PRD 테스트 케이스
이것은Document Extraction, Multimodal AI분야의자동화 워크플로우로, 9개의 노드를 포함합니다.주로 Set, Form, FormTrigger, ApiTemplateIo, ChainLlm 등의 노드를 사용하며. GPT/Claude를 사용하여 제품 요구 사항 문서 및 테스트 시나리오 생성, PDF로 내보내기
- •특별한 사전 요구사항 없이 가져와 바로 사용 가능합니다
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"meta": {
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"templateCredsSetupCompleted": true
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"name": "PRD_Testcase",
"tags": [],
"nodes": [
{
"id": "7aa1d0eb-a145-4713-b12c-72d757924ef1",
"name": "OpenRouter Chat Model",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenRouter",
"position": [
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"parameters": {
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"credentials": {
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"parameters": {
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"credentials": {
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{
"id": "bc40e4ea-8bdd-4a60-88c9-aa4167640f08",
"name": "메모",
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"content": "### 📒 Generate **Product Requirements Document (PRD)** and **test scenarios** form input to PDF with OpenRouter and APITemplate.io\n\nThis workflow generates a **Product Requirements Document (PRD)** and **test scenarios** from structured form inputs. It uses **OpenRouter LLMs (GPT/Claude)** for natural language generation and **APITemplate.io** for PDF export. \n\n## Who’s it for\nThis template is designed for **product managers, business analysts, QA teams, and startup founders** who need to quickly create **Product Requirement Documents (PRDs)** and **test cases** from structured inputs. \n\n## How it works\n1. A **Form Trigger** collects key product details (name, overview, audience, goals, requirements). \n2. The **LLM Chain (OpenRouter GPT/Claude)** generates a professional, structured **PRD in Markdown format**. \n3. A second **LLM Chain** creates **test scenarios and Gherkin-style test cases** based on the PRD. \n4. Data is cleaned and merged using a **Set node**. \n5. The workflow sends the formatted document to **APITemplate.io** to generate a polished **PDF**. \n6. Finally, the workflow returns the PDF via a **Form Completion node** for easy download. \n \n\n## ⚡ Requirements\n- OpenRouter API Key (or any LLM)\n- APITemplate.io account \n\n## 🎯 Use cases\n- Rapid PRD drafting for startups. \n- QA teams generating **test scenarios** automatically. \n- Standardized documentation workflows. \n\n👉 Customize by editing prompts, PDF templates, or extending with integrations (Slack, Notion, Confluence). \n"
},
"typeVersion": 1
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{
"id": "4c5c5daa-2ec9-451e-a827-b1d4cb21aecf",
"name": "PRD LLM 체인",
"type": "@n8n/n8n-nodes-langchain.chainLlm",
"position": [
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"parameters": {
"text": "=Product Name - {{ $json['Product Name'] || 'Not Available'}}\nProduct Overview - {{ $json['Product Overview'] || 'Not Available' }}\nTarget Audience - {{ $json['Target Audience'] || 'Not Available' }}\nGoal & Objective - {{ $json['Goals & Objectives'] || 'Not Available' }}\nFunctional Requirements - {{ $json['Functional Requirements'] || 'Not Available' }}\nDate: {{ $json.submittedAt.split(\"T\")[0] }}\nCreated By - {{ $json['Created By'] || 'Not Available' }}",
"batching": {},
"messages": {
"messageValues": [
{
"message": "=You are an expert product manager and technical writer. \nYour task is to generate a clear, structured **Product Requirements Document (PRD)** in **Markdown format**. \nThe PRD should be professional, concise, and easy to share with engineers, designers, and stakeholders. \n\nUse Information provided by User prompt to Understand the requirement and try to go deep in filing all section.\n\n### Formatting Rules\n- Use proper Markdown headers (`#`, `##`, `###`) for sections. \n- Use bullet points or numbered lists where appropriate. \n- Keep language clear and action-oriented. \n- Do not include explanations of what a PRD is.\n\n### PRD Template\n# Product Requirements Document (PRD)\n\n## 1. Overview\n- **Project Name:** \n- **Document Owner:** (leave blank if not provided)\n- **Last Updated:** (user created date provided by user)\n\n## 2. Problem Statement\n\n## 3. Goals\n\n## 4. Non-Goals\n- (list if provided, else mark as “N/A”)\n\n## 5. Target Audience / Users\n - Pain Points Solved:\n\n## 6. Key Features / Requirements\n -Primary Users:\n -Secondary Users:\n - (expand if needed)\n\n## 7. Key Features\n(expand if missing)\n\n## 8. Functional Requirements\n(expand if missing)\n\n## 8. Technical Constraints\n(expand if missing)\n\n## 9. Success Metrics\n- (expand if missing)\n\n## 10. Risks & Assumptions\n\n---\n"
}
]
},
"promptType": "define"
},
"typeVersion": 1.7
},
{
"id": "b6f3b365-d277-4917-bb39-6c44a3c9d29b",
"name": "Test Case LLM 체인",
"type": "@n8n/n8n-nodes-langchain.chainLlm",
"position": [
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],
"parameters": {
"text": "={{ $json.text }}",
"batching": {},
"messages": {
"messageValues": [
{
"message": "Using the user input PRD document create Test scenario and test case in gherkin language. "
}
]
},
"promptType": "define"
},
"typeVersion": 1.7
},
{
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"name": "Get User Input",
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],
"webhookId": "0a0d6c63-a806-4bb8-a9b6-f29c184a59b7",
"parameters": {
"options": {
"appendAttribution": false
},
"formTitle": "Technical Document Requirement",
"formFields": {
"values": [
{
"fieldLabel": "Product Name",
"placeholder": "Fitness Guru"
},
{
"fieldType": "textarea",
"fieldLabel": "Product Overview",
"placeholder": "An app that helps gym-goers track workouts, find classes, and stay motivated",
"requiredField": true
},
{
"fieldLabel": "Target Audience",
"placeholder": "gym members, personal trainers, gym owners"
},
{
"fieldLabel": "Goals & Objectives",
"placeholder": "Increase gym member engagement, streamline trainer-client interaction"
},
{
"fieldLabel": "Functional Requirements",
"placeholder": "Workout logging → select exercise → enter sets/reps → save → progress updates on dashboard."
}
]
},
"responseMode": "lastNode"
},
"typeVersion": 2.2
},
{
"id": "df78c5c0-2394-4fc4-b04b-da34bd07b7db",
"name": "병합 PRD and Test Case",
"type": "n8n-nodes-base.set",
"position": [
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],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "afee93c8-7b59-40b8-975a-55e4a3c9d35a",
"name": "text",
"type": "string",
"value": "={{ $('PRD LLM Chain').item.json.text }}\n{{ $json.text }}"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "2352e0ea-0f51-4b62-9dd1-b7af7a2a1628",
"name": "Create Document in PDF",
"type": "n8n-nodes-base.apiTemplateIo",
"position": [
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],
"parameters": {
"options": {
"fileName": "PRD_abc.pdf"
},
"download": true,
"resource": "pdf",
"propertiesUi": {
"propertyValues": [
{
"key": "markdown",
"value": "={{ $json.text }}"
}
]
},
"pdfTemplateId": "=e1277b23d41c334e"
},
"credentials": {
"apiTemplateIoApi": {
"id": "wve3UL6j52R45XJI",
"name": "learnbyalok_APITemplate.io account"
}
},
"typeVersion": 1
},
{
"id": "c1b7dcee-035e-46f3-8cfc-985cc7920839",
"name": "Let User Download",
"type": "n8n-nodes-base.form",
"position": [
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"webhookId": "a3e6b03b-d6a8-4390-9884-bfe08fb8cebd",
"parameters": {
"options": {},
"operation": "completion",
"respondWith": "returnBinary",
"completionTitle": "PRD Document is ready",
"completionMessage": "Process completed file will be downloaded! ",
"inputDataFieldName": "=data"
},
"typeVersion": 1
}
],
"active": false,
"pinData": {},
"settings": {
"executionOrder": "v1"
},
"versionId": "a11c8289-d0f2-430d-995b-004ea59f10d9",
"connections": {
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"node": "Merge PRD and Test Case",
"type": "main",
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]
]
},
"7aa1d0eb-a145-4713-b12c-72d757924ef1": {
"ai_languageModel": [
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"type": "ai_languageModel",
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}
}이 워크플로우를 어떻게 사용하나요?
위의 JSON 구성 코드를 복사하여 n8n 인스턴스에서 새 워크플로우를 생성하고 "JSON에서 가져오기"를 선택한 후, 구성을 붙여넣고 필요에 따라 인증 설정을 수정하세요.
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중급 - 문서 추출, 멀티모달 AI
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이 워크플로우는 완전히 무료이며 직접 가져와 사용할 수 있습니다. 다만, 워크플로우에서 사용하는 타사 서비스(예: OpenAI API)는 사용자 직접 비용을 지불해야 할 수 있습니다.
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Alok Kumar
@alokkumarI am a Principal Software Engineer based in Ireland with a deep passion for AI and emerging technologies. With extensive experience in designing and implementing scalable software solutions, I focus on leveraging artificial intelligence to solve real-world problems. I enjoy exploring innovative applications of AI, from intelligent automation to data-driven insights, and I’m dedicated to building systems that are both efficient and impactful.
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