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": "Lead Qualification Agent",
"nodes": [
{
"parameters": {},
"id": "a318f4ea-5255-4822-aef3-e48c61361448",
"name": "Manual Trigger",
"type": "n8n-nodes-base.manualTrigger",
"typeVersion": 1,
"position": [
220,
320
]
},
{
"parameters": {
"keepOnlySet": true,
"values": {
"string": [
{
"name": "agent_slug",
"value": "lead-qualification-agent"
},
{
"name": "agent_title",
"value": "Lead Qualification Agent"
},
{
"name": "agent_description",
"value": "Qualifiziert neue Leads, bewertet Kaufwahrscheinlichkeit und priorisiert CRM-Follow-ups."
},
{
"name": "system_prompt",
"value": "Du bist ein hochspezialisierter Business-Agent. Arbeite pr\u00e4zise, strukturiert, umsetzungsorientiert und ohne Halluzinationen. Nutze ausschlie\u00dflich die bereitgestellten Eingaben. Wenn Daten fehlen oder unsicher sind, markiere sie explizit als offen. Antworte standardm\u00e4\u00dfig auf Deutsch, au\u00dfer die Eingabe verlangt etwas anderes. Liefere Ergebnisse so, dass ein Team sie direkt weiterverwenden kann.\n\nRolle: Lead Qualification Agent. Aufgabe: Qualifiziert neue Leads, bewertet Kaufwahrscheinlichkeit und priorisiert CRM-Follow-ups. Arbeite immer in diesem Output-Rahmen: ICP Fit Score (0-100), Lead Temperature, Priority, Why this lead matters, Risks / Missing data, Next best action, CRM summary."
},
{
"name": "task",
"value": "Analysiere den neuen Inbound-Lead und bewerte Abschlusschance, Fit und Dringlichkeit."
},
{
"name": "goal",
"value": "Eine klare Priorisierung f\u00fcr Vertrieb und CRM erzeugen."
},
{
"name": "context",
"value": "B2B KI-Agentur in DACH. Fokus auf Unternehmen mit Bedarf an Automatisierung, AI Agents oder Prozessdigitalisierung."
},
{
"name": "input_data",
"value": "{\n \"lead_name\": \"Anna Huber\",\n \"company\": \"Huber Logistics GmbH\",\n \"industry\": \"Logistik\",\n \"employees\": 85,\n \"country\": \"Austria\",\n \"website\": \"https://example-logistics.at\",\n \"source\": \"Website Anfrage\",\n \"budget_signal\": \"10k-25k EUR\",\n \"pain_points\": [\n \"zu viele manuelle Supportanfragen\",\n \"keine AI-gest\u00fctzte Lead-Vorqualifizierung\",\n \"hoher Aufwand im Backoffice\"\n ],\n \"requested_solution\": \"AI Kundenservice Agent + CRM Automatisierung\",\n \"timeline\": \"innerhalb von 30 Tagen\",\n \"decision_maker\": \"COO\",\n \"email_quality\": \"business email\",\n \"intent_signals\": [\n \"konkrete Anfrage\",\n \"klarer Use Case\",\n \"Budget-Hinweis vorhanden\"\n ]\n}"
},
{
"name": "output_format",
"value": "Markdown mit klaren \u00dcberschriften und Bulletpoints"
},
{
"name": "output_schema",
"value": "\n- ICP Fit Score (0-100)\n- Lead Temperature\n- Priority\n- Why this lead matters\n- Risks / Missing data\n- Next best action\n- CRM summary"
},
{
"name": "extra_rules",
"value": "Bewerte streng. Erfinde keine Firmendaten. Gib konkrete Sales-Empfehlungen in Deutsch."
},
{
"name": "sample_customer_value",
"value": "Dieser Agent bewertet neue Leads und erzeugt eine CRM-fertige Priorisierung."
}
]
}
},
"id": "889d329e-13c2-46b5-9e52-f16f01110861",
"name": "Set Agent Input",
"type": "n8n-nodes-base.set",
"typeVersion": 3.4,
"position": [
480,
320
]
},
{
"parameters": {
"jsCode": "const user_message = `Aufgabe: ${$json.task}\n\nZiel: ${$json.goal}\n\nKontext: ${$json.context}\n\nEingabedaten (JSON oder Text):\n${$json.input_data}\n\nErwartete Ausgabebausteine:\n${$json.output_schema}\n\nZusatzregeln:\n${$json.extra_rules}`;\n\nreturn [{\n json: {\n ...$json,\n user_message,\n import_note: 'Nach dem Import nur OPENAI_API_KEY bzw. HTTP Credential und optional OPENAI_MODEL anpassen.'\n }\n}];"
},
"id": "2076e137-cf0d-4ae5-bca8-de390857cd31",
"name": "Build Prompt",
"type": "n8n-nodes-base.code",
"typeVersion": 2,
"position": [
760,
320
]
},
{
"parameters": {
"method": "POST",
"url": "https://api.openai.com/v1/responses",
"sendHeaders": true,
"headerParameters": {
"parameters": [
{
"name": "Authorization",
"value": "=Bearer {{$env.OPENAI_API_KEY}}"
},
{
"name": "Content-Type",
"value": "application/json"
}
]
},
"sendBody": true,
"specifyBody": "json",
"jsonBody": "={{ JSON.stringify({ model: $env.OPENAI_MODEL || 'gpt-4.1', instructions: $json.system_prompt, input: $json.user_message }) }}",
"options": {}
},
"id": "8fa63c89-0f00-4367-84b0-d68702c52890",
"name": "Call OpenAI Responses API",
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 4.2,
"position": [
1040,
320
]
},
{
"parameters": {
"jsCode": "const body = $json;\n let text = '';\n if (Array.isArray(body.output)) {\n for (const item of body.output) {\n if (Array.isArray(item.content)) {\n for (const c of item.content) {\n if (c.type === 'output_text' && c.text) text += c.text + '\n';\n }\n }\n }\n }\n return [{\n json: {\n agent: $('Set Agent Input').first().json.agent_title,\n result: text.trim(),\n raw_response: body\n }\n }];"
},
"id": "3a93671d-2dbd-460e-94ee-66f30d9fdcf7",
"name": "Extract Result",
"type": "n8n-nodes-base.code",
"typeVersion": 2,
"position": [
1300,
320
]
}
],
"connections": {
"Manual Trigger": {
"main": [
[
{
"node": "Set Agent Input",
"type": "main",
"index": 0
}
]
]
},
"Set Agent Input": {
"main": [
[
{
"node": "Build Prompt",
"type": "main",
"index": 0
}
]
]
},
"Build Prompt": {
"main": [
[
{
"node": "Call OpenAI Responses API",
"type": "main",
"index": 0
}
]
]
},
"Call OpenAI Responses API": {
"main": [
[
{
"node": "Extract Result",
"type": "main",
"index": 0
}
]
]
}
},
"settings": {
"executionOrder": "v1"
},
"meta": {
"templateCredsSetupCompleted": false
},
"active": false,
"versionId": "0a12679e-b4b7-47e5-8cc1-2b07c6f710cf",
"id": "70c76e29-313c-4e40-83f7-70d66c9396de",
"tags": [
"ai",
"template",
"lead-qualification-agent"
]
}
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About this workflow
Lead Qualification Agent. Uses httpRequest. Event-driven trigger; 5 nodes.
Source: https://github.com/kitz-labs/agent-templates-de/blob/1f4f4a5be56b818bda297731135696542f4907d5/lead-qualifizierung-agent/n8n/lead-qualifizierung-agent.n8n.json — original creator credit. Request a take-down →
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