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Zhongwei Li
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commands/make-builder.md
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commands/make-builder.md
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---
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description: Design Make.com scenarios with AI assistance
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---
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# Make.com Scenario Builder
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Create visual Make.com automation scenarios with detailed module configuration.
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## Usage
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When the user requests a Make.com scenario, design a complete visual workflow with module-by-module instructions.
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## Scenario Templates
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### 1. AI Email Auto-Responder
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**Flow:**
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```
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Gmail: Watch emails
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→ OpenAI: Generate response
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→ Gmail: Send email
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→ Google Sheets: Log conversation
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```
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**Module Configuration:**
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1. **Gmail: Watch emails**
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- Connection: Your Gmail
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- Folder: INBOX
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- Criteria: Unread messages
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- Max results: 10
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2. **OpenAI: Create completion**
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- Connection: Your OpenAI API
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- Model: gpt-4
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- Max tokens: 500
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- Temperature: 0.7
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- Prompt: `Draft a professional response to:\n\nFrom: {{1.from}}\nSubject: {{1.subject}}\nBody: {{1.textPlain}}`
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3. **Gmail: Send an email**
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- To: `{{1.from}}`
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- Subject: `Re: {{1.subject}}`
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- Content: `{{2.choices[0].message.content}}`
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4. **Google Sheets: Add a row**
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- Spreadsheet: Email Log
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- Sheet: Responses
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- From: `{{1.from}}`
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- Subject: `{{1.subject}}`
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- Response: `{{2.choices[0].message.content}}`
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- Date: `{{now}}`
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### 2. Lead Qualification with AI
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**Flow:**
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```
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Webhook: Custom webhook
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→ OpenAI: Score lead
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→ Router:
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├─ High score → Slack notification + HubSpot deal
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├─ Medium score → Email nurture
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└─ Low score → Archive to Airtable
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```
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**Module Configuration:**
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1. **Webhook**
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- Create a custom webhook
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- Expected data: name, email, company, role, budget
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2. **OpenAI: Create completion**
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- Prompt: `Score this lead from 0-100:\nName: {{1.name}}\nCompany: {{1.company}}\nRole: {{1.role}}\nBudget: {{1.budget}}\n\nProvide only the numeric score.`
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- Parse: Use Text parser to extract number
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3. **Router**
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- Route 1 Filter: `{{3.score}}` Greater than `70`
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- Route 2 Filter: `{{3.score}}` Between `40` and `70`
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- Fallback: All other cases
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4A. **Slack: Create a message** (High route)
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- Channel: #sales-leads
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- Text: ` Hot lead: {{1.name}} from {{1.company}} - Score: {{3.score}}`
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4B. **HubSpot: Create a deal** (High route)
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- Deal name: `{{1.company}} - {{1.name}}`
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- Stage: Qualification
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- Amount: `{{1.budget}}`
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5. **ActiveCampaign: Add contact to list** (Medium route)
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- Email: `{{1.email}}`
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- List: Nurture Campaign
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- Tags: `medium-priority,{{1.role}}`
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6. **Airtable: Create a record** (Low route)
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- Base: Leads
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- Table: Archived
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- Fields: Map all lead data + score
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### 3. Content Distribution Pipeline
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**Flow:**
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```
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RSS: Read feed
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→ Filter: New items only
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→ OpenAI: Rewrite for social
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→ Iterator: For each platform
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├─ Twitter: Post
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├─ LinkedIn: Post
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└─ Facebook: Post
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```
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**Module Configuration:**
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1. **RSS: Watch RSS feed items**
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- URL: Your RSS feed
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- Maximum number of returned items: 5
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2. **Filter**
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- Condition: `{{1.published}}` After `{{addHours(now; -24)}}`
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- Label: "Only items from last 24 hours"
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3. **OpenAI: Create completion**
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- Prompt: `Rewrite this article for social media (280 chars max):\n\nTitle: {{1.title}}\nContent: {{1.contentSnippet}}\n\nMake it engaging with relevant hashtags.`
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4. **Set multiple variables**
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- platforms: `["twitter", "linkedin", "facebook"]`
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- content: `{{3.choices[0].message.content}}`
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- link: `{{1.link}}`
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5. **Iterator**
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- Array: `{{4.platforms}}`
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6A. **Twitter: Create a tweet**
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- Text: `{{4.content}}\n\n{{4.link}}`
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6B. **LinkedIn: Create a post**
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- Text: `{{4.content}}\n\n{{4.link}}`
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6C. **Facebook: Create a post**
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- Message: `{{4.content}}`
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- Link: `{{4.link}}`
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### 4. Document Processing Workflow
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**Flow:**
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```
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Google Drive: Watch files
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→ Filter: PDFs only
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→ OCR.space: Extract text
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→ OpenAI: Summarize & extract data
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→ Router:
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├─ Success → Google Sheets: Log + Email summary
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└─ Error → Slack: Notify failure
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```
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**Module Configuration:**
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1. **Google Drive: Watch files**
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- Folder: Inbox
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- Types: application/pdf
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- Limit: 10
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2. **Filter**
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- Condition: File name contains "invoice" OR "receipt"
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3. **HTTP: Make a request (OCR.space)**
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- URL: https://api.ocr.space/parse/image
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- Method: POST
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- Headers: apikey: YOUR_OCR_KEY
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- Body: file: `{{1.data}}`
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4. **OpenAI: Create completion**
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- Prompt: `Extract structured data from this document:\n\n{{3.ParsedResults[0].ParsedText}}\n\nProvide: Date, Amount, Vendor, Category`
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- Format: JSON mode
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5. **Google Sheets: Add a row**
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- Spreadsheet: Document Log
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- Date: `{{4.date}}`
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- Amount: `{{4.amount}}`
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- Vendor: `{{4.vendor}}`
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- Category: `{{4.category}}`
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6. **Gmail: Send an email**
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- To: accounting@company.com
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- Subject: New document processed: `{{1.name}}`
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- Body: Summary of extracted data
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**Error Handler on all modules:**
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- Slack: Send message to #errors channel
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### 5. Customer Support Automation
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**Flow:**
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```
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Zendesk: Watch tickets
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→ OpenAI: Classify urgency + category
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→ Router:
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├─ Urgent → Assign to senior agent + Slack alert
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├─ Normal → Assign to queue + Draft response
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└─ Low → Auto-respond with KB articles
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```
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**Module Configuration:**
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1. **Zendesk: Watch tickets**
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- Status: new
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- Limit: 20
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2. **OpenAI: Create completion**
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- Prompt: `Classify this support ticket:\n\nSubject: {{1.subject}}\nDescription: {{1.description}}\n\nProvide:\n1. Urgency (high/medium/low)\n2. Category (billing/technical/general)\n3. Suggested response`
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3. **Router**
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- Route 1: Urgency = "high"
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- Route 2: Urgency = "medium"
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- Route 3: Urgency = "low"
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4A. **Zendesk: Update ticket** (Urgent)
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- Priority: urgent
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- Assignee: Senior agent ID
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4B. **Slack: Create message** (Urgent)
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- Channel: #support-urgent
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- Text: ` Urgent ticket: {{1.subject}} - {{1.ticket_id}}`
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5. **Zendesk: Update ticket** (Normal)
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- Priority: normal
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- Comment: `{{2.suggested_response}}`
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- Status: pending
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6. **Zendesk: Update ticket** (Low)
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- Comment: Auto-generated response + KB links
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- Status: solved
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## Best Practices
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1. **Always add error handlers** to critical modules
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2. **Use filters early** to reduce operations
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3. **Test with sample data** before activating
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4. **Monitor operations usage** in Make dashboard
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5. **Add notes to modules** for documentation
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6. **Use variables** for reusable values
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7. **Set up notifications** for failures
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8. **Clone scenarios** before major changes
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## Output Format
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When generating a scenario, provide:
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```markdown
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## Scenario: [Name]
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### Business Value
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[What problem this solves]
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### Visual Flow
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[ASCII diagram or clear description]
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### Module Configuration
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[Detailed setup for each module]
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### Data Mapping
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[How data flows between modules]
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### Testing Steps
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1. [Step by step testing instructions]
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### Cost Estimate
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- Operations per execution: X
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- Expected monthly runs: Y
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- Total operations: Z
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- Make plan needed: [Free/Core/Pro]
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### Setup Time
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Estimated: [X] minutes
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```
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This helps users implement Make.com scenarios quickly with clear, actionable instructions.
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