Cheng Siong Chin This workflow corresponds to n8n.io template #13869 — we link there as the canonical source.
This workflow follows the Agent → Agenttool 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 →
{
"id": "uXlhEUBFYoxLsFS8",
"name": "Smart research proposal generator with multi-agent quality control",
"tags": [],
"nodes": [
{
"id": "ca7007ad-158b-4434-8b2e-cb7739b8c455",
"name": "Start Proposal Generation",
"type": "n8n-nodes-base.manualTrigger",
"position": [
256,
400
],
"parameters": {},
"typeVersion": 1
},
{
"id": "df0ede85-7a8a-4cb9-8fbe-daed03ec539e",
"name": "Supervisor Agent",
"type": "@n8n/n8n-nodes-langchain.agent",
"position": [
1072,
416
],
"parameters": {
"text": "={{ $json.chatInput }}",
"options": {
"systemMessage": "You are a research proposal coordinator for AI and Data-Driven Systems funding applications. Your role is to orchestrate the creation of a comprehensive, competitive research proposal that meets international funding agency standards.\n\nYou have access to two specialized agents:\n1. Research Content Agent - Handles problem statements, research objectives, hypotheses, methodology, data strategy, model design, experimental validation, risk mitigation, reproducibility, innovation, and expected contributions\n2. Strategic Planning Agent - Handles work plans, milestones, timelines, deliverables, budget justification, impact assessment (scientific, societal, economic), commercialization strategy, stakeholder engagement, ethical considerations, bias mitigation, and sustainability plans\n\nYou also have access to a Funding Agency Research Tool to gather current information about funding priorities and AI research trends.\n\nYour task:\n1. First, use the Funding Agency Research Tool to gather context about current AI funding priorities and research gaps\n2. Delegate to the Research Content Agent to develop the scientific foundation of the proposal\n3. Delegate to the Strategic Planning Agent to develop the strategic and operational components\n4. Synthesize their outputs into a cohesive, persuasive research proposal\n\nEnsure the final proposal is evidence-based, demonstrates feasibility and scalability, aligns with funding agency priorities, and follows standard grant evaluation criteria."
},
"promptType": "define"
},
"typeVersion": 3.1
},
{
"id": "0148fe81-c040-4086-bd3f-8f7b42e01521",
"name": "Supervisor Model",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"position": [
432,
624
],
"parameters": {
"model": {
"__rl": true,
"mode": "id",
"value": "gpt-4o"
},
"options": {
"temperature": 0.7
},
"builtInTools": {}
},
"credentials": {
"openAiApi": {
"name": "<your credential>"
}
},
"typeVersion": 1.3
},
{
"id": "8dc71381-b990-4546-965b-e6da8fab66ae",
"name": "Research Content Agent",
"type": "@n8n/n8n-nodes-langchain.agentTool",
"position": [
736,
624
],
"parameters": {
"text": "={{ $fromAI('task', 'The specific research content task to complete') }}",
"options": {
"systemMessage": "You are a research methodology expert specializing in AI and Data-Driven Systems. Your role is to develop the scientific foundation of research proposals.\n\nWhen given a task, create comprehensive, rigorous content covering:\n- Problem Statement: Clearly articulate current scientific and industry gaps, grounded in evidence\n- Research Objectives: Define specific, measurable objectives\n- Testable Hypotheses: Formulate clear, falsifiable hypotheses\n- Methodology: Detail data strategy (collection, preprocessing, quality assurance), model design (architecture, algorithms, training approach), experimental validation (metrics, baselines, statistical tests), risk mitigation strategies, and reproducibility measures (code sharing, documentation, version control)\n- Innovation: Describe novel contributions and how they advance the field\n- Expected Contributions: Articulate scientific impact and knowledge advancement\n\nWrite in a persuasive, evidence-based tone suitable for competitive grant applications. Be specific, rigorous, and demonstrate deep technical expertise."
},
"toolDescription": "Develops the scientific foundation of the research proposal including problem statement, objectives, hypotheses, methodology, data strategy, model design, experimental validation, risk mitigation, reproducibility, innovation, and expected contributions"
},
"typeVersion": 3
},
{
"id": "6ffe8e72-d71c-4340-bb38-b2ad9c33fd40",
"name": "Research Content Model",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"position": [
736,
832
],
"parameters": {
"model": {
"__rl": true,
"mode": "id",
"value": "gpt-4o"
},
"options": {
"temperature": 0.6
},
"builtInTools": {}
},
"credentials": {
"openAiApi": {
"name": "<your credential>"
}
},
"typeVersion": 1.3
},
{
"id": "96a15c43-8668-43c8-8800-51d42a4c33a6",
"name": "Strategic Planning Agent",
"type": "@n8n/n8n-nodes-langchain.agentTool",
"position": [
1024,
624
],
"parameters": {
"text": "={{ $fromAI('task', 'The specific strategic planning task to complete') }}",
"options": {
"systemMessage": "You are a research strategy and project management expert specializing in AI and Data-Driven Systems funding applications. Your role is to develop the strategic and operational components of research proposals.\n\nYou have access to specialized models for ethics analysis and impact assessment. Use them to enhance the strategic components of the proposal with comprehensive ethical considerations and impact narratives.\n\nWhen given a task, create comprehensive, well-structured content covering:\n- Work Plan: Structured plan with clear phases, milestones, timeline (Gantt-style if appropriate), and deliverables\n- Budget Justification: Detailed budget aligned to tasks and milestones (personnel, equipment, travel, other costs) with clear rationale\n- Impact Assessment: Anticipated scientific impact (publications, methods, tools), societal impact (benefits to communities, policy influence), and economic impact (industry applications, job creation, market potential)\n- Commercialization/Translation Strategy: Pathway from research to application, IP strategy, industry partnerships, market analysis\n- Stakeholder Engagement: Plan for engaging researchers, industry, policymakers, end-users, and communities\n- Ethical Considerations: Data privacy, informed consent, bias mitigation strategies, fairness assessment, responsible AI practices\n- Sustainability Plan: Strategy for continuing impact beyond funding period (follow-on funding, partnerships, open-source contributions, capacity building)\n\nWrite in a persuasive, evidence-based tone that demonstrates feasibility, scalability, and alignment with funding agency priorities. Be specific about timelines, costs, and measurable outcomes."
},
"toolDescription": "Develops the strategic and operational components of the research proposal including work plan, budget, impact assessment, commercialization strategy, stakeholder engagement, ethics, and sustainability"
},
"typeVersion": 3
},
{
"id": "77e1f9a1-1448-46e7-93c9-3dcca720f7d9",
"name": "Strategic Planning Model",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"position": [
1024,
832
],
"parameters": {
"model": {
"__rl": true,
"mode": "id",
"value": "gpt-4o"
},
"options": {
"temperature": 0.6
},
"builtInTools": {}
},
"credentials": {
"openAiApi": {
"name": "<your credential>"
}
},
"typeVersion": 1.3
},
{
"id": "4119ab75-aebd-4ed3-ac87-536f0173a638",
"name": "Funding Agency Research Tool",
"type": "n8n-nodes-base.httpRequestTool",
"position": [
1312,
624
],
"parameters": {
"url": "={{ $fromAI('url', 'The URL to fetch information about AI funding priorities or research trends', 'string', 'https://api.example.com/ai-funding-trends') }}",
"options": {},
"toolDescription": "Fetches current information about AI research funding priorities, trends, and gaps from external sources to inform proposal development"
},
"typeVersion": 4.4
},
{
"id": "1f6a35b9-d0cd-4e25-bd7b-e6abbdbc93cc",
"name": "Web Search Tool",
"type": "@n8n/n8n-nodes-langchain.toolSerpApi",
"position": [
1520,
640
],
"parameters": {
"options": {}
},
"typeVersion": 1
},
{
"id": "c44c4394-0391-4623-a648-f5794a3d81de",
"name": "Quality Control Agent",
"type": "@n8n/n8n-nodes-langchain.agent",
"position": [
1872,
400
],
"parameters": {
"text": "={{ JSON.stringify($json) }}",
"options": {
"systemMessage": "You are a research proposal quality control expert. Review the generated proposal and assess its quality across multiple dimensions: completeness, scientific rigor, clarity, persuasiveness, alignment with funding priorities, feasibility, innovation level, and budget reasonableness. Identify strengths, weaknesses, and specific improvement recommendations. Provide an overall quality score from 0-100."
},
"promptType": "define",
"hasOutputParser": true
},
"typeVersion": 3.1
},
{
"id": "ed3f1fe2-e7e2-4f98-9649-9a7245a5c050",
"name": "Quality Control Model",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"position": [
1808,
608
],
"parameters": {
"model": {
"__rl": true,
"mode": "id",
"value": "gpt-4o"
},
"options": {
"temperature": 0.2
},
"builtInTools": {}
},
"credentials": {
"openAiApi": {
"name": "<your credential>"
}
},
"typeVersion": 1.3
},
{
"id": "5fdec929-283b-4f02-b162-052c6a7a5e3c",
"name": "Quality Assessment Output",
"type": "@n8n/n8n-nodes-langchain.outputParserStructured",
"position": [
2008,
624
],
"parameters": {
"schemaType": "manual",
"inputSchema": "{\"type\": \"object\", \"properties\": {\"quality_score\": {\"type\": \"number\", \"description\": \"Overall quality score 0-100\"}, \"completeness_score\": {\"type\": \"number\"}, \"rigor_score\": {\"type\": \"number\"}, \"clarity_score\": {\"type\": \"number\"}, \"innovation_score\": {\"type\": \"number\"}, \"strengths\": {\"type\": \"array\", \"items\": {\"type\": \"string\"}}, \"weaknesses\": {\"type\": \"array\", \"items\": {\"type\": \"string\"}}, \"recommendations\": {\"type\": \"array\", \"items\": {\"type\": \"string\"}}, \"pass_threshold\": {\"type\": \"boolean\", \"description\": \"Whether proposal meets minimum quality threshold\"}}, \"required\": [\"quality_score\", \"pass_threshold\", \"strengths\", \"weaknesses\", \"recommendations\"]}"
},
"typeVersion": 1.3
},
{
"id": "aceb9cba-b42f-413d-900b-84f5e426096a",
"name": "Check Quality Score",
"type": "n8n-nodes-base.if",
"position": [
2240,
400
],
"parameters": {
"options": {},
"conditions": {
"options": {
"leftValue": "",
"caseSensitive": false,
"typeValidation": "loose"
},
"combinator": "and",
"conditions": [
{
"id": "id-1",
"operator": {
"type": "number",
"operation": "gte"
},
"leftValue": "={{ $('Quality Control Agent').item.json.output.quality_score }}",
"rightValue": "75"
}
]
}
},
"typeVersion": 2.3
},
{
"id": "795d8fbc-0778-48f2-bb29-7173e362e92e",
"name": "Format Final Proposal",
"type": "n8n-nodes-base.set",
"position": [
2448,
496
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "id-1",
"name": "status",
"type": "string",
"value": "approved"
},
{
"id": "id-2",
"name": "proposal_title",
"type": "string",
"value": "={{ $('Supervisor Agent').item.json.output.title }}"
},
{
"id": "id-3",
"name": "quality_score",
"type": "number",
"value": "={{ $('Quality Control Agent').item.json.output.quality_score }}"
},
{
"id": "id-4",
"name": "full_proposal",
"type": "object",
"value": "={{ JSON.stringify($('Supervisor Agent').item.json.output) }}"
}
]
},
"includeOtherFields": true
},
"typeVersion": 3.4
},
{
"id": "4335c976-1d51-42c3-b2d7-d8b81af8d4be",
"name": "Flag for Revision",
"type": "n8n-nodes-base.set",
"position": [
2448,
304
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "id-1",
"name": "status",
"type": "string",
"value": "needs_revision"
},
{
"id": "id-2",
"name": "quality_score",
"type": "number",
"value": "={{ $('Quality Control Agent').item.json.output.quality_score }}"
},
{
"id": "id-3",
"name": "weaknesses",
"type": "array",
"value": "={{ $('Quality Control Agent').item.json.output.weaknesses }}"
},
{
"id": "id-4",
"name": "recommendations",
"type": "array",
"value": "={{ $('Quality Control Agent').item.json.output.recommendations }}"
}
]
},
"includeOtherFields": true
},
"typeVersion": 3.4
},
{
"id": "91b05631-bcd1-4a28-8edc-e92a0492af54",
"name": "Store Proposal Results",
"type": "n8n-nodes-base.dataTable",
"position": [
2896,
400
],
"parameters": {
"columns": {
"value": null,
"mappingMode": "autoMapInputData"
},
"options": {},
"dataTableId": {
"__rl": true,
"mode": "id",
"value": "<__PLACEHOLDER_VALUE__proposal_results_table__>"
}
},
"typeVersion": 1.1
},
{
"id": "5194b43d-7f59-4f48-9aac-eb3b0a4da8c8",
"name": "Prepare Storage Data",
"type": "n8n-nodes-base.set",
"position": [
2672,
400
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "id-1",
"name": "timestamp",
"type": "string",
"value": "={{ $now.toISO() }}"
},
{
"id": "id-2",
"name": "proposal_id",
"type": "string",
"value": "={{ $runIndex }}-{{ $now.toMillis() }}"
}
]
},
"includeOtherFields": true
},
"typeVersion": 3.4
},
{
"id": "073fb53e-bd16-4c76-b00d-db22e311648f",
"name": "Conversation Memory",
"type": "@n8n/n8n-nodes-langchain.memoryBufferWindow",
"position": [
608,
624
],
"parameters": {
"contextWindowLength": 10
},
"typeVersion": 1.3
},
{
"id": "8cce1954-1968-4a42-ac25-65de08e79d55",
"name": "Ethics Model",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"position": [
1200,
832
],
"parameters": {
"model": {
"__rl": true,
"mode": "id",
"value": "gpt-4o"
},
"options": {
"temperature": 0.4
},
"builtInTools": {}
},
"credentials": {
"openAiApi": {
"name": "<your credential>"
}
},
"typeVersion": 1.3
},
{
"id": "6dccd987-f05a-40c0-8d34-96c76ff0fa42",
"name": "Impact Model",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"position": [
1360,
832
],
"parameters": {
"model": {
"__rl": true,
"mode": "id",
"value": "gpt-4o"
},
"options": {
"temperature": 0.5
},
"builtInTools": {}
},
"credentials": {
"openAiApi": {
"name": "<your credential>"
}
},
"typeVersion": 1.3
},
{
"id": "73662f95-3703-4d2f-9471-09a4c59ea193",
"name": "Parse Proposal Structure",
"type": "n8n-nodes-base.code",
"position": [
1648,
400
],
"parameters": {
"jsCode": "// Parse the Supervisor Agent output and structure it as JSON\nconst items = $input.all();\nconst results = [];\n\nfor (const item of items) {\n const agentOutput = item.json.output || {};\n \n // Structure the proposal data\n const structuredProposal = {\n title: agentOutput.title || 'Untitled Proposal',\n problem_statement: agentOutput.problem_statement || agentOutput.problemStatement || '',\n objectives: agentOutput.objectives || agentOutput.research_objectives || [],\n hypotheses: agentOutput.hypotheses || agentOutput.testable_hypotheses || [],\n methodology: agentOutput.methodology || {},\n innovation: agentOutput.innovation || agentOutput.expected_contributions || '',\n work_plan: agentOutput.work_plan || agentOutput.workPlan || {},\n budget: agentOutput.budget || agentOutput.budget_justification || {},\n impact: agentOutput.impact || agentOutput.impact_assessment || {},\n commercialization_strategy: agentOutput.commercialization_strategy || agentOutput.commercializationStrategy || '',\n stakeholder_engagement: agentOutput.stakeholder_engagement || agentOutput.stakeholderEngagement || '',\n ethical_considerations: agentOutput.ethical_considerations || agentOutput.ethicalConsiderations || '',\n sustainability_plan: agentOutput.sustainability_plan || agentOutput.sustainabilityPlan || ''\n };\n \n results.push({\n json: structuredProposal\n });\n}\n\nreturn results;"
},
"typeVersion": 2
},
{
"id": "cf0d1669-92a0-4e67-8b36-9095a5b4a7c8",
"name": "Sticky Note",
"type": "n8n-nodes-base.stickyNote",
"position": [
1776,
288
],
"parameters": {
"color": 7,
"width": 416,
"height": 736,
"content": "## Quality Control\n**What:** QC Agent scores the parsed proposal output.\n**Why:** Prevents substandard proposals from reaching storage."
},
"typeVersion": 1
},
{
"id": "f47e5a98-f22a-4d07-b738-4340332bd9fa",
"name": "Sticky Note1",
"type": "n8n-nodes-base.stickyNote",
"position": [
1392,
-112
],
"parameters": {
"color": 5,
"width": 384,
"height": 336,
"content": "## Prerequisites\n- Web search API key (SerpAPI/Tavily)\n- Google Sheets or database credentials\n## Use Cases\n- Grant proposal drafting for research institutions\n## Customisation\n- Swap AI models per agent for cost/performance balance\n## Benefits\n- Cuts proposal drafting time by 70\u201380%"
},
"typeVersion": 1
},
{
"id": "d5d892e1-7471-465c-95f2-11c87443e37f",
"name": "Sticky Note2",
"type": "n8n-nodes-base.stickyNote",
"position": [
944,
-96
],
"parameters": {
"width": 400,
"height": 320,
"content": "## Setup Steps\n1. Add OpenAI (or compatible) API credentials to all AI model nodes.\n2. Configure Supervisor, Research Content, Strategic Planning, and QC Agent system prompts.\n3. Set up Funding Agency Research Tool with target agency endpoints or search parameters.\n4. Connect Web Search Tool credentials (e.g., SerpAPI or Tavily).\n5. Configure storage node (Google Sheets/database) with target schema.\n6. Set quality score threshold in the Check Quality Score node."
},
"typeVersion": 1
},
{
"id": "e4c549ad-753f-4e70-b590-462f1516a56b",
"name": "Sticky Note3",
"type": "n8n-nodes-base.stickyNote",
"position": [
320,
-64
],
"parameters": {
"width": 576,
"height": 304,
"content": "## How It Works\nThis workflow automates academic and professional research proposal generation using a multi-agent AI pipeline. It targets researchers, academics, grant writers, and R&D teams who need structured, high-quality proposals efficiently. The core problem it solves: manually drafting proposals is time-consuming, inconsistent, and prone to missing key elements like ethics, impact, and funding alignment. A Supervisor Agent orchestrates three specialist sub-agents, Research Content, Strategic Planning, and Ethics/Impact, each powered by dedicated AI models. A Funding Agency Research Tool and Web Search Tool supply real-time context. The generated proposal is parsed, then evaluated by a Quality Control Agent. Proposals meeting the quality threshold are formatted and stored; those falling short are flagged for human revision, ensuring only polished outputs reach storage."
},
"typeVersion": 1
},
{
"id": "175a8e31-eafd-430a-8ba2-6c61aed3bf7e",
"name": "Sticky Note4",
"type": "n8n-nodes-base.stickyNote",
"position": [
224,
256
],
"parameters": {
"color": 7,
"width": 1536,
"height": 880,
"content": "## Multi-Agent Content Generation\n**What:** Research Content, Strategic Planning, and Ethics/Impact agents draft proposal sections in parallel.\n**Why:** Parallel specialisation improves depth and reduces generation time."
},
"typeVersion": 1
},
{
"id": "77416593-d0b1-4730-871f-be55af9de069",
"name": "Sticky Note5",
"type": "n8n-nodes-base.stickyNote",
"position": [
2208,
176
],
"parameters": {
"color": 7,
"width": 832,
"height": 736,
"content": "\n## Conditional Routing\n**What:** High-scoring proposals are formatted; low-scoring ones are flagged for revision.\n**Why:** Maintains output quality with minimal manual intervention.\n"
},
"typeVersion": 1
}
],
"active": false,
"settings": {
"binaryMode": "separate",
"availableInMCP": false,
"executionOrder": "v1"
},
"versionId": "e2491125-351e-44c3-8dff-3ed8daa97a3a",
"connections": {
"Ethics Model": {
"ai_languageModel": [
[
{
"node": "Strategic Planning Agent",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Impact Model": {
"ai_languageModel": [
[
{
"node": "Strategic Planning Agent",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Web Search Tool": {
"ai_tool": [
[
{
"node": "Supervisor Agent",
"type": "ai_tool",
"index": 0
}
]
]
},
"Supervisor Agent": {
"main": [
[
{
"node": "Parse Proposal Structure",
"type": "main",
"index": 0
}
]
]
},
"Supervisor Model": {
"ai_languageModel": [
[
{
"node": "Supervisor Agent",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Flag for Revision": {
"main": [
[
{
"node": "Prepare Storage Data",
"type": "main",
"index": 0
}
]
]
},
"Check Quality Score": {
"main": [
[
{
"node": "Format Final Proposal",
"type": "main",
"index": 0
}
],
[
{
"node": "Flag for Revision",
"type": "main",
"index": 0
}
]
]
},
"Conversation Memory": {
"ai_memory": [
[
{
"node": "Supervisor Agent",
"type": "ai_memory",
"index": 0
}
]
]
},
"Prepare Storage Data": {
"main": [
[
{
"node": "Store Proposal Results",
"type": "main",
"index": 0
}
]
]
},
"Format Final Proposal": {
"main": [
[
{
"node": "Prepare Storage Data",
"type": "main",
"index": 0
}
]
]
},
"Quality Control Agent": {
"main": [
[
{
"node": "Check Quality Score",
"type": "main",
"index": 0
}
]
]
},
"Quality Control Model": {
"ai_languageModel": [
[
{
"node": "Quality Control Agent",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Research Content Agent": {
"ai_tool": [
[
{
"node": "Supervisor Agent",
"type": "ai_tool",
"index": 0
}
]
]
},
"Research Content Model": {
"ai_languageModel": [
[
{
"node": "Research Content Agent",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Parse Proposal Structure": {
"main": [
[
{
"node": "Quality Control Agent",
"type": "main",
"index": 0
}
]
]
},
"Strategic Planning Agent": {
"ai_tool": [
[
{
"node": "Supervisor Agent",
"type": "ai_tool",
"index": 0
}
]
]
},
"Strategic Planning Model": {
"ai_languageModel": [
[
{
"node": "Strategic Planning Agent",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Quality Assessment Output": {
"ai_outputParser": [
[
{
"node": "Quality Control Agent",
"type": "ai_outputParser",
"index": 0
}
]
]
},
"Start Proposal Generation": {
"main": [
[
{
"node": "Supervisor Agent",
"type": "main",
"index": 0
}
]
]
},
"Funding Agency Research Tool": {
"ai_tool": [
[
{
"node": "Supervisor Agent",
"type": "ai_tool",
"index": 0
}
]
]
}
}
}
Credentials you'll need
Each integration node will prompt for credentials when you import. We strip credential IDs before publishing — you'll add your own.
openAiApi
Pro
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About this workflow
This workflow automates academic and professional research proposal generation using a multi-agent AI pipeline. It targets researchers, academics, grant writers, and R&D teams who need structured, high-quality proposals efficiently. The core problem it solves: manually drafting…
Source: https://n8n.io/workflows/13869/ — original creator credit. Request a take-down →
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Who is this for? Agencies, consultants, and service providers who conduct discovery calls and need to quickly turn conversations into professional proposals.
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