zhongwei/gh-jeremylongshore-claude-code-plugins-plus-plugins-ai-agency-make-scenario-builder
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity
Files
e9a9312d9061296c7220b93e94633f3d24404584
gh-jeremylongshore-claude-c…/commands/make-builder.md
Zhongwei Li e9a9312d90 Initial commit
2025-11-29 18:50:41 +08:00

7.0 KiB
Raw Blame History

description
description
Design Make.com scenarios with AI assistance

Make.com Scenario Builder

Create visual Make.com automation scenarios with detailed module configuration.

Usage

When the user requests a Make.com scenario, design a complete visual workflow with module-by-module instructions.

Scenario Templates

1. AI Email Auto-Responder

Flow:

Gmail: Watch emails
  → OpenAI: Generate response
  → Gmail: Send email
  → Google Sheets: Log conversation

Module Configuration:

  1. Gmail: Watch emails

    • Connection: Your Gmail
    • Folder: INBOX
    • Criteria: Unread messages
    • Max results: 10

  2. OpenAI: Create completion

    • Connection: Your OpenAI API
    • Model: gpt-4
    • Max tokens: 500
    • Temperature: 0.7
    • Prompt: Draft a professional response to:\n\nFrom: {{1.from}}\nSubject: {{1.subject}}\nBody: {{1.textPlain}}

  3. Gmail: Send an email

    • To: {{1.from}}
    • Subject: Re: {{1.subject}}
    • Content: {{2.choices[0].message.content}}

  4. Google Sheets: Add a row

    • Spreadsheet: Email Log
    • Sheet: Responses
    • From: {{1.from}}
    • Subject: {{1.subject}}
    • Response: {{2.choices[0].message.content}}
    • Date: {{now}}

2. Lead Qualification with AI

Flow:

Webhook: Custom webhook
  → OpenAI: Score lead
  → Router:
     ├─ High score → Slack notification + HubSpot deal
     ├─ Medium score → Email nurture
     └─ Low score → Archive to Airtable

Module Configuration:

  1. Webhook

    • Create a custom webhook
    • Expected data: name, email, company, role, budget

  2. OpenAI: Create completion

    • 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.
    • Parse: Use Text parser to extract number

  3. Router

    • Route 1 Filter: {{3.score}} Greater than 70
    • Route 2 Filter: {{3.score}} Between 40 and 70
    • Fallback: All other cases

4A. Slack: Create a message (High route)

  • Channel: #sales-leads
  • Text: Hot lead: {{1.name}} from {{1.company}} - Score: {{3.score}}

4B. HubSpot: Create a deal (High route)

  • Deal name: {{1.company}} - {{1.name}}
  • Stage: Qualification
  • Amount: {{1.budget}}

  1. ActiveCampaign: Add contact to list (Medium route)

    • Email: {{1.email}}
    • List: Nurture Campaign
    • Tags: medium-priority,{{1.role}}

  2. Airtable: Create a record (Low route)

    • Base: Leads
    • Table: Archived
    • Fields: Map all lead data + score

3. Content Distribution Pipeline

Flow:

RSS: Read feed
  → Filter: New items only
  → OpenAI: Rewrite for social
  → Iterator: For each platform
     ├─ Twitter: Post
     ├─ LinkedIn: Post
     └─ Facebook: Post

Module Configuration:

  1. RSS: Watch RSS feed items

    • URL: Your RSS feed
    • Maximum number of returned items: 5

  2. Filter

    • Condition: {{1.published}} After {{addHours(now; -24)}}
    • Label: "Only items from last 24 hours"

  3. OpenAI: Create completion

    • Prompt: Rewrite this article for social media (280 chars max):\n\nTitle: {{1.title}}\nContent: {{1.contentSnippet}}\n\nMake it engaging with relevant hashtags.

  4. Set multiple variables

    • platforms: ["twitter", "linkedin", "facebook"]
    • content: {{3.choices[0].message.content}}
    • link: {{1.link}}

  5. Iterator

    • Array: {{4.platforms}}

6A. Twitter: Create a tweet

  • Text: {{4.content}}\n\n{{4.link}}

6B. LinkedIn: Create a post

  • Text: {{4.content}}\n\n{{4.link}}

6C. Facebook: Create a post

  • Message: {{4.content}}
  • Link: {{4.link}}

4. Document Processing Workflow

Flow:

Google Drive: Watch files
  → Filter: PDFs only
  → OCR.space: Extract text
  → OpenAI: Summarize & extract data
  → Router:
     ├─ Success → Google Sheets: Log + Email summary
     └─ Error → Slack: Notify failure

Module Configuration:

  1. Google Drive: Watch files

    • Folder: Inbox
    • Types: application/pdf
    • Limit: 10

  2. Filter

    • Condition: File name contains "invoice" OR "receipt"

  3. HTTP: Make a request (OCR.space)

  4. OpenAI: Create completion

    • Prompt: Extract structured data from this document:\n\n{{3.ParsedResults[0].ParsedText}}\n\nProvide: Date, Amount, Vendor, Category
    • Format: JSON mode

  5. Google Sheets: Add a row

    • Spreadsheet: Document Log
    • Date: {{4.date}}
    • Amount: {{4.amount}}
    • Vendor: {{4.vendor}}
    • Category: {{4.category}}

  6. Gmail: Send an email

Error Handler on all modules:

  • Slack: Send message to #errors channel

5. Customer Support Automation

Flow:

Zendesk: Watch tickets
  → OpenAI: Classify urgency + category
  → Router:
     ├─ Urgent → Assign to senior agent + Slack alert
     ├─ Normal → Assign to queue + Draft response
     └─ Low → Auto-respond with KB articles

Module Configuration:

  1. Zendesk: Watch tickets

    • Status: new
    • Limit: 20

  2. OpenAI: Create completion

    • 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

  3. Router

    • Route 1: Urgency = "high"
    • Route 2: Urgency = "medium"
    • Route 3: Urgency = "low"

4A. Zendesk: Update ticket (Urgent)

  • Priority: urgent
  • Assignee: Senior agent ID

4B. Slack: Create message (Urgent)

  • Channel: #support-urgent
  • Text: Urgent ticket: {{1.subject}} - {{1.ticket_id}}

  1. Zendesk: Update ticket (Normal)

    • Priority: normal
    • Comment: {{2.suggested_response}}
    • Status: pending

  2. Zendesk: Update ticket (Low)

    • Comment: Auto-generated response + KB links
    • Status: solved

Best Practices

  1. Always add error handlers to critical modules
  2. Use filters early to reduce operations
  3. Test with sample data before activating
  4. Monitor operations usage in Make dashboard
  5. Add notes to modules for documentation
  6. Use variables for reusable values
  7. Set up notifications for failures
  8. Clone scenarios before major changes

Output Format

When generating a scenario, provide:

## Scenario: [Name]

### Business Value
[What problem this solves]

### Visual Flow
[ASCII diagram or clear description]

### Module Configuration
[Detailed setup for each module]

### Data Mapping
[How data flows between modules]

### Testing Steps
1. [Step by step testing instructions]

### Cost Estimate
- Operations per execution: X
- Expected monthly runs: Y
- Total operations: Z
- Make plan needed: [Free/Core/Pro]

### Setup Time
Estimated: [X] minutes

This helps users implement Make.com scenarios quickly with clear, actionable instructions.

Reference in New Issue View Git Blame Copy Permalink