \"...\",\n \"contrarian_angle\": \"...\",\n \"retention_thesis\": \"...\",\n \"target_emotion\": \"...\",\n \"open_loops\": [\"Loop 1\", \"Loop 2\", \"Loop 3\"]\n}", "options": { "systemMessage": "You are a master YouTube content strategist. You turn raw forum posts and industry news into high-retention video premises. Return valid JSON only." } }, "id": "a030435e-647e-4b9b-bd25-5705f7be8538", "name": "Agent 1: Trend & Hook Strategist", "type": "@n8n/n8n-nodes-langchain.agent", "typeVersion": 3.1, "position": [ 720, 208 ] }, { "parameters": { "modelName": "models/gemini-2.5-flash", "options": {} }, "id": "ef06b358-bf9a-474d-a8c9-74b87d50159d", "name": "Gemini Model - Agent 1", "type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini", "typeVersion": 1.1, "position": [ 720, 400 ], "credentials": { "googlePalmApi": { "id": "bYHzK3NKnwkitc2i", "name": "Google Gemini(PaLM) Api account" } } }, { "parameters": { "jsCode": "\nconst inputNode = $('Is Reddit Mode?').first().json.mode === 'reddit' \n ? $('Parse & Extract Top Post').first().json \n : $('Parse Custom Input').first().json;\n\nconst rawOutput = $input.first().json.output || '{}';\n\nlet research = {};\ntry {\n const cleaned = rawOutput.replace(/```json/g, '').replace(/```/g, '').trim();\n research = JSON.parse(cleaned);\n} catch (e) {\n research = {\n chosen_topic: \"Why 84% of Autonomous AI Agents Collapse in Production\",\n contrarian_angle: \"The issue is not model intelligence; it is state drift and unhandled edge timeouts.\",\n retention_thesis: \"Most tutorials build fragile toy prototypes; enterprise systems require deterministic state machines.\",\n target_emotion: \"Shock, curiosity, vindication\",\n open_loops: [\n \"The exact $4,000 error that broke an agency automation\",\n \"Why adding more LLM tools degrades system reliability\",\n \"The 3-layer architecture used by senior automation engineers\"\n ]\n };\n}\n\nreturn [{\n json: {\n ...inputNode,\n topic_research: research\n }\n}];\n" }, "id": "47446536-a9da-4f83-ab8b-8e8deeda4772", "name": "Format Research Intelligence", "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ 1008, 208 ] }, { "parameters": { "promptType": "define", "text": "=You are Agent 2 (Viral Script & Scene Architect).\n\nWrite an elite faceless YouTube script based on this intelligence:\nTopic: {{ $json.topic_research.chosen_topic }}\nContrarian Angle: {{ $json.topic_research.contrarian_angle }}\nRetention Thesis: {{ $json.topic_research.retention_thesis }}\nTarget Duration: {{ $json.target_duration_minutes }} Minutes\nOpen Loops: {{ JSON.stringify($json.topic_research.open_loops) }}\n\nSTRICT 5-PART RETENTION RULES:\n1. Hook (0:00-0:30): Visual pattern interrupt, negative hypothesis, stake escalation. No greetings.\n2. Context & Fast Payoff (0:30-2:00): Deliver early reward, open secondary loop.\n3. Core Story Beats (2:00-6:30): 3 escalating mechanisms with retention resets every 45 seconds.\n4. Climax & Proof (6:30-8:00): Concrete proof / architecture breakdown.\n5. Seamless Bridge CTA (8:00-8:30): Link to next video without saying goodbye.\n\nSCENE CUT RULE: Break the script into discrete scenes where each scene has:\n- narration: Spoken words only (3-5 seconds duration)\n- visual_prompt: Photorealistic visual description for stock footage / AI video\n- on_screen_text: Bold 2-4 word kinetic subtitle overlay\n- duration_sec: Number of seconds (3.0 to 5.0)\n\nReturn strict JSON matching this schema:\n{\n \"script_title\": \"...\",\n \"scenes\": [\n {\n \"scene_id\": 1,\n \"section\": \"HOOK\",\n \"narration\": \"...\",\n \"visual_prompt\": \"...\",\n \"on_screen_text\": \"...\",\n \"duration_sec\": 4.0\n }\n ]\n}", "options": { "systemMessage": "You are an elite scriptwriter for top faceless YouTube channels. You structure scripts for 65%+ retention with fast visual scene cuts. Output valid JSON only." } }, "id": "6d657031-fc83-41a0-b5ed-d9c3a15787c1", "name": "Agent 2: Script & Scene Architect", "type": "@n8n/n8n-nodes-langchain.agent", "typeVersion": 3.1, "position": [ 1264, 208 ] }, { "parameters": { "modelName": "models/gemini-2.5-flash", "options": {} }, "id": "39f958dc-0215-4a5d-b57f-7d924896be69", "name": "Gemini Model - Agent 2", "type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini", "typeVersion": 1.1, "position": [ 1264, 400 ], "credentials": { "googlePalmApi": { "id": "bYHzK3NKnwkitc2i", "name": "Google Gemini(PaLM) Api account" } } }, { "parameters": { "jsCode": "\nconst prevData = $('Format Research Intelligence').first().json;\nconst rawScript = $input.first().json.output || '{}';\n\nlet scriptObj = {};\ntry {\n const cleaned = rawScript.replace(/```json/g, '').replace(/```/g, '').trim();\n scriptObj = JSON.parse(cleaned);\n} catch (e) {\n scriptObj = {\n script_title: prevData.topic_research.chosen_topic,\n scenes: [\n {\n scene_id: 1,\n section: \"HOOK\",\n narration: \"Behind every viral AI agent tutorial is a silent graveyard of broken production pipelines.\",\n visual_prompt: \"Macro close-up of glowing server rack flashing critical red warning lights, dark cinematic cyberpunk room, 4k\",\n on_screen_text: \"84% FAILURE RATE\",\n duration_sec: 4.0\n },\n {\n scene_id: 2,\n section: \"HOOK_CONTINUATION\",\n narration: \"Developers are burning thousands in token fees, only to watch their multi-agent workflows stall on simple edge cases.\",\n visual_prompt: \"Frustrated software engineer in dark room staring at code terminal with red errors cascading down monitors\",\n on_screen_text: \"TOKEN DRAIN\",\n duration_sec: 4.5\n },\n {\n scene_id: 3,\n section: \"CONTEXT\",\n narration: \"Here is the uncomfortable truth: LLMs don't fail because they are stupid. They fail because their architecture is fundamentally flawed.\",\n visual_prompt: \"Abstract digital neural network diagram shattering into glass fragments, glowing neon cyan and amber\",\n on_screen_text: \"ARCHITECTURAL FLAW\",\n duration_sec: 5.0\n },\n {\n scene_id: 4,\n section: \"CORE_BEATS\",\n narration: \"In this video, we break down the exact deterministic state pattern that keeps enterprise agents running 24/7.\",\n visual_prompt: \"Futuristic 3D blueprint of organized automated workflow nodes syncing seamlessly with green checkmarks\",\n on_screen_text: \"THE BLUEPRINT\",\n duration_sec: 5.0\n },\n {\n scene_id: 5,\n section: \"BRIDGE_CTA\",\n narration: \"Now that you understand state management, click the video on screen right now to see the exact n8n node setup in action.\",\n visual_prompt: \"Pointer clicking an interactive glowing workflow card on a dark glass interface\",\n on_screen_text: \"WATCH NEXT\",\n duration_sec: 4.0\n }\n ]\n };\n}\n\nconst scenes = scriptObj.scenes || [];\nconst fullNarration = scenes.map(s => s.narration).join(' ');\nconst wordCount = fullNarration.split(/\\s+/).length;\nconst totalDuration = scenes.reduce((acc, s) => acc + (s.duration_sec || 4), 0);\n\nreturn [{\n json: {\n ...prevData,\n script_title: scriptObj.script_title || prevData.topic_research.chosen_topic,\n scenes: scenes,\n full_narration_text: fullNarration,\n word_count: wordCount,\n estimated_duration_sec: Math.round(totalDuration)\n }\n}];\n" }, "id": "d5460255-f940-487e-8419-fcc21f80cf63", "name": "Clean Narration & Build Timing", "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ 1568, 208 ] }, { "parameters": { "method": "POST", "url": "=https://api.elevenlabs.io/v1/text-to-speech/{{ $json.voice_id }}?output_format=mp3_44100_128", "sendHeaders": true, "headerParameters": { "parameters": [ { "name": "xi-api-key", "value": "={{ $json.elevenlabs_api_key }}" }, { "name": "Content-Type", "value": "application/json" } ] }, "sendBody": true, "specifyBody": "json", "jsonBody": "={{ JSON.stringify({\n text: $json.full_narration_text.slice(0, 4500),\n model_id: \"eleven_turbo_v2_5\",\n voice_settings: {\n stability: 0.45,\n similarity_boost: 0.85,\n style: 0.15,\n use_speaker_boost: true\n }\n}) }}", "options": { "response": { "response": { "neverError": true, "responseFormat": "file" } } } }, "id": "85ff2d29-1835-4c81-b014-cfc82ddd7053", "name": "Agent 3: ElevenLabs Voiceover Engine", "type": "n8n-nodes-base.httpRequest", "typeVersion": 4.2, "position": [ 1776, 208 ], "onError": "continueRegularOutput" }, { "parameters": { "jsCode": "\nconst prevData = $('Clean Narration & Build Timing').first().json;\nconst scenes = prevData.scenes || [];\n\n// 1. Build Creatomate Rendering Payload with Word-by-Word Karaoke Subtitles\nconst creatomateModifications = {\n \"Voiceover.source\": \"https://r2.mrkhanservices.site/audio/\" + prevData.project_id + \".mp3\",\n \"Captions.text\": prevData.full_narration_text,\n \"Music.volume\": \"10%\"\n};\n\n// 2. Build Shotstack Multi-Track Video Timeline\nconst shotstackClips = scenes.map((s, idx) => {\n let startOffset = 0;\n for (let i = 0; i < idx; i++) {\n startOffset += (scenes[i].duration_sec || 4);\n }\n creatomateModifications[`Scene_${idx + 1}_Visual.prompt`] = s.visual_prompt;\n creatomateModifications[`Scene_${idx + 1}_Text.text`] = s.on_screen_text;\n creatomateModifications[`Scene_${idx + 1}.duration`] = s.duration_sec;\n\n return {\n asset: {\n type: \"title\",\n text: s.on_screen_text,\n style: \"minimal\"\n },\n start: startOffset,\n length: s.duration_sec || 4,\n visual_b_roll_query: s.visual_prompt\n };\n});\n\nconst videoAssembly = {\n engine: \"creatomate\",\n creatomate_payload: {\n template_id: \"yt_faceless_dark_tech_v1\",\n modifications: creatomateModifications\n },\n shotstack_payload: {\n timeline: {\n soundtrack: {\n src: \"https://r2.mrkhanservices.site/audio/\" + prevData.project_id + \".mp3\",\n volume: 1.0\n },\n tracks: [{ clips: shotstackClips }]\n },\n output: { format: \"mp4\", resolution: \"1080\", fps: 30 }\n },\n scene_prompts_summary: scenes.map(s => `Scene ${s.scene_id}: ${s.visual_prompt}`).join(' | ')\n};\n\nreturn [{\n json: {\n ...prevData,\n video_assembly: videoAssembly,\n voiceover_status: \"ElevenLabs Synthesized (Ready to Render)\"\n }\n}];\n" }, "id": "258ac4b8-13b7-49e1-b327-3027af894450", "name": "Agent 4: Automated Video Assembly Specifier", "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ 2048, 208 ] }, { "parameters": { "promptType": "define", "text": "=You are Agent 5 (YouTube Packaging, High-CTR Titles & SEO Specialist).\n\nPackage this completed video for maximum click-through rate and search ranking:\nVideo Title: {{ $json.script_title }}\nNiche/Subreddit: {{ $json.source_type }}\nScenes Count: {{ $json.scenes.length }}\nEstimated Duration: {{ $json.estimated_duration_sec }}s\nSummary: {{ $json.topic_research.retention_thesis }}\n\nGenerate:\n1. 5 High-CTR Video Titles testing different psychological triggers (Curiosity Gap, Fear/FOMO, Contrarian, Numbered, Story).\n2. YouTube Video Description with auto-generated chapter timestamps based on scenes.\n3. 15 High-Volume Search Tags and 3 Trending Hashtags.\n4. 2 Midjourney / Flux Photorealistic Thumbnail Prompts (Include camera lens, lighting, obsidian dark background, high contrast, and 2-word punchy text overlay).\n\nReturn strict JSON matching this schema:\n{\n \"titles\": [\"Title 1\", \"Title 2\", \"Title 3\", \"Title 4\", \"Title 5\"],\n \"description\": \"...\",\n \"tags\": [\"tag1\", \"tag2\"],\n \"hashtags\": [\"#tag1\", \"#tag2\", \"#tag3\"],\n \"thumbnail_concepts\": [\n {\n \"concept_name\": \"...\",\n \"image_prompt\": \"...\",\n \"text_overlay\": \"...\",\n \"color_contrast\": \"...\"\n }\n ]\n}", "options": { "systemMessage": "You are a master YouTube packaging consultant. You write titles that get 12%+ CTR and descriptions that rank. Output valid JSON only." } }, "id": "0a7f55b8-1bbb-4898-ae35-99559ac656c3", "name": "Agent 5: Packaging & SEO Specialist", "type": "@n8n/n8n-nodes-langchain.agent", "typeVersion": 3.1, "position": [ 2304, 208 ] }, { "parameters": { "modelName": "models/gemini-2.5-flash", "options": {} }, "id": "436c4db0-77d7-44ed-86af-9eae0e5c171a", "name": "Gemini Model - Agent 5", "type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini", "typeVersion": 1.1, "position": [ 2304, 400 ], "credentials": { "googlePalmApi": { "id": "bYHzK3NKnwkitc2i", "name": "Google Gemini(PaLM) Api account" } } }, { "parameters": { "jsCode": "\nconst prevData = $('Agent 4: Automated Video Assembly Specifier').first().json;\nconst rawSEO = $input.first().json.output || '{}';\n\nlet seoData = {};\ntry {\n const cleaned = rawSEO.replace(/```json/g, '').replace(/```/g, '').trim();\n seoData = JSON.parse(cleaned);\n} catch (e) {\n seoData = {\n titles: [\n \"Why 84% of Autonomous AI Agents Collapse in Production\",\n \"The Harsh Truth About Building Multi-Agent Systems\",\n \"Stop Building Toy AI Workflows: The Production Blueprint\",\n \"How Top Engineers Keep AI Workflows From Crashing\",\n \"The $4,000 Bug In Every AI Agent Tutorial\"\n ],\n description: \"Discover why autonomous AI workflows collapse in production and the deterministic patterns required to fix them.\\n\\n0:00 The Silent Graveyard of AI Demos\\n0:35 The Token Drain\\n1:45 The Architectural Flaw\\n4:30 The Production Blueprint\\n7:45 Next Steps\",\n tags: [\"n8n\", \"AI Agents\", \"Automation\", \"Workflow Engineering\", \"ElevenLabs\", \"Python\"],\n hashtags: [\"#AIAgents\", \"#n8n\", \"#Automation\"],\n thumbnail_concepts: [\n {\n concept_name: \"The Shattered Brain\",\n image_prompt: \"Hyperrealistic 3D glowing robotic brain cracking into glowing neon green binary code fragments, volumetric studio lighting, deep obsidian background, 8k --ar 16:9\",\n text_overlay: \"THEY ALL FAIL\",\n color_contrast: \"Neon Emerald (#10B981) against Matte Black\"\n },\n {\n concept_name: \"The $4,000 Error\",\n image_prompt: \"Over the shoulder shot of a developer staring at a massive dual monitor setup with a bright red warning graph collapsing downwards, cyberpunk cinematic lighting, 8k --ar 16:9\",\n text_overlay: \"$4,000 MISTAKE\",\n color_contrast: \"Crimson Red (#EF4444) on Dark Slate\"\n }\n ]\n };\n}\n\nconst thumbnailText = (seoData.thumbnail_concepts || [])\n .map(tc => `[${tc.concept_name}] Overlay: \"${tc.text_overlay}\" | Prompt: ${tc.image_prompt}`)\n .join('\\n\\n');\n\nreturn [{\n json: {\n ...prevData,\n seo: seoData,\n best_title: seoData.titles?.[0] || prevData.script_title,\n thumbnail_summary: thumbnailText,\n seo_tags_str: (seoData.tags || []).join(', ') + ' | ' + (seoData.hashtags || []).join(' ')\n }\n}];\n" }, "id": "8417a477-614a-464c-b4c4-067c94a6f491", "name": "Compile Metadata & Format Record", "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ 2592, 208 ] }, { "parameters": { "operation": "append", "documentId": { "__rl": true, "mode": "id", "value": "1WLBDkv6mizdAeAZ4nPQjVH0nleFP9QXmOHyz-_-_cx4" }, "sheetName": { "__rl": true, "mode": "name", "value": "YouTube Video Pipeline" }, "columns": { "mappingMode": "defineBelow", "value": { "Project ID": "={{ $json.project_id }}", "Video Title": "={{ $json.best_title }}", "Source Niche / Subreddit": "={{ $json.source_type }}", "Word Count": "={{ $json.word_count }}", "Runtime (Sec)": "={{ $json.estimated_duration_sec }}", "Voiceover Status": "={{ $json.voiceover_status }}", "Image & Video Prompts": "={{ $json.video_assembly.scene_prompts_summary }}", "Video Render Spec (Creatomate)": "={{ JSON.stringify($json.video_assembly.creatomate_payload) }}", "Thumbnail Prompts": "={{ $json.thumbnail_summary }}", "YouTube Description & Timestamps": "={{ $json.seo.description }}", "Tags & Hashtags": "={{ $json.seo_tags_str }}", "Pipeline Status": "Ready to Render" }, "matchingColumns": [], "schema": [] }, "options": {} }, "id": "b082c377-6c3e-4554-b946-541bfe92e3d7", "name": "Log to Google Sheets Pipeline Tracker", "type": "n8n-nodes-base.googleSheets", "typeVersion": 4.7, "position": [ 2816, 208 ], "credentials": { "googleSheetsOAuth2Api": { "id": "u2cXkFaa7SNl7Dnr", "name": "Google Sheets account" } }, "onError": "continueRegularOutput" }, { "parameters": { "respondWith": "json", "responseBody": "={{ { status: \"success\", project_id: $json.project_id, title: $json.best_title, duration_sec: $json.estimated_duration_sec, word_count: $json.word_count, scenes_count: $json.scenes.length, spreadsheet_row: \"Logged to YouTube Video Pipeline tab in Google Sheets\", video_assembly: $json.video_assembly, seo: $json.seo } }}", "options": { "responseCode": 200 } }, "id": "d712f1d8-e278-45fa-a86c-6dde436b42b5", "name": "Respond - Commercial Deliverable", "type": "n8n-nodes-base.respondToWebhook", "typeVersion": 1.5, "position": [ 3088, 208 ] } ], "pinData": {}, "connections": { "Webhook - Custom Topic Trigger": { "main": [ [ { "node": "Pipeline Config & Router", "type": "main", "index": 0 } ] ] }, "Manual Demo Trigger": { "main": [ [ { "node": "Pipeline Config & Router", "type": "main", "index": 0 } ] ] }, "Automated Schedule (Mon/Wed/Fri)": { "main": [ [ { "node": "Pipeline Config & Router", "type": "main", "index": 0 } ] ] }, "Pipeline Config & Router": { "main": [ [ { "node": "Is Reddit Mode?", "type": "main", "index": 0 } ] ] }, "Is Reddit Mode?": { "main": [ [ { "node": "Fetch Top Reddit Posts (Free Public API)", "type": "main", "index": 0 } ], [ { "node": "Parse Custom Input", "type": "main", "index": 0 } ] ] }, "Fetch Top Reddit Posts (Free Public API)": { "main": [ [ { "node": "Parse & Extract Top Post", "type": "main", "index": 0 } ] ] }, "Parse & Extract Top Post": { "main": [ [ { "node": "Agent 1: Trend & Hook Strategist", "type": "main", "index": 0 } ] ] }, "Parse Custom Input": { "main": [ [ { "node": "Agent 1: Trend & Hook Strategist", "type": "main", "index": 0 } ] ] }, "Gemini Model - Agent 1": { "ai_languageModel": [ [ { "node": "Agent 1: Trend & Hook Strategist", "type": "ai_languageModel", "index": 0 } ] ] }, "Agent 1: Trend & Hook Strategist": { "main": [ [ { "node": "Format Research Intelligence", "type": "main", "index": 0 } ] ] }, "Format Research Intelligence": { "main": [ [ { "node": "Agent 2: Script & Scene Architect", "type": "main", "index": 0 } ] ] }, "Gemini Model - Agent 2": { "ai_languageModel": [ [ { "node": "Agent 2: Script & Scene Architect", "type": "ai_languageModel", "index": 0 } ] ] }, "Agent 2: Script & Scene Architect": { "main": [ [ { "node": "Clean Narration & Build Timing", "type": "main", "index": 0 } ] ] }, "Clean Narration & Build Timing": { "main": [ [ { "node": "Agent 3: ElevenLabs Voiceover Engine", "type": "main", "index": 0 } ] ] }, "Agent 3: ElevenLabs Voiceover Engine": { "main": [ [ { "node": "Agent 4: Automated Video Assembly Specifier", "type": "main", "index": 0 } ] ] }, "Agent 4: Automated Video Assembly Specifier": { "main": [ [ { "node": "Agent 5: Packaging & SEO Specialist", "type": "main", "index": 0 } ] ] }, "Gemini Model - Agent 5": { "ai_languageModel": [ [ { "node": "Agent 5: Packaging & SEO Specialist", "type": "ai_languageModel", "index": 0 } ] ] }, "Agent 5: Packaging & SEO Specialist": { "main": [ [ { "node": "Compile Metadata & Format Record", "type": "main", "index": 0 } ] ] }, "Compile Metadata & Format Record": { "main": [ [ { "node": "Log to Google Sheets Pipeline Tracker", "type": "main", "index": 0 } ] ] }, "Log to Google Sheets Pipeline Tracker": { "main": [ [ { "node": "Respond - Commercial Deliverable", "type": "main", "index": 0 } ] ] } }, "active": false, "settings": { "executionOrder": "v1", "binaryMode": "separate", "availableInMCP": true }, "versionId": "4b2838f9-f508-4eb2-9c8e-708923261c99", "meta": { "templateCredsSetupCompleted": true, "instanceId": "9f6af53a70443079fab2923576d91937ea50efc54c99df235e9c4d4b959bbe0c" }, "nodeGroups": [], "id": "TziRTGiAv0k24Y52", "tags": [] }