This workflow follows the Form → Form Trigger 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": "TikTok Visual Hook Splitter",
"nodes": [
{
"parameters": {
"content": "## TikTok Visual Hook Splitter\n\n### How it works\n\n1. Form collects a TikTok URL.\n2. RenderIO downloads it via yt-dlp and runs an FFmpeg pass that stream-copies the source and writes scene-cut timestamps to `scenes.txt`.\n3. A Code node fetches `scenes.txt` and extracts the first scene cut between 1 s and 6 s.\n4. An HTTP Request POSTs to RenderIO `run-ffmpeg-command` with a dynamic `-t <hookEndSec>` so the source is trimmed at exactly the detected reaction-to-demo cut.\n5. Form completion returns the hook MP4 link.\n\n### Why a mix of RenderIO node + HTTP Request\n\nThe Split Visual Hook step needs the trim time substituted at runtime. The renderio community node currently marks `ffmpegCommand` as `noDataExpression: true` so `{{ $json.hookEndSec }}` is not evaluated. The `httpRequest.jsonBody` field DOES evaluate it, so the split step uses HTTP Request with the same `renderioApi` credential.\n\nRenderIO placeholders use the new `<<alias>>` syntax so they no longer collide with n8n's `{{ }}` expression syntax.\n\n### Setup steps\n\n- [ ] Add a RenderIO API credential (used by all four RenderIO calls).\n- [ ] Submit a TikTok URL.\n\n### Customization\n\nTweak the scene threshold (`0.3`) in **Download And Detect Scenes** for tighter or looser cut detection, or change `[minS, maxS]` in **Parse First Scene Cut** for different hook-length policies.",
"height": 720,
"width": 480
},
"id": "37199307-c5a6-4a81-aa92-d13d38ccb14c",
"name": "Sticky Note 525df699",
"type": "n8n-nodes-base.stickyNote",
"typeVersion": 1,
"position": [
-432,
-672
]
},
{
"parameters": {
"content": "## Input & download\n\nForm submission triggers RenderIO download + scene detection in one FFmpeg pass.",
"height": 320,
"width": 512,
"color": 7
},
"id": "9e9a3467-0354-45b9-9bf4-6da6362ce041",
"name": "Sticky Note eb0fabe5",
"type": "n8n-nodes-base.stickyNote",
"typeVersion": 1,
"position": [
48,
160
]
},
{
"parameters": {
"content": "## Detection polling\n\nWait \u2192 `command.get` \u2192 If terminal status. Loops back via the retry sticky below on QUEUED / PROCESSING / RUNNING.",
"height": 320,
"width": 640,
"color": 7
},
"id": "48b2c829-170b-46f6-af21-d9e7a24d3f0c",
"name": "Sticky Note 6ae76f29",
"type": "n8n-nodes-base.stickyNote",
"typeVersion": 1,
"position": [
592,
160
]
},
{
"parameters": {
"content": "## Detection retry\n\nWait 10 s then re-check.",
"height": 284,
"width": 256,
"color": 7
},
"id": "c2a8c039-24ed-4d1b-8874-ade0c799c78c",
"name": "Sticky Note c92d1141",
"type": "n8n-nodes-base.stickyNote",
"typeVersion": 1,
"position": [
1008,
512
]
},
{
"parameters": {
"content": "## Parse + dynamic trim\n\nCode node parses `scenes.txt` for the first `pts_time`; HTTP Request POSTs the trim with `-t {{ $json.hookEndSec }}` evaluated at runtime.",
"height": 304,
"width": 416,
"color": 7
},
"id": "40ad1ce3-685b-48f8-853a-ad9e9bd88ba9",
"name": "Sticky Note 0ee79fa7",
"type": "n8n-nodes-base.stickyNote",
"typeVersion": 1,
"position": [
1248,
80
]
},
{
"parameters": {
"content": "## Split polling\n\nWait \u2192 `command.get` \u2192 If terminal status, mirrors the detection loop.",
"height": 304,
"width": 640,
"color": 7
},
"id": "8e46359c-d8ff-4562-9b2d-5502a391aa6e",
"name": "Sticky Note ab3ae771",
"type": "n8n-nodes-base.stickyNote",
"typeVersion": 1,
"position": [
1680,
80
]
},
{
"parameters": {
"content": "## Split retry\n\nWait 10 s then re-check.",
"height": 284,
"width": 272,
"color": 7
},
"id": "ad981519-3d95-4981-b7ca-508711393aa9",
"name": "Sticky Note 5025a6f6",
"type": "n8n-nodes-base.stickyNote",
"typeVersion": 1,
"position": [
2112,
400
]
},
{
"parameters": {
"content": "## Deliver\n\nForm completion returns the hook MP4 link.",
"height": 304,
"width": 280,
"color": 7
},
"id": "0ee3b056-2c83-41c3-a3f7-067d1aa8a3b8",
"name": "Sticky Note 51d4164d",
"type": "n8n-nodes-base.stickyNote",
"typeVersion": 1,
"position": [
2352,
0
]
},
{
"parameters": {
"formTitle": "TikTok Visual Hook Splitter",
"formDescription": "Paste a TikTok URL where the first 1-6 seconds are a reaction shot (smile, cry, gasp) and the rest is an app/product demo. The workflow auto-detects the reaction-to-demo cut with FFmpeg, then trims the source at that exact time. Ready to feed into Kling motion control with your AI avatar to mass-produce on-brand UGC reactions.",
"formFields": {
"values": [
{
"fieldLabel": "TikTok URL",
"placeholder": "https://www.tiktok.com/@user/video/...",
"requiredField": true
}
]
},
"responseMode": "lastNode",
"options": {
"buttonLabel": "Extract Visual Hook"
}
},
"id": "dca3e6e0-1922-44f7-afbb-9dfb4ff09d6d",
"name": "When TikTok URL Submitted",
"type": "n8n-nodes-base.formTrigger",
"typeVersion": 2.3,
"position": [
96,
304
],
"executeOnce": true
},
{
"parameters": {
"operation": "downloadAndProcessMedia",
"ffmpegCommand": "-i <<in_video>> -c copy -map 0 <<out_video>> -vf \"select='gt(scene,0.3)',metadata=print:file=<<out_scenes>>\" -an -f null -",
"mediaUrls": {
"urlValues": [
{
"key": "in_video",
"value": "={{ $json[\"TikTok URL\"] }}"
}
]
},
"outputFiles": {
"fileValues": [
{
"value": "source.mp4"
},
{
"key": "out_scenes",
"value": "scenes.txt"
}
]
}
},
"id": "b5765337-3e59-4691-b46b-cb863e9577f6",
"name": "Download And Detect Scenes",
"type": "n8n-nodes-renderio.renderio",
"typeVersion": 1,
"position": [
384,
288
],
"credentials": {
"renderioApi": {
"name": "<your credential>"
}
}
},
{
"parameters": {},
"id": "d0ded013-7cfb-406e-98fe-795914ef10e8",
"name": "Wait 5s for Detection",
"type": "n8n-nodes-base.wait",
"typeVersion": 1.1,
"position": [
640,
304
]
},
{
"parameters": {
"operation": "get",
"commandId": "={{ $('Download And Detect Scenes').item.json.command_id }}"
},
"id": "55fcfb03-3972-43f8-bb36-58e839aea22f",
"name": "Check Detection Status",
"type": "n8n-nodes-renderio.renderio",
"typeVersion": 1,
"position": [
864,
304
],
"credentials": {
"renderioApi": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"conditions": [
{
"id": "d1",
"leftValue": "={{ $json.status }}",
"rightValue": "PROCESSING",
"operator": {
"type": "string",
"operation": "notEquals"
}
},
{
"id": "d2",
"leftValue": "={{ $json.status }}",
"rightValue": "QUEUED",
"operator": {
"type": "string",
"operation": "notEquals"
}
},
{
"id": "d3",
"leftValue": "={{ $json.status }}",
"rightValue": "RUNNING",
"operator": {
"type": "string",
"operation": "notEquals"
}
}
],
"combinator": "and"
},
"options": {}
},
"id": "c1ef7063-6235-4b13-aa4f-6bbcf8908943",
"name": "If Detection Done",
"type": "n8n-nodes-base.if",
"typeVersion": 2.3,
"position": [
1072,
304
]
},
{
"parameters": {
"mode": "runOnceForEachItem",
"jsCode": "const scenesUrl = $input.item.json.output_files.out_scenes.storage_url;\nconst sourceVideoUrl = $input.item.json.output_files.out_video.storage_url;\nconst raw = await this.helpers.httpRequest({ method: 'GET', url: scenesUrl, returnFullResponse: false });\nconst text = typeof raw === 'string' ? raw : JSON.stringify(raw);\nconst minS = 1;\nconst maxS = 6;\nconst times = [];\nconst re = /pts_time:([0-9]+\\.?[0-9]*)/g;\nlet m;\nwhile ((m = re.exec(text)) !== null) times.push(parseFloat(m[1]));\nlet hookEnd, reason;\nif (times.length === 0) { hookEnd = maxS; reason = 'no_scene_cut_fallback_to_max'; }\nelse {\n const first = times[0];\n if (first < minS) {\n const next = times.find(t => t >= minS);\n hookEnd = next != null ? Math.min(next, maxS) : maxS;\n reason = next != null ? 'first_cut_too_early_used_next' : 'first_cut_too_early_used_max';\n } else {\n hookEnd = Math.min(first, maxS);\n reason = first <= maxS ? 'first_scene_cut' : 'first_cut_above_max_capped';\n }\n}\nconst hookEndSec = Math.round(hookEnd * 1000) / 1000;\nreturn { json: { hookEndSec, allSceneCuts: times, reason, sourceVideoUrl } };"
},
"id": "f7e1fee5-9c16-42ef-b6f5-84acbf2f3865",
"name": "Parse First Scene Cut",
"type": "n8n-nodes-base.code",
"typeVersion": 2,
"position": [
1296,
224
]
},
{
"parameters": {
"method": "POST",
"url": "https://renderio.dev/api/v1/run-ffmpeg-command",
"authentication": "predefinedCredentialType",
"nodeCredentialType": "renderioApi",
"sendBody": true,
"specifyBody": "json",
"jsonBody": "={{ JSON.stringify({ input_files: { in_video: $json.sourceVideoUrl }, output_files: { out_hook: 'visual_hook.mp4' }, ffmpeg_command: '-i <<in_video>> -t ' + $json.hookEndSec + ' -c:v libx264 -preset veryfast -crf 20 -c:a aac -b:a 128k -movflags +faststart <<out_hook>>' }) }}",
"options": {}
},
"id": "229064ab-ce46-4048-9041-4d89fccc9559",
"name": "Split Visual Hook",
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 4.4,
"position": [
1504,
224
],
"credentials": {
"renderioApi": {
"name": "<your credential>"
}
}
},
{
"parameters": {},
"id": "870ce5b9-edf9-4e3f-bd18-f39bb85bbbb8",
"name": "Wait 5s for Split",
"type": "n8n-nodes-base.wait",
"typeVersion": 1.1,
"position": [
1728,
224
]
},
{
"parameters": {
"operation": "get",
"commandId": "={{ $('Split Visual Hook').item.json.command_id }}"
},
"id": "ad3e426d-4021-4634-89c6-c0510ca547af",
"name": "Check Split Status",
"type": "n8n-nodes-renderio.renderio",
"typeVersion": 1,
"position": [
1952,
224
],
"credentials": {
"renderioApi": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"conditions": [
{
"id": "s1",
"leftValue": "={{ $json.status }}",
"rightValue": "PROCESSING",
"operator": {
"type": "string",
"operation": "notEquals"
}
},
{
"id": "s2",
"leftValue": "={{ $json.status }}",
"rightValue": "QUEUED",
"operator": {
"type": "string",
"operation": "notEquals"
}
},
{
"id": "s3",
"leftValue": "={{ $json.status }}",
"rightValue": "RUNNING",
"operator": {
"type": "string",
"operation": "notEquals"
}
}
],
"combinator": "and"
},
"options": {}
},
"id": "d8df58be-a759-4d45-b14c-dceb2e6145c4",
"name": "If Split Done",
"type": "n8n-nodes-base.if",
"typeVersion": 2.3,
"position": [
2176,
224
]
},
{
"parameters": {
"operation": "completion",
"completionTitle": "Visual hook extracted",
"completionMessage": "=Status: **{{ $json.status }}**\n\nHook end time: **{{ $('Parse First Scene Cut').item.json.hookEndSec }}s** (detection: {{ $('Parse First Scene Cut').item.json.reason }})\n\nAll scene cuts detected: {{ JSON.stringify($('Parse First Scene Cut').item.json.allSceneCuts) }}\n\n[Download visual hook MP4]({{ $json.output_files.out_hook.storage_url }})\n\nFeed this clip into RenderIO + Kling motion control with your AI avatar to mass-produce on-brand UGC reactions.",
"options": {}
},
"id": "3c5e1c7d-c071-4170-bf4d-972e30d6f439",
"name": "Display Hook Download",
"type": "n8n-nodes-base.form",
"typeVersion": 2.3,
"position": [
2448,
144
]
},
{
"parameters": {
"amount": 10
},
"id": "c672827f-a002-4960-b992-f9a6bd3f2963",
"name": "Wait 10s Retry Split",
"type": "n8n-nodes-base.wait",
"typeVersion": 1.1,
"position": [
2208,
512
]
},
{
"parameters": {
"amount": 10
},
"id": "7166de8e-d3b6-41e9-bbd6-74b3470880b9",
"name": "Wait 10s Retry Detect",
"type": "n8n-nodes-base.wait",
"typeVersion": 1.1,
"position": [
1088,
640
]
}
],
"connections": {
"When TikTok URL Submitted": {
"main": [
[
{
"node": "Download And Detect Scenes",
"type": "main",
"index": 0
}
]
]
},
"Download And Detect Scenes": {
"main": [
[
{
"node": "Wait 5s for Detection",
"type": "main",
"index": 0
}
]
]
},
"Wait 5s for Detection": {
"main": [
[
{
"node": "Check Detection Status",
"type": "main",
"index": 0
}
]
]
},
"Check Detection Status": {
"main": [
[
{
"node": "If Detection Done",
"type": "main",
"index": 0
}
]
]
},
"If Detection Done": {
"main": [
[
{
"node": "Parse First Scene Cut",
"type": "main",
"index": 0
}
],
[
{
"node": "Wait 10s Retry Detect",
"type": "main",
"index": 0
}
]
]
},
"Parse First Scene Cut": {
"main": [
[
{
"node": "Split Visual Hook",
"type": "main",
"index": 0
}
]
]
},
"Split Visual Hook": {
"main": [
[
{
"node": "Wait 5s for Split",
"type": "main",
"index": 0
}
]
]
},
"Wait 5s for Split": {
"main": [
[
{
"node": "Check Split Status",
"type": "main",
"index": 0
}
]
]
},
"Check Split Status": {
"main": [
[
{
"node": "If Split Done",
"type": "main",
"index": 0
}
]
]
},
"If Split Done": {
"main": [
[
{
"node": "Display Hook Download",
"type": "main",
"index": 0
}
],
[
{
"node": "Wait 10s Retry Split",
"type": "main",
"index": 0
}
]
]
},
"Wait 10s Retry Split": {
"main": [
[
{
"node": "Check Split Status",
"type": "main",
"index": 0
}
]
]
},
"Wait 10s Retry Detect": {
"main": [
[
{
"node": "Check Detection Status",
"type": "main",
"index": 0
}
]
]
}
},
"active": true,
"settings": {
"executionOrder": "v1",
"binaryMode": "separate",
"availableInMCP": true
},
"versionId": "d8884f0c-fcd0-49e6-8106-c24541033fe6",
"meta": {
"aiBuilderAssisted": true
},
"id": "RVIrQymPm5XFQCtG",
"tags": []
}
Credentials you'll need
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renderioApi
Pro
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About this workflow
TikTok Visual Hook Splitter. Uses formTrigger, n8n-nodes-renderio, httpRequest, form. Event-driven trigger; 21 nodes.
Source: https://github.com/RenderIO/workflows/blob/main/workflows/tiktok-visual-hook-splitter.json — original creator credit. Request a take-down →
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