Make Builder
Design Make.com scenarios with AI assistance
- Type
- Slash Command
- Repository
- jeremylongshore/tons-of-skills-marketplace
- GitHub stars
- 2.8k
- License
- MIT
- Repo last updated
- Sep 27, 2026
What Make Builder is
Make Builder is a slash command published in the jeremylongshore/tons-of-skills-marketplace repository on GitHub, which has about 2.8k stars. The repository describes itself as: “Model-agnostic agent-skills platform with a harness-free canonical layer, verified adapters, and the ccpi package manager. Explore at tonsofskills.com.”
A slash command is a reusable prompt saved as a markdown file and run by typing its name after a slash. In Claude Code, custom commands have been merged into skills: a file in .claude/commands/ and a skill folder in .claude/skills/ both create the same kind of command, and existing command files keep working.
Make Builder gives you a repeatable way to run the same instructions without retyping them, optionally with arguments.
How to install Make Builder
Claude Code
- Download make-builder.md from the repository.
- Save it to ~/.claude/commands/ (all projects) or .claude/commands/ (one project). As a skill, you can instead save it as ~/.claude/skills/<name>/SKILL.md.
- Run it by typing / followed by its name.
Claude Cowork
- Turn the command into a skill: create a folder with the file saved as SKILL.md and zip it.
- In Customize → Skills, click +, then upload the ZIP.
- Run it from any task with / and the skill name.
New to extending Cowork? Our plugins guide and Customize guide explain how skills, plugins, and connectors fit together.
Inside the source file
An excerpt from plugins/ai-agency/make-scenario-builder/commands/make-builder.md, shared under the repository's MIT license. Read the full file on GitHub.
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 conversationModule Configuration:
- Gmail: Watch emails
- Connection: Your Gmail
- Folder: INBOX
- Criteria: Unread messages
- Max results: 10
- 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}}
- Gmail: Send an email
- To: {{1.from}}
- Subject: Re: {{1.subject}}
- Content: {{2.choices[0].message.content}}
- 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 AirtableModule Configuration:
- Webhook
- Create a custom webhook
- Expected data: name, email, company, role, budget
- 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
- 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}}
- ActiveCampaign: Add contact to list (Medium route)
- Email: {{1.email}}
- List: Nurture Campaign
- Tags: medium-priority,{{1.role}}
- 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: PostModule Configuration:
- RSS: Watch RSS feed items
- URL: Your RSS feed
- Maximum number of returned items: 5
- Filter
- Condition: {{1.published}} After {{addHours(now; -24)}}
- Label: "Only items from last 24 hours"
- 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.
- Set multiple variables
- platforms: ["twitter", "linkedin", "facebook"]
- content: {{3.choices[0].message.content}}
- link: {{1.link}}
- 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 failureModule Configuration:
- Google Drive: Watch files
- Folder: Inbox
- Types: application/pdf
- Limit: 10
- Filter
- Condition: File name contains "invoice" OR "receipt"
- HTTP: Make a request (OCR.space)
- URL:
- Method: POST
- Headers: apikey: YOUR_OCR_KEY
- Body: file: {{1.data}}
- 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
- Google Sheets: Add a row
- Spreadsheet: Document Log
- Date: {{4.date}}
- Amount: {{4.amount}}
- Vendor: {{4.vendor}}
- Category: {{4.category}}
- Gmail: Send an email
- To: [email protected]
- Subject: New document processed: {{1.name}}
- Body: Summary of extracted data
Error Handler on all modules:
Before you install
- Read the whole file first. Skills, commands, and subagents are instructions Claude will follow, so make sure they match what you want.
- Check which tools, scripts, or MCP servers it uses. Local servers and scripts run with your permissions.
- Try it in a test project or a copy of your files before pointing it at real work.
- Pin the version you tested, and review changes before updating.
- Watch for instructions that fetch web content or run shell commands; those are where prompt injection risks start. See our prompt injection guide.
FAQ
What is Make Builder?
Make Builder is a slash command for Claude Code and Claude Cowork from the jeremylongshore/tons-of-skills-marketplace repository on GitHub. Design Make.com scenarios with AI assistance
How do I install Make Builder in Claude Code?
Download make-builder.md from the repository. Save it to ~/.claude/commands/ (all projects) or .claude/commands/ (one project). As a skill, you can instead save it as ~/.claude/skills/<name>/SKILL.md. Run it by typing / followed by its name.
Can I use Make Builder in Claude Cowork?
Turn the command into a skill: create a folder with the file saved as SKILL.md and zip it. In Customize → Skills, click +, then upload the ZIP. Run it from any task with / and the skill name.
Is Make Builder safe to install?
It is a third-party community resource, not reviewed by Anthropic or this site. Read the source file first, check which tools and connectors it uses, and install only from sources you trust.
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