Generar un esquema de base de datos completo para bases de datos SQL con el sistema multi-agente de Claude
Este es unautomatización que contiene 31 nodos.Utiliza principalmente nodos como If, Set, Form, Postgres, FormTrigger. Usar el sistema multiagente de Claude para generar un esquema de base de datos completo para bases de datos SQL
- •Información de conexión de la base de datos PostgreSQL
- •Clave de API de Anthropic
Nodos utilizados (31)
Categoría
{
"nodes": [
{
"id": "6372d515-3314-4ca8-acf4-462fb4e2fbb1",
"name": "Inicializar Variables",
"type": "n8n-nodes-base.set",
"position": [
-832,
-3104
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "init_iteration",
"name": "iteration_count",
"type": "number",
"value": 0
},
{
"id": "init_feedback",
"name": "previous_feedback",
"type": "string",
"value": "="
},
{
"id": "form_data",
"name": "form_data",
"type": "object",
"value": "={{ $json }}"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "e102d0ff-e176-49b5-a999-a3ccf2fb7f42",
"name": "Modelo de Arquitecto",
"type": "@n8n/n8n-nodes-langchain.lmChatAnthropic",
"position": [
-480,
-2880
],
"parameters": {
"model": {
"__rl": true,
"mode": "list",
"value": "claude-sonnet-4-5-20250929",
"cachedResultName": "Claude Sonnet 4.5"
},
"options": {
"topP": 0.9,
"temperature": 0.3
}
},
"credentials": {
"anthropicApi": {
"id": "rFsH3A7ko19Tb8xL",
"name": "Anthropic account"
}
},
"typeVersion": 1.3
},
{
"id": "1648a9d6-a261-45b8-8dc9-516fd62a7a3e",
"name": "Modelo de Revisor",
"type": "@n8n/n8n-nodes-langchain.lmChatAnthropic",
"position": [
-64,
-2944
],
"parameters": {
"model": {
"__rl": true,
"mode": "list",
"value": "claude-sonnet-4-5-20250929",
"cachedResultName": "Claude Sonnet 4.5"
},
"options": {
"topP": 0.85,
"temperature": 0.1
}
},
"credentials": {
"anthropicApi": {
"id": "rFsH3A7ko19Tb8xL",
"name": "Anthropic account"
}
},
"typeVersion": 1.3
},
{
"id": "87d374f8-babb-41f5-ac5c-f45be51df90c",
"name": "Modelo de Optimizador",
"type": "@n8n/n8n-nodes-langchain.lmChatAnthropic",
"position": [
320,
-2928
],
"parameters": {
"model": {
"__rl": true,
"mode": "list",
"value": "claude-sonnet-4-5-20250929",
"cachedResultName": "Claude Sonnet 4.5"
},
"options": {
"topP": 0.95,
"temperature": 0.5
}
},
"credentials": {
"anthropicApi": {
"id": "rFsH3A7ko19Tb8xL",
"name": "Anthropic account"
}
},
"typeVersion": 1.3
},
{
"id": "a5028fd9-b726-413b-86aa-9f3735395bb9",
"name": "Agente 1: Arquitecto de Base de Datos",
"type": "@n8n/n8n-nodes-langchain.agent",
"position": [
-544,
-3120
],
"parameters": {
"text": "=Database Requirements:\n- What they're building: {{ $json.form_data['What are you building?'] }}\n- Database Technology: {{ $json.form_data['Database Technology'] }}\n- Industry: {{ $json.form_data['Industry/Niche'] }}\n- Data to track: {{ $json.form_data['What data do you need to track?'] }}\n- Team size: {{ $json.form_data['Team Size'] }}\n- Expected scale: {{ $json.form_data['Expected Scale'] }}\n- Key workflows: {{ $json.form_data['Key Workflows'] }}\n- Integrations: {{ $json.form_data['Any integrations needed?'] }}\n- Special requirements: {{ $json.form_data['Special Requirements'] }}\n\n{{ $json.previous_feedback ? '⚠️ PREVIOUS DESIGN HAD ISSUES - ITERATION ' + ($json.iteration_count + 1) + '/3:\\n\\nPrevious Feedback:\\n' + $json.previous_feedback + '\\n\\nPlease redesign the schema addressing ALL the concerns mentioned above. Focus especially on CRITICAL and HIGH priority items.\\n\\n' : '' }}\n\nPlease design a complete {{ $json.form_data['Database Technology'] }} database schema for this use case. Output your design as structured JSON.",
"options": {
"systemMessage": "=You are a senior {{ $json.form_data['Database Technology'] }} database architect with 15+ years experience.\nYou design production-grade schemas that are scalable, normalized, and follow best practices. You consider performance, indexing, and future growth.\n\nOutput your design as structured JSON with:\n- tables: Array of table objects with:\n - name: string\n - columns: Array of {name, type, constraints, description}\n - primary_key: string or array\n - indexes: Array of {name, columns, type}\n - foreign_keys: Array of {column, references_table, references_column}\n- enums: Array of {name, values}\n- extensions: Array of extension names needed\n- relationships: Description of how tables relate\n- reasoning: Explanation for key design decisions\n\nBe thorough and production-ready. Consider the scale and requirements carefully."
},
"promptType": "define"
},
"typeVersion": 2.2
},
{
"id": "58921f8a-0b6f-460b-8202-69327c364d45",
"name": "Agente 2: Revisor de Esquema",
"type": "@n8n/n8n-nodes-langchain.agent",
"position": [
-144,
-3120
],
"parameters": {
"text": "=Original Requirements:\n{{ JSON.stringify($('Initialize Variables').item.json.form_data, null, 2) }}\n\nProposed Schema from Agent 1:\n{{ $('Agent 1: Database Architect').item.json.output }}\n\nPlease conduct a thorough review of this database schema design. Check for issues in normalization, indexing, data types, constraints, performance, scalability, and security.\n\nOutput structured feedback with severity levels: CRITICAL, HIGH, MEDIUM, LOW",
"options": {
"systemMessage": "You are a {{ $('Initialize Variables').item.json.form_data['Database Technology'] }} code reviewer and database optimization expert.\nYour job is to find issues, enforce best practices, and ensure production-readiness.\n\nReview checklist:\n- Normalization (3NF minimum, appropriate denormalization)\n- Indexing strategy (missing indexes? over-indexing?)\n- Data types (appropriate choices for the database type)\n- Constraints (missing NOT NULL? need CHECK constraints?)\n- Performance (N+1 query risks? missing composite indexes?)\n- Scalability (will this work at 10x, 100x scale?)\n- Security (sensitive data? need encryption? row-level security?)\n- Missing common fields (created_at, updated_at, soft deletes)\n- Relationships properly defined\n\nOutput structured feedback in this format:\n\nCRITICAL Issues:\n- [Issue 1]\n- [Issue 2]\n\nHIGH Priority:\n- [Issue 1]\n\nMEDIUM Priority:\n- [Issue 1]\n\nLOW Priority / Suggestions:\n- [Issue 1]\n\nPositive Aspects:\n- [Good thing 1]\n\nBe thorough but fair. If the design is solid, say so."
},
"promptType": "define"
},
"typeVersion": 2.2
},
{
"id": "4e2a9518-4587-4ffe-a4a0-3f771019f22e",
"name": "Agente 3: Optimizador y Evaluador",
"type": "@n8n/n8n-nodes-langchain.agent",
"position": [
272,
-3120
],
"parameters": {
"text": "=Original Requirements:\n{{ JSON.stringify($('Initialize Variables').item.json.form_data, null, 2) }}\n\nProposed Schema:\n{{ $('Agent 1: Database Architect').item.json.output }}\n\nReview Feedback:\n{{ $('Agent 2: Schema Reviewer').item.json.output }}\n\nPlease:\n1. Apply final polish and optimizations to the schema\n2. Add advanced features (materialized views, helper functions, useful views)\n3. Provide monitoring recommendations\n4. Create a comprehensive score card\n5. Generate implementation guidance\n\nScore each dimension 0-10 with justification. Be honest but constructive.",
"options": {
"systemMessage": "You are a {{ $('Initialize Variables').item.json.form_data['Database Technology'] }} performance optimizer and database strategist.\nApply final polish, add advanced features, and score the design holistically.\n\nAdd:\n- Performance optimizations (materialized views, covering indexes, partitioning if needed)\n- Developer experience improvements (useful views, helper functions)\n- Monitoring recommendations (what to track in production)\n- Migration strategy (how to deploy safely)\n- Backup and disaster recovery considerations\n\nCreate a comprehensive score card:\n\n📊 DATABASE ARCHITECTURE SCORE\n\nOverall Grade: [A+, A, A-, B+, B, B-, C+, C, C-, D, F] ([score]/100)\n\nDetailed Scores:\n━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\n\nSchema Design: [X]/10\n[Brief justification]\n\nPerformance: [X]/10\n[Brief justification]\n\nScalability: [X]/10\n[Brief justification]\n\nDeveloper Experience: [X]/10\n[Brief justification]\n\nProduction Readiness: [X]/10\n[Brief justification]\n\nSecurity: [X]/10\n[Brief justification]\n\n━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\n\n💪 Key Strengths:\n• [Strength 1]\n• [Strength 2]\n• [Strength 3]\n\n⚠️ Recommended Improvements:\n• [Improvement 1]\n• [Improvement 2]\n\n🚀 Next Steps:\n1. [Step 1]\n2. [Step 2]\n3. [Step 3]\n\nScore fairly but be honest. Grade A/B means production-ready, C means needs work, D/F means major issues."
},
"promptType": "define"
},
"typeVersion": 2.2
},
{
"id": "0b898ea5-9799-4b59-b26b-0b0521a8e2c6",
"name": "Seguimiento de Iteración",
"type": "n8n-nodes-base.set",
"position": [
608,
-2896
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "iteration",
"name": "iteration_count",
"type": "number",
"value": "={{ $('Initialize Variables').item.json.iteration_count + 1 }}"
},
{
"id": "feedback",
"name": "previous_feedback",
"type": "string",
"value": "={{ $('Agent 3: Optimizer & Scorer').item.json.output }}"
},
{
"id": "form_data_passthrough",
"name": "form_data",
"type": "object",
"value": "={{ $('Initialize Variables').item.json.form_data }}"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "21ea3c45-a89d-4f45-b044-958be52b13be",
"name": "Modelo Generador SQL",
"type": "@n8n/n8n-nodes-langchain.lmChatAnthropic",
"position": [
1248,
-2944
],
"parameters": {
"model": {
"__rl": true,
"mode": "list",
"value": "claude-sonnet-4-5-20250929",
"cachedResultName": "Claude Sonnet 4.5"
},
"options": {
"topP": 0.85,
"temperature": 0.2
}
},
"credentials": {
"anthropicApi": {
"id": "rFsH3A7ko19Tb8xL",
"name": "Anthropic account"
}
},
"typeVersion": 1.3
},
{
"id": "739b10a8-f533-403f-b71f-9095d982b669",
"name": "Agente 4: Generar Script SQL",
"type": "@n8n/n8n-nodes-langchain.agent",
"position": [
1232,
-3200
],
"parameters": {
"text": "=Database Technology: {{ $('Initialize Variables').item.json.form_data['Database Technology'] }}\n\nFinal Approved Schema:\n{{ $('Agent 1: Database Architect').item.json.output }}\n\nOptimizations and Enhancements:\n{{ $('Agent 3: Optimizer & Scorer').item.json.output }}\n\nPlease generate a complete, production-ready SQL migration script for {{ $('Initialize Variables').item.json.form_data['Database Technology'] }}.\n\nOutput ONLY the SQL script, no markdown formatting, no additional commentary.",
"options": {
"systemMessage": "=You are a {{ $('Initialize Variables').item.json.form_data['Database Technology'] }} SQL script generator.\n\nTake the database schema design and convert it into a complete, production-ready SQL migration script.\n\nYour output must:\n- Start with proper transaction handling (BEGIN; ... COMMIT;)\n- Include all necessary extensions (for PostgreSQL)\n- Create ENUMs before tables that use them\n- Create tables in correct dependency order (referenced tables first)\n- Add all indexes after table creation\n- Add all constraints and triggers\n- Include helpful comments explaining complex parts\n- Be idempotent where possible (IF NOT EXISTS clauses)\n- End with a commented-out rollback script\n\nFormat:\n-- ============================================\n-- Database Migration Script\n-- Generated: [timestamp]\n-- Database: {{ $('Initialize Variables').item.json.form_data['Database Technology'] }}\n-- ============================================\n\nBEGIN;\n\n[Your SQL here]\n\nCOMMIT;\n\n-- ============================================\n-- ROLLBACK SCRIPT (commented out)\n-- ============================================\n-- BEGIN;\n-- [DROP statements in reverse order]\n-- COMMIT;\n\nOutput ONLY the SQL script. No markdown code blocks, no explanations."
},
"promptType": "define"
},
"typeVersion": 2.2
},
{
"id": "509218a4-3447-49f9-a8bc-b789ba3432ec",
"name": "Respuesta de Éxito",
"type": "n8n-nodes-base.set",
"position": [
2320,
-3312
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "status",
"name": "execution_status",
"type": "string",
"value": "success"
},
{
"id": "message",
"name": "message",
"type": "string",
"value": "✅ Database created successfully!"
},
{
"id": "sql_script",
"name": "sql_script",
"type": "string",
"value": "={{ $('Agent 4: Generate SQL Script').item.json.output }}"
},
{
"id": "schema_design",
"name": "schema_design",
"type": "string",
"value": "={{ $('Agent 1: Database Architect').item.json.output }}"
},
{
"id": "review_feedback",
"name": "review_feedback",
"type": "string",
"value": "={{ $('Agent 2: Schema Reviewer').item.json.output }}"
},
{
"id": "score_card",
"name": "score_card",
"type": "string",
"value": "={{ $('Agent 3: Optimizer & Scorer').item.json.output }}"
},
{
"id": "iterations",
"name": "iterations_needed",
"type": "number",
"value": "={{ $('Initialize Variables').item.json.iteration_count }}"
},
{
"id": "database_tech",
"name": "database_technology",
"type": "string",
"value": "={{ $('Initialize Variables').item.json.form_data['Database Technology'] }}"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "fa2b059f-7347-4c81-a194-4e7b02e0a033",
"name": "Respuesta de Error",
"type": "n8n-nodes-base.set",
"position": [
2320,
-3088
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "status",
"name": "execution_status",
"type": "string",
"value": "failed"
},
{
"id": "message",
"name": "message",
"type": "string",
"value": "⚠️ SQL script generated but execution failed. You can still use the script manually."
},
{
"id": "error",
"name": "sql_error",
"type": "string",
"value": "={{ $('Execute SQL in PostgreSQL').item.json.error }}"
},
{
"id": "sql_script",
"name": "sql_script",
"type": "string",
"value": "={{ $('Agent 4: Generate SQL Script').item.json.output }}"
},
{
"id": "schema_design",
"name": "schema_design",
"type": "string",
"value": "={{ $('Agent 1: Database Architect').item.json.output }}"
},
{
"id": "review_feedback",
"name": "review_feedback",
"type": "string",
"value": "={{ $('Agent 2: Schema Reviewer').item.json.output }}"
},
{
"id": "score_card",
"name": "score_card",
"type": "string",
"value": "={{ $('Agent 3: Optimizer & Scorer').item.json.output }}"
},
{
"id": "iterations",
"name": "iterations_needed",
"type": "number",
"value": "={{ $('Initialize Variables').item.json.iteration_count }}"
},
{
"id": "database_tech",
"name": "database_technology",
"type": "string",
"value": "={{ $('Initialize Variables').item.json.form_data['Database Technology'] }}"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "0b8ee65f-e057-4e2e-93c4-859797612c93",
"name": "Máximo de Iteraciones Alcanzado",
"type": "n8n-nodes-base.set",
"position": [
1024,
-3024
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "max_iterations_msg",
"name": "message",
"type": "string",
"value": "⚠️ Reached maximum iterations (3). Proceeding with best available design."
},
{
"id": "passthrough_iteration",
"name": "iteration_count",
"type": "number",
"value": "={{ $json.iteration_count }}"
},
{
"id": "passthrough_form",
"name": "form_data",
"type": "object",
"value": "={{ $json.form_data }}"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "ccef25b6-60e3-408e-8d2f-dbc9d907bcc4",
"name": "¿Es Puntuación A o B?",
"type": "n8n-nodes-base.if",
"position": [
672,
-3168
],
"parameters": {
"options": {},
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "fdbb64c0-d9c9-4568-8aec-2e7679ae846f",
"operator": {
"type": "string",
"operation": "regex"
},
"leftValue": "={{ $json.output }}",
"rightValue": "Overall Grade: [AB][+-]?"
}
]
}
},
"typeVersion": 2.2
},
{
"id": "b25d8d4c-46dc-4a65-99a3-3c03a4ba819c",
"name": "¿Se Puede Reintentar?",
"type": "n8n-nodes-base.if",
"position": [
832,
-2848
],
"parameters": {
"options": {},
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "fdbb64c0-d9c9-4568-8aec-2e7679ae846f",
"operator": {
"type": "number",
"operation": "lte"
},
"leftValue": "={{ $json.iteration_count }}",
"rightValue": 3
}
]
}
},
"typeVersion": 2.2
},
{
"id": "c8d4da4b-62af-4d22-8bab-ddfca874ed72",
"name": "Formulario",
"type": "n8n-nodes-base.form",
"position": [
2608,
-3184
],
"webhookId": "0ef42fe9-17ab-4887-b49b-e889d2056d87",
"parameters": {
"options": {},
"operation": "completion",
"completionTitle": "SQL Creation Finished",
"completionMessage": "={{ $json }}"
},
"typeVersion": 2.3
},
{
"id": "e5fbeabe-a5de-492e-8cbe-6849882db5fc",
"name": "Ejecutar SQL en PostgreSQL",
"type": "n8n-nodes-base.postgres",
"onError": "continueErrorOutput",
"position": [
2000,
-3200
],
"parameters": {
"query": "{{ $json.output }}",
"options": {},
"operation": "executeQuery"
},
"credentials": {
"postgres": {
"id": "pYPv5XduSxmDtomy",
"name": "Postgres account"
}
},
"typeVersion": 2.6
},
{
"id": "146b4b49-a91a-4280-8e2e-74f54f40c9ac",
"name": "Nota Adhesiva",
"type": "n8n-nodes-base.stickyNote",
"position": [
-1728,
-3104
],
"parameters": {
"color": 7,
"width": 528,
"height": 256,
"content": "## 📝 Form Intake\n**User fills database requirements**\n\n⚙️ **Customization Options:**\n- Add more fields for specific industries\n- Add file upload for existing schema\n- Add budget field for pricing tiers\n- Collect company name for personalization\n\n💡 **Tip:** The more detailed the input, the better the AI agents perform!"
},
"typeVersion": 1
},
{
"id": "c707c920-7fda-4fb0-a175-e6ab1aed64f8",
"name": "Nota Adhesiva1",
"type": "n8n-nodes-base.stickyNote",
"position": [
-1200,
-3424
],
"parameters": {
"color": 4,
"width": 352,
"height": 240,
"content": "## 🔧 Setup Phase\n**Prepares data for agent pipeline**\n\n⚙️ **Customization:**\n- Store user data in CRM here\n- Log to analytics (Mixpanel/Segment)\n- Add user identification/tracking\n\n🎯 **Purpose:** Enables retry loop with context"
},
"typeVersion": 1
},
{
"id": "b375bb08-5363-463d-b34a-76e98eff5443",
"name": "Nota Adhesiva2",
"type": "n8n-nodes-base.stickyNote",
"position": [
-672,
-3488
],
"parameters": {
"color": 7,
"width": 352,
"height": 320,
"content": "## 🤖 Agent 1: Architect\n**Creates initial schema design**\n\n⚙️ **Model Config:**\n- Temp: 0.3 (creative but consistent)\n- Max tokens: 4000\n\n🎨 **Customization:**\n- Switch to GPT-4 for cost savings\n- Increase temperature for creative solutions\n- Add industry-specific templates\n\n📊 **Expected time:** 30-45 seconds"
},
"typeVersion": 1
},
{
"id": "3d373fbc-87de-42c2-82e1-536bc7550cef",
"name": "Nota Adhesiva3",
"type": "n8n-nodes-base.stickyNote",
"position": [
-256,
-3488
],
"parameters": {
"color": 7,
"width": 336,
"height": 320,
"content": "## 🤖 Agent 2: Reviewer\n**Quality control & validation**\n\n⚙️ **Model Config:**\n- Temp: 0.1 (strict & analytical)\n- Max tokens: 3000\n\n🎨 **Customization:**\n- Add compliance checks (GDPR, HIPAA)\n- Add industry-specific validations\n- Integrate with linting tools\n\n⚡ **Expected time:** 20-30 seconds"
},
"typeVersion": 1
},
{
"id": "28deacd5-06af-4ec2-b77b-823354b9e306",
"name": "Nota Adhesiva4",
"type": "n8n-nodes-base.stickyNote",
"position": [
160,
-3488
],
"parameters": {
"color": 7,
"width": 336,
"height": 320,
"content": "## 🤖 Agent 3: Optimizer\n**Final polish & scoring**\n\n⚙️ **Model Config:**\n- Temp: 0.5 (balanced creativity)\n- Max tokens: 3500\n\n🎨 **Customization:**\n- Adjust scoring criteria\n- Add performance benchmarking\n- Custom grading rubrics per industry\n\n🎯 **Outputs:** Score card + enhancements"
},
"typeVersion": 1
},
{
"id": "b71dce06-6436-446f-8d77-b0f5c46e87e1",
"name": "Nota Adhesiva5",
"type": "n8n-nodes-base.stickyNote",
"position": [
624,
-3536
],
"parameters": {
"color": 7,
"width": 432,
"height": 336,
"content": "## 🔄 Quality Gate\n**Ensures high-quality output**\n\n⚙️ **Current Logic:**\n- A/B grades → Proceed ✅\n- C/D/F grades → Retry (max 3x)\n\n🎨 **Customization:**\n- Change threshold (accept C+?)\n- Add manual approval step\n- Send low scores to human review\n- Adjust max retries (1-5)\n\n💰 **Trade-off:** More retries = higher cost but better quality"
},
"typeVersion": 1
},
{
"id": "2a05b10e-906c-4be7-919e-b22d74ac15cb",
"name": "Nota Adhesiva6",
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"content": "## 🔁 Retry Loop\n**Iterative improvement system**\n\n⚙️ **Current:** Max 3 attempts\n\n🎨 **Customization:**\n- Increase max retries for complex projects\n- Add different agents for retries\n- Implement escalation (retry with Opus)\n- Track retry metrics for optimization\n\n📊 **Insight:** Most designs pass in 1-2 iterations"
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"content": "## 🤖 Agent 4: SQL Generator\n**Converts schema to executable SQL**\n\n⚙️ **Model Config:**\n- Temp: 0.2 (precision critical)\n- Max tokens: 4000\n\n🎨 **Customization:**\n- Add migration versioning (Flyway/Liquibase)\n- Generate ORM models (Prisma schema)\n- Add seed data generation\n- Support multiple SQL dialects\n\n💾 **Output:** Production-ready SQL script"
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"content": "## ✅ Execution Validation\n**Handles success & failures gracefully**\n\n⚙️ **Current Behavior:**\n- Success → Full response\n- Failure → Script + error details\n\n🎨 **Customization:**\n- Retry failed SQL automatically\n- Send errors to monitoring (Sentry)\n- Trigger webhook on success\n- Add rollback capability\n\n🎯 **User always gets usable output**"
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"content": "## 🚀 Workflow Overview\n**AI Database Architect - Multi-Agent System**\n\n📊 **Performance:**\n- Average time: 60-90 seconds\n- Success rate: ~85% first attempt\n- Cost per run: ~$0.15-0.30\n\n🎯 **Conversion Strategy:**\n1. Free: Blueprint + Score\n2. Paid: Implementation + 3 automations\n3. Enterprise: Full setup + optimization\n\n📈 **Optimization Ideas:**\n- A/B test agent prompts\n- Cache common patterns\n- Pre-built templates for industries\n- Parallel agent execution\n\n💡 **Track:** Completion rate, avg score, retry count"
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"content": "## Query Execute\n\nIf you are using **PostgreSQL** this will automatically run the script on your database"
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"fieldLabel": "Team Size",
"placeholder": "5"
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"placeholder": "e.g. lead comes in → assign to agent → track showings → close deal → commission calculation"
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"fieldLabel": "Special Requirements",
"placeholder": "multi-language, file uploads, complex relationships, audit logging, etc."
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}¿Cómo usar este flujo de trabajo?
Copie el código de configuración JSON de arriba, cree un nuevo flujo de trabajo en su instancia de n8n y seleccione "Importar desde JSON", pegue la configuración y luego modifique la configuración de credenciales según sea necesario.
¿En qué escenarios es adecuado este flujo de trabajo?
Avanzado
¿Es de pago?
Este flujo de trabajo es completamente gratuito, puede importarlo y usarlo directamente. Sin embargo, tenga en cuenta que los servicios de terceros utilizados en el flujo de trabajo (como la API de OpenAI) pueden requerir un pago por su cuenta.
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Evervise
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