This workflow follows the Execute Workflow Trigger → HTTP Request recipe pattern — see all workflows that pair these two integrations.
The workflow JSON
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{
"name": "50_543_RESEARCH_DATA",
"nodes": [
{
"id": "543-trigger",
"name": "When Called by Another Workflow",
"type": "n8n-nodes-base.executeWorkflowTrigger",
"typeVersion": 1,
"position": [
250,
400
],
"parameters": {}
},
{
"id": "543-route",
"name": "Route Research Intent",
"type": "n8n-nodes-base.switch",
"typeVersion": 3.2,
"position": [
480,
400
],
"parameters": {
"rules": {
"rules": [
{
"outputKey": "TRENDS",
"conditions": {
"options": {
"caseSensitive": true,
"leftValue": ""
},
"conditions": [
{
"leftValue": "={{ $json.intent }}",
"rightValue": "NOCODB_TRENDS",
"operator": {
"type": "string",
"operation": "equals"
}
}
]
}
},
{
"outputKey": "SENTIMENT",
"conditions": {
"options": {
"caseSensitive": true,
"leftValue": ""
},
"conditions": [
{
"leftValue": "={{ $json.intent }}",
"rightValue": "NOCODB_SENTIMENT",
"operator": {
"type": "string",
"operation": "equals"
}
}
]
}
},
{
"outputKey": "OPPORTUNITIES",
"conditions": {
"options": {
"caseSensitive": true,
"leftValue": ""
},
"conditions": [
{
"leftValue": "={{ $json.intent }}",
"rightValue": "NOCODB_CONTENT",
"operator": {
"type": "string",
"operation": "equals"
}
}
]
}
},
{
"outputKey": "AGENTS",
"conditions": {
"options": {
"caseSensitive": true,
"leftValue": ""
},
"conditions": [
{
"leftValue": "={{ $json.intent }}",
"rightValue": "AGENTS",
"operator": {
"type": "string",
"operation": "equals"
}
}
]
}
},
{
"outputKey": "CONTENT_PIECES",
"conditions": {
"options": {
"caseSensitive": true,
"leftValue": ""
},
"conditions": [
{
"leftValue": "={{ $json.intent }}",
"rightValue": "CONTENT_PIECES",
"operator": {
"type": "string",
"operation": "equals"
}
}
]
}
},
{
"outputKey": "PIPELINE",
"conditions": {
"options": {
"caseSensitive": true,
"leftValue": ""
},
"conditions": [
{
"leftValue": "={{ $json.intent }}",
"rightValue": "PIPELINE",
"operator": {
"type": "string",
"operation": "equals"
}
}
]
}
},
{
"outputKey": "AUDIT",
"conditions": {
"options": {
"caseSensitive": true,
"leftValue": ""
},
"conditions": [
{
"leftValue": "={{ $json.intent }}",
"rightValue": "AUDIT",
"operator": {
"type": "string",
"operation": "equals"
}
}
]
}
}
]
},
"options": {
"fallbackOutput": "extra"
}
}
},
{
"id": "543-fetch-trends",
"name": "Fetch Trends",
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 4.2,
"position": [
760,
80
],
"parameters": {
"method": "GET",
"url": "https://directus.automation-plus-ki.de/items/300_trends",
"authentication": "none",
"sendHeaders": true,
"headerParameters": {
"parameters": [
{
"name": "Authorization",
"value": "Bearer ={{ $env.DIRECTUS_TOKEN }}"
}
]
},
"sendQuery": true,
"queryParameters": {
"parameters": [
{
"name": "limit",
"value": "5"
},
{
"name": "sort",
"value": "-CreatedAt"
}
]
},
"options": {
"timeout": 8000
}
},
"onError": "continueRegularOutput"
},
{
"id": "543-fetch-sentiment",
"name": "Fetch Sentiment",
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 4.2,
"position": [
760,
200
],
"parameters": {
"method": "GET",
"url": "https://directus.automation-plus-ki.de/items/310_sentiment",
"authentication": "none",
"sendHeaders": true,
"headerParameters": {
"parameters": [
{
"name": "Authorization",
"value": "Bearer ={{ $env.DIRECTUS_TOKEN }}"
}
]
},
"sendQuery": true,
"queryParameters": {
"parameters": [
{
"name": "limit",
"value": "5"
},
{
"name": "sort",
"value": "-CreatedAt"
}
]
},
"options": {
"timeout": 8000
}
},
"onError": "continueRegularOutput"
},
{
"id": "543-fetch-opportunities",
"name": "Fetch Opportunities",
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 4.2,
"position": [
760,
320
],
"parameters": {
"method": "GET",
"url": "https://directus.automation-plus-ki.de/items/320_content_opportunities",
"authentication": "none",
"sendHeaders": true,
"headerParameters": {
"parameters": [
{
"name": "Authorization",
"value": "Bearer ={{ $env.DIRECTUS_TOKEN }}"
}
]
},
"sendQuery": true,
"queryParameters": {
"parameters": [
{
"name": "limit",
"value": "5"
},
{
"name": "sort",
"value": "-CreatedAt"
}
]
},
"options": {
"timeout": 8000
}
},
"onError": "continueRegularOutput"
},
{
"id": "543-fetch-agents",
"name": "Fetch Crew Agents",
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 4.2,
"position": [
760,
440
],
"parameters": {
"method": "GET",
"url": "http://s0k444ck0w4cgc400skwkos0.<HETZNER_HOST>.sslip.io/crews/",
"authentication": "none",
"options": {
"timeout": 10000
}
},
"onError": "continueRegularOutput"
},
{
"id": "543-fetch-pieces",
"name": "Fetch Content Pieces",
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 4.2,
"position": [
760,
560
],
"parameters": {
"method": "GET",
"url": "https://directus.automation-plus-ki.de/items/330_knowledge_items",
"authentication": "none",
"sendHeaders": true,
"headerParameters": {
"parameters": [
{
"name": "Authorization",
"value": "Bearer ={{ $env.DIRECTUS_TOKEN }}"
}
]
},
"sendQuery": true,
"queryParameters": {
"parameters": [
{
"name": "limit",
"value": "10"
},
{
"name": "sort",
"value": "-created_at"
}
]
},
"options": {
"timeout": 8000
}
},
"onError": "continueRegularOutput"
},
{
"id": "543-fetch-pipeline",
"name": "Fetch Pipeline Jobs",
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 4.2,
"position": [
760,
680
],
"parameters": {
"method": "GET",
"url": "https://directus.automation-plus-ki.de/items/400_content_pipeline",
"authentication": "none",
"sendHeaders": true,
"headerParameters": {
"parameters": [
{
"name": "Authorization",
"value": "Bearer ={{ $env.DIRECTUS_TOKEN }}"
}
]
},
"sendQuery": true,
"queryParameters": {
"parameters": [
{
"name": "limit",
"value": "10"
},
{
"name": "sort",
"value": "-created_at"
}
]
},
"options": {
"timeout": 8000
}
},
"onError": "continueRegularOutput"
},
{
"id": "543-fetch-audit",
"name": "Fetch Audit Trail",
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 4.2,
"position": [
760,
800
],
"parameters": {
"method": "GET",
"url": "https://directus.automation-plus-ki.de/items/audit_log",
"authentication": "none",
"sendHeaders": true,
"headerParameters": {
"parameters": [
{
"name": "Authorization",
"value": "Bearer ={{ $env.DIRECTUS_TOKEN }}"
}
]
},
"sendQuery": true,
"queryParameters": {
"parameters": [
{
"name": "limit",
"value": "10"
},
{
"name": "sort",
"value": "-ts"
}
]
},
"options": {
"timeout": 8000
}
},
"onError": "continueRegularOutput"
},
{
"id": "543-fmt-trends",
"name": "Format Trends",
"type": "n8n-nodes-base.code",
"typeVersion": 2,
"position": [
1040,
80
],
"parameters": {
"jsCode": "const chatId = $('When Called by Another Workflow').first().json.chatId;\nconst data = $input.first().json;\nconst rows = data?.data ?? [];\n\nif (rows.length === 0) {\n return [{ json: { chatId, response: '*Trends:* Noch keine Daten.\\n\\nWorkflow `30_310_TREND_MONITOR` l\u00e4uft t\u00e4gl. 08:00.' } }];\n}\n\nconst lines = rows.map((r, i) => {\n const title = r.Title ?? r.title ?? r.Trend ?? r.trend ?? 'Unbekannt';\n const score = r.Score ?? r.score ?? r.Engagement ?? '-';\n const date = r.CreatedAt ? new Date(r.CreatedAt).toLocaleDateString('de-DE') : '';\n return `${i + 1}. *${title}*\\nScore: ${score} | ${date}`;\n});\n\nreturn [{ json: { chatId, response: `*Aktuelle Trends* (letzte ${rows.length}):\\n\\n${lines.join('\\n\\n')}` } }];"
}
},
{
"id": "543-fmt-sentiment",
"name": "Format Sentiment",
"type": "n8n-nodes-base.code",
"typeVersion": 2,
"position": [
1040,
200
],
"parameters": {
"jsCode": "const chatId = $('When Called by Another Workflow').first().json.chatId;\nconst data = $input.first().json;\nconst rows = data?.data ?? [];\n\nif (rows.length === 0) {\n return [{ json: { chatId, response: '*Sentiment:* Noch keine Daten.\\n\\nWorkflow `30_320_SENTIMENT_TRACKER` l\u00e4uft Mo. 08:00.' } }];\n}\n\nconst emo = { positive: '\ud83d\udfe2', neutral: '\ud83d\udfe1', negative: '\ud83d\udd34' };\nconst lines = rows.map((r, i) => {\n const topic = r.Topic ?? r.topic ?? r.Trend ?? 'Unbekannt';\n const s = (r.Sentiment ?? r.sentiment ?? 'neutral').toLowerCase();\n const score = r.Score ?? r.score ?? '-';\n const date = r.CreatedAt ? new Date(r.CreatedAt).toLocaleDateString('de-DE') : '';\n return `${i + 1}. ${emo[s] ?? '\u26aa'} *${topic}*\\n${s} | Score: ${score} | ${date}`;\n});\n\nreturn [{ json: { chatId, response: `*Sentiment-Analyse* (letzte ${rows.length}):\\n\\n${lines.join('\\n\\n')}` } }];"
}
},
{
"id": "543-fmt-opportunities",
"name": "Format Opportunities",
"type": "n8n-nodes-base.code",
"typeVersion": 2,
"position": [
1040,
320
],
"parameters": {
"jsCode": "const chatId = $('When Called by Another Workflow').first().json.chatId;\nconst data = $input.first().json;\nconst rows = data?.data ?? [];\n\nif (rows.length === 0) {\n return [{ json: { chatId, response: '*Content Opportunities:* Noch keine Daten.\\n\\nWorkflow `30_330_CONTENT_OPPORTUNITY` l\u00e4uft t\u00e4gl. 09:30.' } }];\n}\n\nconst prio = { high: '\ud83d\udd25', medium: '\ud83d\udccb', low: '\ud83d\udca1' };\nconst lines = rows.map((r, i) => {\n const title = r.Title ?? r.title ?? r.Opportunity ?? 'Unbekannt';\n const p = (r.Priority ?? r.priority ?? 'medium').toLowerCase();\n const fmt = r.Format ?? r.format ?? r.Type ?? '';\n const date = r.CreatedAt ? new Date(r.CreatedAt).toLocaleDateString('de-DE') : '';\n return `${i + 1}. ${prio[p] ?? '\ud83d\udccb'} *${title}*\\n${p}${fmt ? ' | ' + fmt : ''} | ${date}`;\n});\n\nreturn [{ json: { chatId, response: `*Content Opportunities* (letzte ${rows.length}):\\n\\n${lines.join('\\n\\n')}` } }];"
}
},
{
"id": "543-fmt-agents",
"name": "Format Agents",
"type": "n8n-nodes-base.code",
"typeVersion": 2,
"position": [
1040,
440
],
"parameters": {
"jsCode": "const chatId = $('When Called by Another Workflow').first().json.chatId;\nconst data = $input.first().json;\nconst crews = Array.isArray(data) ? data : [];\n\nif (crews.length === 0) {\n return [{ json: { chatId, response: '\u274c Crew API nicht erreichbar.' } }];\n}\n\nconst totalAgents = crews.reduce((s, c) => s + (c.agents ?? 0), 0);\n\nconst lines = crews.map(c => {\n const lastRun = c.last_run\n ? (() => {\n const diff = Date.now() - new Date(c.last_run).getTime();\n const m = Math.floor(diff / 60000);\n if (m < 1) return 'gerade eben';\n if (m < 60) return `vor ${m}m`;\n const h = Math.floor(m / 60);\n if (h < 24) return `vor ${h}h`;\n return `vor ${Math.floor(h / 24)}d`;\n })()\n : 'noch nie';\n const pieces = c.recent_pieces?.length ?? 0;\n return `\u2022 *${c.name}* \u2014 ${c.agents} Agents | ${lastRun}${pieces > 0 ? ` | ${pieces} Outputs` : ''}`;\n});\n\nreturn [{ json: { chatId, response: `*Crew AI Agent Teams* (${crews.length} Crews, ${totalAgents} Agents):\\n\\n${lines.join('\\n')}` } }];"
}
},
{
"id": "543-fmt-pieces",
"name": "Format Content Pieces",
"type": "n8n-nodes-base.code",
"typeVersion": 2,
"position": [
1040,
560
],
"parameters": {
"jsCode": "const chatId = $('When Called by Another Workflow').first().json.chatId;\nconst data = $input.first().json;\nconst rows = data?.data ?? [];\n\nif (rows.length === 0) {\n return [{ json: { chatId, response: '*Content Pieces:* Noch keine Daten.\\n\\nStarte mit: `starte Content Master Flow`' } }];\n}\n\nconst statusEmo = { draft: '\u270f\ufe0f', review: '\ud83d\udd0d', approved: '\u2705', published: '\ud83d\ude80', archived: '\ud83d\udce6' };\nconst lines = rows.map((r, i) => {\n const title = r.title ?? r.Title ?? r.piece_id ?? 'Unbekannt';\n const status = (r.status ?? 'draft').toLowerCase();\n const cat = r.category ?? '';\n const date = r.created_at ?? r.CreatedAt ?? '';\n const dateStr = date ? new Date(date).toLocaleDateString('de-DE') : '';\n return `${i + 1}. ${statusEmo[status] ?? '\ud83d\udcc4'} *${title}*\\n${status}${cat ? ' | ' + cat : ''}${dateStr ? ' | ' + dateStr : ''}`;\n});\n\nconst draftN = rows.filter(r => r.status === 'draft').length;\nconst pubN = rows.filter(r => r.status === 'published').length;\n\nreturn [{ json: { chatId, response: `*Content Pieces* (${rows.length} gesamt \u2014 ${draftN} Draft, ${pubN} Published):\\n\\n${lines.join('\\n\\n')}` } }];"
}
},
{
"id": "543-fmt-pipeline",
"name": "Format Pipeline",
"type": "n8n-nodes-base.code",
"typeVersion": 2,
"position": [
1040,
680
],
"parameters": {
"jsCode": "const chatId = $('When Called by Another Workflow').first().json.chatId;\nconst data = $input.first().json;\nconst rows = data?.data ?? [];\n\nif (rows.length === 0) {\n return [{ json: { chatId, response: '*Pipeline:* Keine Jobs vorhanden.\\n\\nStarte mit: `starte Content Master Flow`' } }];\n}\n\nconst stageEmo = { text: '\ud83d\udcdd', image: '\ud83d\uddbc\ufe0f', voice: '\ud83c\udf99\ufe0f', publish: '\ud83d\ude80' };\nconst statusEmo = { running: '\u26a1', done: '\u2705', failed: '\u274c', pending: '\u23f3' };\n\nconst lines = rows.map((r, i) => {\n const jobId = r.job_id ?? r.Id ?? i + 1;\n const topic = r.topic ?? r.Topic ?? 'Unbekannt';\n const stage = (r.stage ?? r.Stage ?? 'text').toLowerCase();\n const status = (r.status ?? r.Status ?? 'pending').toLowerCase();\n const date = r.created_at ?? r.CreatedAt ?? '';\n const dateStr = date ? new Date(date).toLocaleDateString('de-DE') : '';\n return `${i + 1}. ${statusEmo[status] ?? '\u23f3'} *${topic}*\\n${stageEmo[stage] ?? '\ud83d\udccb'} ${stage} | ${status}${dateStr ? ' | ' + dateStr : ''}`;\n});\n\nreturn [{ json: { chatId, response: `*Content Pipeline* (letzte ${rows.length} Jobs):\\n\\n${lines.join('\\n\\n')}` } }];"
}
},
{
"id": "543-fmt-audit",
"name": "Format Audit",
"type": "n8n-nodes-base.code",
"typeVersion": 2,
"position": [
1040,
800
],
"parameters": {
"jsCode": "const chatId = $('When Called by Another Workflow').first().json.chatId;\nconst data = $input.first().json;\nconst rows = data?.data ?? [];\n\nif (rows.length === 0) {\n return [{ json: { chatId, response: '*Audit Trail:* Noch keine Eintr\u00e4ge.\\n\\nEintr\u00e4ge entstehen automatisch bei Workflow-Ausf\u00fchrungen.' } }];\n}\n\nconst resultEmo = { ok: '\u2705', error: '\u274c', blocked: '\ud83d\udeab' };\n\nconst lines = rows.map((r, i) => {\n const actor = r.actor ?? r.Actor ?? 'system';\n const action = r.action ?? r.Action ?? '-';\n const resource = r.resource_type ?? r.resource_id ?? '-';\n const result = (r.result ?? 'ok').toLowerCase();\n const ts = r.ts ?? r.Ts ?? r.CreatedAt ?? '';\n const tsStr = ts ? new Date(ts).toLocaleString('de-DE', { timeZone: 'Europe/Berlin', hour: '2-digit', minute: '2-digit', day: '2-digit', month: '2-digit' }) : '';\n return `${i + 1}. ${resultEmo[result] ?? '\u2705'} *${action}*\\n${actor} \u2192 ${resource}${tsStr ? ' | ' + tsStr : ''}`;\n});\n\nreturn [{ json: { chatId, response: `*Audit Trail* (letzte ${rows.length} Aktionen):\\n\\n${lines.join('\\n\\n')}` } }];"
}
},
{
"id": "543-fallback",
"name": "Fallback Response",
"type": "n8n-nodes-base.set",
"typeVersion": 3.4,
"position": [
1040,
920
],
"parameters": {
"assignments": {
"assignments": [
{
"id": "f1",
"name": "chatId",
"value": "={{ $('When Called by Another Workflow').first().json.chatId }}",
"type": "string"
},
{
"id": "f2",
"name": "response",
"value": "\u2753 Unbekannte Research-Abfrage. Verf\u00fcgbar: `trends`, `sentiment`, `chancen`, `agents`, `content`, `pipeline`, `audit`",
"type": "string"
}
]
}
}
}
],
"connections": {
"When Called by Another Workflow": {
"main": [
[
{
"node": "Route Research Intent",
"type": "main",
"index": 0
}
]
]
},
"Route Research Intent": {
"main": [
[
{
"node": "Fetch Trends",
"type": "main",
"index": 0
}
],
[
{
"node": "Fetch Sentiment",
"type": "main",
"index": 0
}
],
[
{
"node": "Fetch Opportunities",
"type": "main",
"index": 0
}
],
[
{
"node": "Fetch Crew Agents",
"type": "main",
"index": 0
}
],
[
{
"node": "Fetch Content Pieces",
"type": "main",
"index": 0
}
],
[
{
"node": "Fetch Pipeline Jobs",
"type": "main",
"index": 0
}
],
[
{
"node": "Fetch Audit Trail",
"type": "main",
"index": 0
}
],
[
{
"node": "Fallback Response",
"type": "main",
"index": 0
}
]
]
},
"Fetch Trends": {
"main": [
[
{
"node": "Format Trends",
"type": "main",
"index": 0
}
]
]
},
"Fetch Sentiment": {
"main": [
[
{
"node": "Format Sentiment",
"type": "main",
"index": 0
}
]
]
},
"Fetch Opportunities": {
"main": [
[
{
"node": "Format Opportunities",
"type": "main",
"index": 0
}
]
]
},
"Fetch Crew Agents": {
"main": [
[
{
"node": "Format Agents",
"type": "main",
"index": 0
}
]
]
},
"Fetch Content Pieces": {
"main": [
[
{
"node": "Format Content Pieces",
"type": "main",
"index": 0
}
]
]
},
"Fetch Pipeline Jobs": {
"main": [
[
{
"node": "Format Pipeline",
"type": "main",
"index": 0
}
]
]
},
"Fetch Audit Trail": {
"main": [
[
{
"node": "Format Audit",
"type": "main",
"index": 0
}
]
]
}
},
"settings": {
"executionOrder": "v1",
"saveDataErrorExecution": "all",
"saveDataSuccessExecution": "none"
},
"staticData": null,
"tags": [
"telegram",
"research"
],
"meta": {
"description": "543 \u2014 Sub-Workflow: Research & Operations Daten f\u00fcr Telegram (Trends, Sentiment, Opportunities, Agents, Content Pieces, Pipeline, Audit)"
}
}
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About this workflow
50_543_RESEARCH_DATA. Uses executeWorkflowTrigger, httpRequest. Event-driven trigger; 17 nodes.
Source: https://github.com/timo-goetz-ai/apki-core-platform/blob/5cd9c9d9ed0ed464da995af94683e9301965a3bc/automations/n8n-workflows/telegram/50_543_RESEARCH_DATA.json — original creator credit. Request a take-down →
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