The workflow JSON
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{
"name": "\u20a9^\u2661^\u20a9 Agent Swarm (LLM) \u2014 Webhook + History + Handoffs",
"nodes": [
{
"parameters": {
"httpMethod": "POST",
"path": "agent-swarm",
"options": {
"responseData": "auto",
"responseCode": 200
}
},
"id": "1",
"name": "Webhook In",
"type": "n8n-nodes-base.webhook",
"typeVersion": 1,
"position": [
-40,
0
]
},
{
"parameters": {
"functionCode": "// Normalize input, attach a sessionId, and basic meta\nconst body = $json.body ?? $json ?? {};\nconst sessionId = body.sessionId || $query.sessionId || $headers['x-session-id'] || Date.now().toString();\nconst userGoal = body.goal || body.prompt || body.query || 'Summarize and analyze topic';\nconst userData = body.data || {};\nconst now = new Date().toISOString();\n\nreturn [{\n json: {\n meta: {\n sessionId,\n receivedAt: now,\n ip: $headers['x-forwarded-for'] || $headers['cf-connecting-ip'] || $headers['x-real-ip'] || null,\n userAgent: $headers['user-agent'] || null\n },\n input: {\n goal: userGoal,\n data: userData\n }\n }\n}];\n"
},
"id": "2",
"name": "Init Context",
"type": "n8n-nodes-base.function",
"typeVersion": 2,
"position": [
200,
0
]
},
{
"parameters": {
"operation": "get",
"dataStoreId": "={{$env.SWARM_DATASTORE_ID}}",
"key": "={{$json.meta.sessionId}}",
"returnAll": false
},
"id": "3",
"name": "History: Get",
"type": "n8n-nodes-base.dataStore",
"typeVersion": 1,
"position": [
440,
0
]
},
{
"parameters": {
"functionCode": "// Merge previous history (if any) with the fresh input\nconst prev = $json.value || null;\nconst history = prev && prev.history ? prev.history : [];\n// keep last 10 turns to bound token usage\nconst trimmed = history.slice(-10);\n\nconst merged = {\n meta: $json.meta || prev?.meta || {},\n input: $json.input || {},\n history: trimmed\n};\n\nreturn [{ json: merged }];\n"
},
"id": "4",
"name": "History: Merge",
"type": "n8n-nodes-base.function",
"typeVersion": 2,
"position": [
680,
0
]
},
{
"parameters": {
"functionCode": "// Helper: build OpenAI Chat payload with role prompts\nfunction chatPayload(systemPrompt, userContent, temperature=0.3) {\n const model = $env.OPENAI_MODEL || \"gpt-4o-mini\";\n return {\n model,\n temperature,\n messages: [\n { role: \"system\", content: systemPrompt },\n // pack short history for handoff-awareness\n ...($json.history || []).map(h => ({ role: h.role || \"user\", content: h.content })),\n { role: \"user\", content: userContent }\n ]\n };\n}\n\nconst goal = $json.input.goal;\n\nreturn [{\n json: {\n researcher: chatPayload(\n \"You are Researcher-\u03b1. Discover facts, sources, constraints. Return JSON: {insights:[],sources:[],risks:[],next_step:\"...\"}. Be concise, cite URLs.\",\n `Goal: ${goal}\\nData: ${JSON.stringify($json.input.data || {}, null, 2)}`\n ),\n strategist: chatPayload(\n \"You are Strategist-\u03b2. Turn findings into a step-by-step plan. Return JSON: {plan:[{step,why,owner}],dependencies:[],success_criteria:[],next_step:\"...\"}.\",\n \"Use Researcher-\u03b1 output in your reasoning.\"\n ),\n builder: chatPayload(\n \"You are Builder-\u03b3. Produce the concrete deliverable (code/text). Return JSON: {artifact_type:\"code|copy|plan\", artifact:\"...\", notes:[],next_step:\"...\"}.\",\n \"Implement Strategist-\u03b2 plan minimally (MVP).\"\n ),\n reviewer: chatPayload(\n \"You are Reviewer-\u03b4. Critique for safety, legality, quality, and goal fit. Return JSON: {approved:true|false, issues:[], fixes:[], final_summary:\"...\"}. Be strict but practical.\",\n \"Review the Builder-\u03b3 artifact with context.\"\n )\n }\n}];\n"
},
"id": "5",
"name": "Assemble Agent Prompts",
"type": "n8n-nodes-base.function",
"typeVersion": 2,
"position": [
920,
0
]
},
{
"parameters": {
"method": "POST",
"url": "https://api.openai.com/v1/chat/completions",
"authentication": "genericCredentialType",
"genericAuthType": "headerAuth",
"sendBody": true,
"jsonParameters": true,
"options": {},
"specifyAuthentication": "headerAuth",
"headerAuth": {
"name": "Authorization",
"value": "={{'Bearer ' + $env.OPENAI_API_KEY}}"
},
"queryParametersUi": {
"parameter": []
},
"headersUi": {
"parameter": [
{
"name": "Content-Type",
"value": "application/json"
}
]
},
"bodyParametersJson": "={{$json.researcher}}"
},
"id": "6",
"name": "Researcher-\u03b1 (OpenAI)",
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 4,
"position": [
1160,
-140
]
},
{
"parameters": {
"functionCode": "// Parse OpenAI response into JSON\nconst text = $json.choices?.[0]?.message?.content ?? '{}';\nlet parsed;\ntry { parsed = JSON.parse(text); } catch(e) { parsed = { raw: text }; }\nreturn [{ json: { researcher: parsed } }];\n"
},
"id": "7",
"name": "Researcher: Parse",
"type": "n8n-nodes-base.function",
"typeVersion": 2,
"position": [
1400,
-140
]
},
{
"parameters": {
"method": "POST",
"url": "https://api.openai.com/v1/chat/completions",
"authentication": "genericCredentialType",
"genericAuthType": "headerAuth",
"sendBody": true,
"jsonParameters": true,
"specifyAuthentication": "headerAuth",
"headerAuth": {
"name": "Authorization",
"value": "={{'Bearer ' + $env.OPENAI_API_KEY}}"
},
"headersUi": {
"parameter": [
{
"name": "Content-Type",
"value": "application/json"
}
]
},
"bodyParametersJson": "={{$json.$prevNode[\"Assemble Agent Prompts\"].strategist}}"
},
"id": "8",
"name": "Strategist-\u03b2 (OpenAI)",
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 4,
"position": [
1160,
0
]
},
{
"parameters": {
"functionCode": "const text = $json.choices?.[0]?.message?.content ?? '{}';\nlet parsed;\ntry { parsed = JSON.parse(text); } catch(e) { parsed = { raw: text }; }\nreturn [{ json: { strategist: parsed } }];\n"
},
"id": "9",
"name": "Strategist: Parse",
"type": "n8n-nodes-base.function",
"typeVersion": 2,
"position": [
1400,
0
]
},
{
"parameters": {
"method": "POST",
"url": "https://api.openai.com/v1/chat/completions",
"authentication": "genericCredentialType",
"genericAuthType": "headerAuth",
"sendBody": true,
"jsonParameters": true,
"specifyAuthentication": "headerAuth",
"headerAuth": {
"name": "Authorization",
"value": "={{'Bearer ' + $env.OPENAI_API_KEY}}"
},
"headersUi": {
"parameter": [
{
"name": "Content-Type",
"value": "application/json"
}
]
},
"bodyParametersJson": "={{$json.$prevNode[\"Assemble Agent Prompts\"].builder}}"
},
"id": "10",
"name": "Builder-\u03b3 (OpenAI)",
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 4,
"position": [
1160,
140
]
},
{
"parameters": {
"functionCode": "const text = $json.choices?.[0]?.message?.content ?? '{}';\nlet parsed;\ntry { parsed = JSON.parse(text); } catch(e) { parsed = { raw: text }; }\nreturn [{ json: { builder: parsed } }];\n"
},
"id": "11",
"name": "Builder: Parse",
"type": "n8n-nodes-base.function",
"typeVersion": 2,
"position": [
1400,
140
]
},
{
"parameters": {
"method": "POST",
"url": "https://api.openai.com/v1/chat/completions",
"authentication": "genericCredentialType",
"genericAuthType": "headerAuth",
"sendBody": true,
"jsonParameters": true,
"specifyAuthentication": "headerAuth",
"headerAuth": {
"name": "Authorization",
"value": "={{'Bearer ' + $env.OPENAI_API_KEY}}"
},
"headersUi": {
"parameter": [
{
"name": "Content-Type",
"value": "application/json"
}
]
},
"bodyParametersJson": "={{$json.$prevNode[\"Assemble Agent Prompts\"].reviewer}}"
},
"id": "12",
"name": "Reviewer-\u03b4 (OpenAI)",
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 4,
"position": [
1160,
300
]
},
{
"parameters": {
"functionCode": "const text = $json.choices?.[0]?.message?.content ?? '{}';\nlet parsed;\ntry { parsed = JSON.parse(text); } catch(e) { parsed = { raw: text }; }\nreturn [{ json: { reviewer: parsed } }];\n"
},
"id": "13",
"name": "Reviewer: Parse",
"type": "n8n-nodes-base.function",
"typeVersion": 2,
"position": [
1400,
300
]
},
{
"parameters": {
"conditions": {
"boolean": [
{
"value1": "={{$json.reviewer.approved === true}}"
}
]
}
},
"id": "14",
"name": "Approved?",
"type": "n8n-nodes-base.if",
"typeVersion": 1,
"position": [
1620,
220
]
},
{
"parameters": {
"functionCode": "// Assemble final output when approved\nreturn [{\n json: {\n status: \"approved\",\n sessionId: $json.meta?.sessionId,\n insights: $json.researcher?.insights,\n sources: $json.researcher?.sources,\n plan: $json.strategist?.plan,\n artifact: $json.builder?.artifact,\n artifact_type: $json.builder?.artifact_type,\n summary: $json.reviewer?.final_summary,\n timestamp: new Date().toISOString()\n }\n}];\n"
},
"id": "15",
"name": "Assemble Final (OK)",
"type": "n8n-nodes-base.function",
"typeVersion": 2,
"position": [
1840,
160
]
},
{
"parameters": {
"functionCode": "// Return issues & fixes when not approved\nreturn [{\n json: {\n status: \"changes_requested\",\n sessionId: $json.meta?.sessionId,\n issues: $json.reviewer?.issues || [],\n fixes: $json.reviewer?.fixes || [],\n partial: {\n insights: $json.researcher?.insights,\n plan: $json.strategist?.plan,\n artifact: $json.builder?.artifact\n },\n timestamp: new Date().toISOString()\n }\n}];\n"
},
"id": "16",
"name": "Assemble Final (Revise)",
"type": "n8n-nodes-base.function",
"typeVersion": 2,
"position": [
1840,
300
]
},
{
"parameters": {
"operation": "upsert",
"dataStoreId": "={{$env.SWARM_DATASTORE_ID}}",
"key": "={{$json.sessionId || $json.meta?.sessionId}}",
"value": "={{$json}}"
},
"id": "17",
"name": "History: Upsert",
"type": "n8n-nodes-base.dataStore",
"typeVersion": 1,
"position": [
2060,
220
]
},
{
"parameters": {
"responseBody": "={{$json}}",
"responseCode": 200
},
"id": "18",
"name": "Respond",
"type": "n8n-nodes-base.respondToWebhook",
"typeVersion": 1,
"position": [
2280,
220
]
}
],
"connections": {
"Webhook In": {
"main": [
[
{
"node": "Init Context",
"type": "main",
"index": 0
}
]
]
},
"Init Context": {
"main": [
[
{
"node": "History: Get",
"type": "main",
"index": 0
}
]
]
},
"History: Get": {
"main": [
[
{
"node": "History: Merge",
"type": "main",
"index": 0
}
]
]
},
"History: Merge": {
"main": [
[
{
"node": "Assemble Agent Prompts",
"type": "main",
"index": 0
}
]
]
},
"Assemble Agent Prompts": {
"main": [
[
{
"node": "Researcher-\u03b1 (OpenAI)",
"type": "main",
"index": 0
}
],
[
{
"node": "Strategist-\u03b2 (OpenAI)",
"type": "main",
"index": 0
}
],
[
{
"node": "Builder-\u03b3 (OpenAI)",
"type": "main",
"index": 0
}
],
[
{
"node": "Reviewer-\u03b4 (OpenAI)",
"type": "main",
"index": 0
}
]
]
},
"Researcher-\u03b1 (OpenAI)": {
"main": [
[
{
"node": "Researcher: Parse",
"type": "main",
"index": 0
}
]
]
},
"Strategist-\u03b2 (OpenAI)": {
"main": [
[
{
"node": "Strategist: Parse",
"type": "main",
"index": 0
}
]
]
},
"Builder-\u03b3 (OpenAI)": {
"main": [
[
{
"node": "Builder: Parse",
"type": "main",
"index": 0
}
]
]
},
"Reviewer-\u03b4 (OpenAI)": {
"main": [
[
{
"node": "Reviewer: Parse",
"type": "main",
"index": 0
}
]
]
},
"Researcher: Parse": {
"main": [
[
{
"node": "Approved?",
"type": "main",
"index": 0
}
]
]
},
"Strategist: Parse": {
"main": [
[
{
"node": "Approved?",
"type": "main",
"index": 0
}
]
]
},
"Builder: Parse": {
"main": [
[
{
"node": "Approved?",
"type": "main",
"index": 0
}
]
]
},
"Reviewer: Parse": {
"main": [
[
{
"node": "Approved?",
"type": "main",
"index": 0
}
]
]
},
"Approved?": {
"main": [
[
{
"node": "Assemble Final (OK)",
"type": "main",
"index": 0
}
],
[
{
"node": "Assemble Final (Revise)",
"type": "main",
"index": 0
}
]
]
},
"Assemble Final (OK)": {
"main": [
[
{
"node": "History: Upsert",
"type": "main",
"index": 0
}
]
]
},
"Assemble Final (Revise)": {
"main": [
[
{
"node": "History: Upsert",
"type": "main",
"index": 0
}
]
]
},
"History: Upsert": {
"main": [
[
{
"node": "Respond",
"type": "main",
"index": 0
}
]
]
}
},
"settings": {
"saveExecutionProgress": true,
"executionOrder": "v1"
},
"staticData": null
}
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About this workflow
₩^♡^₩ Agent Swarm (LLM) — Webhook + History + Handoffs. Uses dataStore, httpRequest. Webhook trigger; 18 nodes.
Source: https://github.com/405naturaldesign-tech/puraestate/blob/fc713a902df1e926a8beebcb3f1f402ab2fbbec0/n8n-workflows/agent_swarm_n8n.json — original creator credit. Request a take-down →
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