Claude can now use Skills to improve how it performs specific tasks. Skills are folders that include instructions, scripts, and resources that Claude can load when needed.

Claude will only access a skill when it’s relevant to the task at hand. When used, skills make Claude better at specialized tasks like working with Excel or following your organization’s brand guidelines.

101 Real-World Uses for Agent Skills

Productivity & Workflows

1. Auto-summarize daily Slack standups.

2. Convert raw meeting notes into client-ready summaries.

3. Apply your company’s brand voice to all written outputs.

4. Generate task lists from long project updates.

5. Create custom templates for proposals and decks.

6. Sync Claude with Google Drive folder structures.

7. Detect deadlines from chat messages and add to calendar.

8. Generate daily recap emails from multiple channels.

9. Auto-organize Notion pages by topic or team.

10. Create onboarding docs customized for new hires.

Marketing & Growth

11. Write copy following your brand tone (preloaded Skill).

12. Create ad copy variants based on audience personas.

13. Generate influencer outreach scripts.

14. Summarize social comments into insights.

15. Tag social mentions by sentiment and intent.

16. Draft newsletters from blog RSS feeds.

17. Auto-format LinkedIn carousels or captions.

18. Localize marketing content into multiple languages.

19. A/B test subject lines automatically.

20. Write and format press releases using company templates.

Sales & GTM

21. Build cold email sequences from account data.

22. Score prospects using AI enrichment.

23. Auto-fill CRM fields from notes or LinkedIn exports.

24. Generate call recap summaries with next steps.

25. Personalize follow-ups based on buyer intent.

26. Create territory and ICP-specific pitch decks.

27. Analyze competitor sales materials for tone.

28. Generate summaries from call transcripts (using Claude Code).

29. Draft proposal PDFs using preloaded skill templates.

30. Recommend next-step actions for each opportunity stage.

Finance & Operations

31. Build auto-updating financial dashboards.

32. Generate expense reports from receipts.

33. Automate invoice creation with templates.

34. Convert CSVs to summarized Excel dashboards.

35. Detect budget anomalies from uploaded sheets.

36. Forecast spend patterns with embedded code.

37. Write procurement summaries for approvals.

38. Standardize vendor contract summaries.

39. Build macros for recurring financial tasks.

40. Sync daily finance updates to Slack or email.

Technical Teams & Engineering

41. Load engineering playbooks on command.

42. Auto-generate test cases from PR descriptions.

43. Create release notes automatically.

44. Transform bug reports into JIRA tickets.

45. Integrate Claude Code with GitHub Actions.

46. Review and comment on pull requests with team-specific rules.

47. Build CLI tools using Claude-generated scripts.

48. Simulate error resolutions using logs.

49. Create architecture diagrams from text.

50. Generate documentation updates post-release.

Claude Code + API

51. Manage skill versions programmatically via /v1/skills.

52. Embed API key instructions within skills securely.

53. Use Claude Code to test executable snippets safely.

54. Package your team’s automation recipes into deployable skills.

55. Auto-document code repositories.

56. Translate pseudocode to working scripts.

57. Run spreadsheet automation directly from API calls.

58. Integrate Skills into your MCP or agent pipelines.

59. Share custom workflows as team-accessible Claude Skills.

60. Build internal toolchains without traditional coding.

Data Analysis & Research

61. Auto-clean CSVs and detect missing values.

62. Generate visual summaries from Excel data.

63. Write and run SQL queries automatically.

64. Create AI-assisted dashboards from prompts.

65. Detect trends in weekly metrics reports.

66. Generate executive summaries from long datasets.

67. Merge multiple data sources and deduplicate entries.

68. Convert research PDFs into key insight slides.

69. Categorize qualitative feedback automatically.

70. Apply machine learning predictions directly via Skills.

Personal Productivity

71. Summarize articles into 3-line takeaways.

72. Organize your reading list by topic.

73. Track your daily energy or productivity trends.

74. Auto-generate weekly reflection journal entries.

75. Rewrite emails politely but concisely.

76. Generate to-do lists from texts.

77. Schedule workout or meal plans.

78. Create trip itineraries from chat logs.

79. Budget personal expenses with Claude’s Excel Skill.

80. Create gratitude or journaling prompts.

Team Ops & HR

81. Generate job descriptions in your org’s tone.

82. Summarize interview notes into scorecards.

83. Auto-send onboarding sequences to new employees.

84. Create training modules using internal skill libraries.

85. Summarize performance reviews with sentiment analysis.

86. Generate policy documents automatically.

87. Auto-update employee handbooks.

88. Match roles to internal projects.

89. Analyze engagement surveys.

90. Generate internal newsletters.

Creative & Content Workflows

91. Brainstorm campaign ideas using stacked skills (Brand + Tone + Channel).

92. Create storyboard scripts for videos.

93. Generate caption banks for social media.

94. Create visual moodboards (with Claude Code).

95. Format podcast show notes.

96. Write blog outlines based on SEO keyword research.

97. Build publication-ready whitepapers.

98. Repurpose YouTube transcripts into carousels.

99. Auto-format design briefs for Figma.

100. Generate eBook drafts in your brand tone.

101. Create personal “voice skill” to make Claude write like you.

Getting Started

• For Individuals: Enable Skills in Settings → Labs → Skills.

• For Teams: Ask your admin to activate Skills organization-wide.

• For Developers: Explore the /v1/skills endpoint and Claude Console.

Final Thought

Agent Skills are Claude’s bridge between AI intuition and operational precision.
Once your workflows are captured as skills, Claude becomes more than an assistant — it becomes an extension of your organization’s collective expertise.

We’ve all been there — sitting on a massive lead list that looked great last quarter but now feels like a graveyard.
People switch jobs. Titles change. Companies pivot.

And somehow, marketing ops is always chasing accuracy that’s already gone.

But here’s something interesting I’ve been testing —
a new AI Marketing Ops Agent from Warmly that quietly keeps your prospect universe fresh.

It’s not another enrichment tool or data vendor.
It’s more like a smart sidekick that keeps learning who your best buyers actually are — and keeps updating your list as things change.

It starts with rethinking your ICP

Most of us define ICPs with demographics and firmographics:
industry, team size, location, tech stack… the usual suspects.

But that’s like describing someone’s LinkedIn profile without knowing how they behave.

Warmly takes a different route — it uses AI to learn from your best customers.
Who they are. What triggers their buying moment.
Which signals (hires, funding, activity) precede a deal.

It then turns that insight into a self-improving scoring model —
so instead of you finding prospects, the system keeps surfacing them for you.

From accounts → to actual people

Because let’s be honest — “target accounts” don’t buy.
People inside them do.

Warmly automatically identifies your buying committees —
the 3–5 decision makers who actually influence the sale.

No more guessing who to reach out to or syncing across SDRs and marketers to find “the right person.”
It just shows you who’s relevant, right now, in each account.

And it doesn’t go stale

The best part? It’s live.

Warmly constantly tracks 1st, 2nd, and 3rd-party intent signals —
everything from product research activity to new funding, to hiring spikes —
and automatically prioritizes leads based on what’s happening this week.

So when something shifts, your lists and playbooks shift too.
No manual cleanup. No spreadsheets. No Slack messages asking “is this lead still valid?”

I think what’s really powerful here isn’t the automation itself — it’s the mental space it frees up.
Instead of maintaining a list, you start working from a living system that keeps learning.

And if you’ve ever felt like marketing ops is half maintenance, half detective work —
this feels like a small step toward peace.

Here’s where you can check it out if you’re curious: Warmly →

In this post, you will see how easy it is to build an AI agent on Activepieces, use it in your flows, and also chain multiple agents together

How To Build An AI Agent on Activepieces

Step 1: Sign up on Activepieces

Step 2: Go to your dashboard and select Agents on the left side

Step 3: Click on New Agent

This is where the building begins

Step 4: Give your Agent a name and description

Step 5: Type in your instructions

Step 6: Click on Add Tool and select either From Piece (To choose from over 320 available integrations) or From Flow (To convert your flows to tools that your AI agents can use)

Now your AI agent is ready 😎

To automatically use it as a specialized chatbot with a chat interface, click on Use Agent

How To Add Your AI Agent to Your Flow

Adding an agent to your flow in Activepieces is the same as adding a new step/tool to your flow

Here is an example of adding an SEO blog writing agent to your flow

I already have the built-out SEO flow here (this part conducts the keyword research), so the AI agent needs to be added in the last step to collect all the keyword research information and write the blog draft .

(NB: AI agents can be added to any step in your workflow)

To add an AI agent

• Step 1: Click on the plus (+) sign to add a new step

• Step 2: Click on AI and Agents and select from any agent you have already built.

Step 3: Give your AI agent a prompt

You can also create a new agent at any step while building your flow by selecting “Create Agent” if you dont already have the agent created

How To Chain Multiple Agents

This is also the same way as adding steps to your flows

Step 1: Click the plus (+) sign

Step 2: Select AI and agents

Step 3: Select the agent you want to chain to your previous one

You can chain AI agents at any point in your workflow

This guide walks you through how to set up a ChatGPT AI Agent that connects to Facebook Ads via MCP (Model Context Protocol) and syncs performance data automatically — without manual exports or dashboards.

Once set up, you’ll be able to ask:

“Show me what campaigns drove the best ROAS last month.”

The agent instantly creates visual reports, compares campaign performance, and even recommends next steps. Then, you’ll integrate it with Omnisend to bring your Email + SMS data into the same ecosystem — giving you a unified view of ad and retention metrics.

🧠 What This Agent Can Do

• Pull live campaign data from Facebook Ads

• Visualize ROAS, CTR, CPC, and CPA instantly

• Compare performance across time periods or audiences

• Auto-generate performance summaries and recommendations

• Combine Facebook Ads and Omnisend reports into unified dashboards

• Execute campaign-level actions based on insights

⚙️ Step 1: Connect Facebook Ads via MCP

1. Go to your MCP Server (e.g. Agentpass or your hosted MCP).

2. Install the Facebook Ads Connector.

3. Authenticate with your Facebook Business Account.

4. Add access tokens for the Ad Accounts you want to monitor.

5. Test the connection by running the command:

/facebook get_campaigns

1. You should see a list of campaigns with IDs and spend data.

📊 Step 2: Create the ChatGPT Agent

1. In your MCP dashboard, click Create New Agent.

2. Name it something like Facebook Ads Analyst.

3. Under “Connected Data Sources”, select Facebook Ads.

4. Set the agent’s personality/instructions:

You are a performance marketing analyst.
Your job is to analyze Facebook ad performance and summarize insights.
Always visualize key metrics and recommend 2-3 next steps.

1. Save and deploy the agent.

Now you can prompt it:

“Compare ROAS and CPC across my top 5 campaigns this quarter.”

🔄 Step 3: Integrate Omnisend

Omnisend allows you to connect Email + SMS metrics with your ads data.

1. Create a free Omnisend account here.

2. Use the MCP Omnisend connector or API key to sync metrics.

3. Connect the same ChatGPT Agent to Omnisend.

4. Use a combined query, e.g.:

“Compare email open rates vs. Facebook CTR last month.”

This lets the agent analyze both datasets together and tell you what’s truly driving conversions.

💥 Why Omnisend

Bonus free tier:

• 250 contacts

• 500 emails/month

• 60 SMS (one-time)

• 500 web push notifications/month

Why use it:

• 💰 $68 ROI per $1 spent — proven eCommerce efficiency

• 💡 Enterprise features, startup pricing

• 🌍 Global SMS + 24/7 support

• 🛠️ Trusted by 150,000+ businesses (4.7⭐ rating)

🧩 Step 4: Automate Insights + Reports

Once connected, your ChatGPT agent can:

• Pull Facebook + Omnisend data automatically

• Generate charts for performance overview

• Write short summaries like:

“Campaign A outperformed Campaign B by 22% ROAS. Email open rate correlated with ad engagement spikes on weekends.”

• Suggest next steps:

“Scale Campaign A budget by 10%. Test weekend-only sends for top Omnisend segment.”

🗣️ Example Prompts

• “Show me ROAS and spend trends for the last 30 days.”

• “Which Omnisend segments convert best after seeing Facebook ads?”

• “Generate a weekly performance summary for both channels.”

• “Visualize CTR vs. open rate correlation.”

🔗 Bonus: One-Command Report Setup

Use this command inside ChatGPT (once MCP + Omnisend are linked):

/run report performance last_month

It’ll pull your ads + Omnisend data, visualize key metrics, and suggest optimizations — in seconds.

✅ Final Outcome

You now have:

• A ChatGPT AI Agent acting as a full-time ads analyst.

• Seamless Facebook Ads + Omnisend integration via MCP.

• Real-time insights and reports, zero dashboards.

Goal: Create an AI Agent that runs your full GTM stack — lead finding, social listening, inbound handling, and multi-channel outreach — automatically.

⚙️ Step 1: Create Your Replit Agent Workspace

1. Go to replit.com and click “Create Repl.”

2. Choose AI Agent as the project type.

3. Name it something like GTM_Agent or LeadOps_Assistant.

4. Inside, you’ll see a blank agent flow and an “Add Connector” option.

🔌 Step 2: Understand Connectors

Connectors = pre-built integrations that let your agent talk to apps instantly.
No APIs. No dev accounts. Just log in once.

Before Connectors

You’d have to:

• Get developer credentials

• Add API keys

• Wait for integrations to build manually

After Connectors

Now you:

• Ask your agent: “Connect to LinkedIn”

• Log in → Agent gets instant access to your data

• Start building workflows on top of it

🧩 Step 3: Add the Core Connectors

Log into each one via Replit’s Connectors tab:

Use CaseConnectorWhat It DoesLead sourcingReddit / Quora / TelegramFinds and listens to intent conversationsInbound handlingLinkedInReplies, DMs, and organizes inboundOutreachGmail / Cold Email ToolSends automated cold emailsFunnel opsSubstack + DiscordRuns multi-channel content + communityResearchGoogle Search / Notion / WebhooksGathers data + saves insights

🧠 Step 4: Design Your Agent Logic

Use plain English prompts to define your workflows.

Example:

When new post appears on Reddit about “lead generation tools”:
→ Summarize thread
→ Save usernames + context to Notion
→ Draft LinkedIn message for follow-up
→ Schedule cold email via Gmail

You can chain multiple actions like:

Reddit → Notion → LinkedIn → Gmail → Discord

This builds your end-to-end GTM funnel that runs 24/7.

🪄 Step 5: Train the Agent on Your Brand Voice

Feed your tone and messaging:

• Drop 3–5 of your previous posts or cold emails into the “Training” area

• Add a few “good vs. bad” message examples

• Give a short system instruction:

“You’re a GTM Operator who writes in a friendly, confident, and technical tone.”

Now the agent speaks like you.

📨 Step 6: Automate and Test

1. Hit Run Agent.

2. Ask: “Find 5 intent-based leads on Reddit about ‘CRM automation.’”

3. Watch it search, summarize, and queue messages.

4. Tweak logic until it fits your funnel perfectly.

💡 Step 7: Deploy for Continuous Operation

1. Click “Deploy Agent” → “Always On”.

2. Choose a name and set runtime preferences.

3. It’ll now:

   • Listen across channels

   • Collect & qualify leads

   • Message them

   • Update your Notion or CRM

Basically, your AI SDR team that never sleeps.

🗂️ Step 8: Optional — Export or Share

You can:

• Export the workflow as .repl file

• Share the public URL for demo access

• Clone and build different versions (Reddit-only agent, Email agent, etc.)

Discover powerful automation workflows from the N8N community and unlock GitHub's goldmine of workflow templates. Access thousands of ready-made solutions and contribute to the world's most collaborative automation ecosystem.

What is N8N Workflow Automation?

N8N is an open-source workflow automation platform that connects applications and services through visual node-based workflows. Unlike traditional automation tools, N8N offers complete transparency, unlimited customization, and community-driven development.

N8N Core Advantages:

Open Source Benefits:

• Full Code Access: Inspect, modify, and enhance any workflow logic

• No Vendor Lock-in: Deploy on your infrastructure with complete control

• Community Innovation: Benefit from global developer contributions

• Cost Efficiency: Scale without licensing restrictions or usage limits

Visual Workflow Design:

• Node-Based Interface: Drag-and-drop workflow creation

• Real-Time Testing: Execute and debug workflows step-by-step

• Data Transformation: Built-in functions for processing and formatting data

• Conditional Logic: Advanced branching and decision-making capabilities

Community Workflow Ecosystem

N8N Community Platform

The N8N community platform hosts over 3,200 automation workflows created by users worldwide, covering every imaginable business scenario and integration.

Community Features:

• Workflow Sharing: Users contribute their most effective automation solutions

• Use Case Documentation: Detailed explanations and implementation guides

• Rating System: Community validation of workflow quality and effectiveness

• Discussion Forums: Support, troubleshooting, and optimization tips

Popular Categories:

• Data Integration: Sync information between platforms and databases

• Social Media Management: Content scheduling, monitoring, and analytics

• E-commerce Operations: Order processing, inventory management, customer service

• Marketing Automation: Lead nurturing, email campaigns, customer journeys

• Business Intelligence: Reporting, analytics, and dashboard automation

🔄 Workflow Discovery Process

Search & Filter Options:

• By Integration: Find workflows for specific applications (Slack, Salesforce, etc.)

• By Industry: Discover solutions tailored to your business sector

• By Complexity: Filter from simple data transfers to complex business processes

• By Popularity: Access most-used and highly-rated community workflows

Implementation Approach:

1. Browse Community Library → 2. Select Relevant Workflow →
3. Review Documentation → 4. Import to N8N Instance →
5. Customize for Your Needs → 6. Test & Deploy

GitHub Resources: The Goldmine

Why GitHub N8N Resources Are Invaluable

GitHub repositories contain the most comprehensive, battle-tested, and innovative N8N workflows available anywhere. These resources represent real-world solutions developed by professionals and contributed by the community.

GitHub Advantages:

• Version Control: Track workflow evolution and improvements over time

• Documentation Quality: Detailed README files with setup and usage instructions

• Code Examples: Advanced techniques and custom function implementations

• Issue Tracking: Community support for troubleshooting and enhancements

• Fork & Contribute: Build upon existing workflows and share improvements

Featured GitHub Repositories

Primary Repositories:

1. n8n-free-templates

• Repository Owner: wassupjay

• Content Focus: Free, ready-to-use workflow templates

• Highlights: Business automation, data processing, notification systems

• Use Cases: Small to medium business operations, startup automation needs

2. awesome-n8n-templates

• Repository Owner: enescingoz

• Content Focus: Curated collection of advanced workflows

• Highlights: Complex integrations, enterprise-level solutions

• Use Cases: Advanced automation scenarios, multi-step business processes

Repository Benefits:

• Continuous Updates: Regular additions of new workflows and improvements

• Community Contributions: Multiple developers enhancing and expanding templates

• Real-World Testing: Workflows proven in production environments

• Comprehensive Documentation: Detailed setup guides and customization options

GitHub Repository Features

Template Organization:

• Category-Based Structure: Workflows organized by business function and use case

• Difficulty Levels: From beginner-friendly to expert-level implementations

• Integration Lists: Clear mapping of required applications and services

• Performance Notes: Execution time estimates and resource requirements

Documentation Standards:

Typical Repository Structure:
├── README.md (Overview and quick start guide)
├── workflows/ (JSON files for importing into N8N)
├── documentation/ (Detailed setup and customization guides)
├── examples/ (Sample data and test scenarios)
└── assets/ (Screenshots and workflow diagrams)

Implementation Strategies

Community Workflow Integration

Step-by-Step Process:

1. Explore Community Library: Browse workflows by category and use case

2. Evaluate Compatibility: Check required integrations and dependencies

3. Import Workflow: Download JSON file and import into your N8N instance

4. Configure Connections: Set up authentication for required applications

5. Customize Logic: Adapt workflow to match your specific business needs

6. Test Thoroughly: Validate all paths and error handling scenarios

Customization Areas:

• Data Mapping: Adjust field mappings between different applications

• Conditional Logic: Modify decision trees based on your business rules

• Error Handling: Implement appropriate fallback and notification procedures

• Scheduling: Configure trigger timing and frequency for your operations

GitHub Template Utilization

Repository Workflow:

1. Identify Need → 2. Search GitHub Repositories →
3. Review Code & Documentation → 4. Clone or Download →
5. Import to N8N → 6. Customize & Test → 7. Deploy & Monitor

Advanced Techniques:

• Fork Repositories: Create your own versions for organization-specific modifications

• Contribute Back: Share improvements and bug fixes with the community

• Issue Tracking: Report problems and request enhancements

• Collaboration: Work with repository maintainers on complex implementations

Workflow Categories & Applications

Business Operations

Core Automation Areas:

• Customer Relationship Management: Lead tracking, follow-up automation, deal progression

• Financial Operations: Invoice processing, expense tracking, payment reconciliation

• Human Resources: Onboarding workflows, time tracking, performance management

• Project Management: Task creation, status updates, milestone notifications

Implementation Examples:

• CRM Integration: Sync leads from website forms to Salesforce with automatic assignment

• Expense Processing: Extract data from receipts, categorize expenses, route for approval

• Employee Onboarding: Create accounts, send documentation, schedule training sessions

Marketing & Sales

Automation Opportunities:

• Lead Generation: Capture, qualify, and distribute leads across sales teams

• Email Marketing: Trigger campaigns based on user behavior and preferences

• Social Media: Schedule content, monitor mentions, track engagement metrics

• Analytics: Compile performance data from multiple platforms into unified reports

Advanced Workflows:

• Multi-Channel Campaigns: Coordinate email, social media, and advertising efforts

• Customer Journey Mapping: Track and optimize touchpoints throughout sales funnel

• Performance Attribution: Connect marketing activities to revenue outcomes

Data Management

Data Processing Workflows:

• ETL Operations: Extract, transform, and load data between systems

• Backup & Synchronization: Maintain data consistency across platforms

• Quality Control: Validate, clean, and standardize incoming data

• Reporting Automation: Generate and distribute regular business reports

Integration Scenarios:

• Database Synchronization: Keep customer data consistent across CRM, billing, and support systems

• API Data Processing: Transform and route data from third-party services

• File Management: Organize, process, and distribute documents automatically

Resource Access & Links

Official Community Platform

N8N Community Workflows

Access over 3,200 community-contributed workflows with detailed documentation, ratings, and implementation guides.

Browse N8N Community Workflows →

Featured GitHub Repositories

Primary Template Collections:

N8N Free Templates

• Repository: wassupjay/n8n-free-templates

• Focus: Ready-to-use business automation templates

• Content: CRM integration, data processing, notification systems

Awesome N8N Templates

• Repository: enescingoz/awesome-n8n-templates

• Focus: Advanced workflow solutions and enterprise patterns

• Content: Complex integrations, multi-step processes, custom functions

Additional Resources:

• N8N Official Documentation: Comprehensive guides and API references

• Community Forum: Support, discussions, and troubleshooting help

• Video Tutorials: Step-by-step implementation walkthroughs

• Integration Guides: Specific instructions for popular application connections

https://github.com/wassupjay/n8n-free-templates

https://github.com/enescingoz/awesome-n8n-templates

1. What You’ll Ship

• One brain, three channels

• Two-way chat: WhatsApp & SMS

• One-way nurture: Email via Omnisend

• Auto-tag, score, and trigger automations

• Human handoff when confidence is low

2. Minimal Stack

• WhatsApp: Twilio / 360dialog / Gupshup

• SMS: Twilio / Omnisend SMS

• Orchestrator: n8n

• Brain: OpenAI / Anthropic

• Lifecycle & Comms: Omnisend

• (Optional) Memory DB: Postgres / Notion

👉 Pro Tip: Ship v1 without memory—add it later.

3. Data Model (Contacts + Events)

Contact fields: phone, email, whatsapp_opt_in, sms_opt_in, first_name, source, lead_score, stage, interests
Custom events: conversation_started, intent_detected, resource_requested, handoff_requested, booking_link_clicked

📌 Events = clean triggers for Omnisend automations.

4. n8n Workflows

Flow A — Inbound Router (Core)

{
  "nodes": [
    { "name": "Webhook In", "type": "Webhook", "params": { "path": "twilio-inbound" } },
    { "name": "Parse Payload", "type": "Function", "params": { "code": "normalize and scrub PII" } },
    { "name": "LLM Reply", "type": "OpenAI", "params": { "prompt": "short helpful reply, detect intent" } },
    { "name": "Check Confidence", "type": "IF", "params": { "condition": "confidence >= 0.7" } },
    { "name": "Update Omnisend", "type": "HTTP Request", "params": { "method": "POST", "url": "https://api.omnisend.com/contacts" } },
    { "name": "Reply via Twilio", "type": "Twilio", "params": { "action": "sendMessage" } },
    { "name": "Human Handoff", "type": "Slack", "params": { "channel": "#handoff-alerts" } }
  ]
}

Flow B — Keyword Opt-in

{
  "nodes": [
    { "name": "Webhook In", "type": "Webhook", "params": { "path": "keyword-optin" } },
    { "name": "Check Keyword", "type": "Switch", "params": { "cases": ["NEWSLETTER","CHEATSHEET","VIDEO"] } },
    { "name": "Ask Email", "type": "Twilio", "params": { "message": "Drop your best email. 1 email/week. Reply STOP anytime." } },
    { "name": "Validate Email", "type": "Regex", "params": { "pattern": ".+@.+" } },
    { "name": "Update Omnisend", "type": "HTTP Request", "params": { "method": "PATCH", "url": "https://api.omnisend.com/contacts" } },
    { "name": "Trigger Event", "type": "HTTP Request", "params": { "url": "https://api.omnisend.com/events/resource_requested" } },
    { "name": "Deliver Asset", "type": "HTTP Request", "params": { "url": "https://api.omnisend.com/campaigns/send" } }
  ]
}

Flow C — Newsletter Sync

{
  "nodes": [
    { "name": "Get Campaign Stats", "type": "HTTP Request", "params": { "url": "https://api.omnisend.com/campaigns/stats" } },
    { "name": "Parse Opens/Clicks", "type": "Function", "params": { "code": "map metrics to contact IDs" } },
    { "name": "Update Contacts", "type": "HTTP Request", "params": { "method": "PATCH", "url": "https://api.omnisend.com/contacts" } },
    { "name": "Optional WhatsApp Summary", "type": "Twilio", "params": { "message": "Lite campaign summary" } }
  ]
}

5. Omnisend Setup That Matters

Segments:

• intent:newsletter

• intent:leadgen_workflow

• channel:whatsapp / sms

• high_intent (score ≥ 70)

Automations:

• Newsletter Welcome (E1 now, E2 D+2, E3 D+4 split)

• Lead Magnet Delivery (email + SMS nudge)

• Sales Assist (booking link + Slack alert)

6. Launch Checklist

☑️ Twilio WA/SMS webhooks live
☑️ n8n flows A/B/C deployed
☑️ Omnisend contacts + segments + events
☑️ Automations wired to events
☑️ UTM & tracking tested
☑️ Handoff alerts to Slack/Telegram

7. Roadmap (v2+)

• Memory DB for context

• Intent-specific playbooks (pricing, support, demo)

• Multi-language

• RAG on docs/FAQs

• Agent-to-human shared inbox

⚡ Step 1 – Create Your MCP Server

• Log into Agentpass

• Create a new MCP server → name it:

growth-mcp

⚡ Step 2 – Import OpenAPI Specs

Upload your OpenAPI spec files for:

• CRM

• Enrichment API

• Reddit

• Substack

• Email

👉 Agentpass will auto-generate MCP-compatible tools from these specs.

⚡ Step 3 – Add Authentication

• Add OAuth + API keys once per tool

• Tokens auto-rotate → no more manual refreshes

Example (config.yaml):

auth:
  crm: OAuth
  enrichment: API_KEY
  reddit: OAuth
  substack: API_KEY
  email: API_KEY

⚡ Step 4 – Organize Tools

Keep it clean with folder-based commands:

leads/
  fetch_by_signal
  enrich_company

reddit/
  scan_threads
  extract_buying_intent

substack/
  list_authors

email/
  warm_sequence_send

crm/
  upsert_contact

⚡ Step 5 – Deploy & Connect

• 1-click Deploy in Agentpass

• Copy the connection string

• Paste it into your AI agent

Example:

agentpass connect growth-mcp --token=<your_connection_string>

💡 Final Workflow (runs instantly)

Your AI outreach engine now:

1. Scans Reddit & Substack for leads

2. Enriches them with tech stack, funding, decision-makers

3. Nurtures via warm email funnels

4. Syncs all activity back into your CRM

🎯 Pro-Tip: Extend in Minutes

• Add more tools: HubSpot, LinkedIn, Product Hunt, etc.

• Drop in the OpenAPI → Agentpass MCP handles the rest

• Keep all workflows AI-ready + secure

✨ With this setup, what used to take hours of scripts + zaps now runs in 14 minutes flat.

0) Prerequisites (10–30 min once)

• Accounts & API keys: Reddit (script app), Substack (export/API), Gmail/Google Cloud (OAuth), Slack (bot), HubSpot (Private App), Smartlead (API), Clay (API).

• Machine: Any Linux/Mac/Windows box (4 GB RAM+).

• Secrets management: .env locally or a secret store (Doppler/1Password/Vault).

• Optional brokers: Redis/RabbitMQ for queues if you expect >5k ops/day.

1) Quick Install & Boot (≈14 minutes)

A. Directory scaffold

mcp/
  .env
  mcp.config.yaml
  policies/
    default.policy.yaml
  workflows/
    reddit_to_crm.yaml
    substack_to_sheet.yaml
    warm_email_funnel.yaml
    slack_qa.yaml
    content_distribution.yaml
  logs/
  data/

B. Environment variables (.env) — rename values

# Reddit
REDDIT_CLIENT_ID=xxxx
REDDIT_CLIENT_SECRET=xxxx
REDDIT_USER_AGENT=growth-exe-mcp/1.0

# Substack (token or app password if enabled)
SUBSTACK_TOKEN=xxxx

# Google
GOOGLE_CLIENT_ID=xxxx
GOOGLE_CLIENT_SECRET=xxxx
GOOGLE_REFRESH_TOKEN=xxxx

# Slack
SLACK_BOT_TOKEN=xoxb-xxxx
SLACK_APP_TOKEN=xapp-xxxx

# HubSpot
HUBSPOT_TOKEN=pat-xxxx

# Smartlead
SMARTLEAD_API_KEY=xxxx

# Clay
CLAY_API_KEY=xxxx

C. MCP Server config (mcp.config.yaml) — template

server:
  port: 8787
  log_level: info
  auth:
    mode: token
    tokens:
      - name: ops-console
        value: REPLACE_ME_CONSOLE_TOKEN
      - name: daily-sweep-agent
        value: REPLACE_ME_SWEEP_TOKEN

namespaces:
  - name: sales
    resources:
      - type: reddit
        alias: reddit_public
        creds:
          client_id: ${REDDIT_CLIENT_ID}
          client_secret: ${REDDIT_CLIENT_SECRET}
          user_agent: ${REDDIT_USER_AGENT}
      - type: hubspot
        alias: hubspot_crm
        creds:
          token: ${HUBSPOT_TOKEN}
      - type: smartlead
        alias: smartlead_mail
        creds:
          api_key: ${SMARTLEAD_API_KEY}
  - name: marketing
    resources:
      - type: substack
        alias: substack_list
        creds:
          token: ${SUBSTACK_TOKEN}
      - type: google_sheets
        alias: sheets_ops
        creds:
          client_id: ${GOOGLE_CLIENT_ID}
          client_secret: ${GOOGLE_CLIENT_SECRET}
          refresh_token: ${GOOGLE_REFRESH_TOKEN}
      - type: slack
        alias: slack_connect
        creds:
          bot_token: ${SLACK_BOT_TOKEN}
          app_token: ${SLACK_APP_TOKEN}

agents:
  - id: lead_scout
    allowed:
      namespaces: [sales, marketing]
      tools: [reddit.search, reddit.fetch_comments, clay.enrich, hubspot.upsert_contact, sheets.append_rows]
  - id: warmoutreach
    allowed:
      namespaces: [sales]
      tools: [smartlead.create_campaign, smartlead.send_email, hubspot.attach_engagement]
  - id: support_bot
    allowed:
      namespaces: [marketing]
      tools: [slack.listen, slack.reply, sheets.lookup_faq]

observability:
  request_log: ./logs/requests.ndjson
  event_log: ./logs/events.ndjson

queueing:
  type: memory           # switch to redis for scale
  concurrency: 4

rate_limits:
  reddit:
    rpm: 50
  hubspot:
    rpm: 80
  smartlead:
    rpm: 60

D. Policies (least privilege) policies/default.policy.yaml

rules:
  - subject: agent:lead_scout
    allow:
      - tool: reddit.search
      - tool: reddit.fetch_comments
      - tool: clay.enrich
      - tool: sheets.append_rows
      - tool: hubspot.upsert_contact
    deny:
      - tool: smartlead.send_email

  - subject: agent:warmoutreach
    allow:
      - tool: smartlead.create_campaign
      - tool: smartlead.send_email
      - tool: hubspot.attach_engagement
    deny:
      - tool: reddit.*
      - tool: sheets.append_rows

  - subject: agent:support_bot
    allow:
      - tool: slack.listen
      - tool: slack.reply
      - tool: sheets.lookup_faq

E. Start the server

• Binary/CLI: agentpass-mcp serve --config ./mcp.config.yaml --env ./.env

• Docker (template):

docker run -d --name mcp \
  -p 8787:8787 \
  --env-file .env \
  -v $(pwd)/mcp.config.yaml:/app/mcp.config.yaml \
  -v $(pwd)/policies:/app/policies \
  -v $(pwd)/logs:/app/logs \
  agentpass/mcp-server:latest serve --config /app/mcp.config.yaml

Adjust binary/image names to your local setup; the snippet is a template.

F. Sanity tests (pick any)

• Auth test: call GET /health with the ops-console token.

• Tool list: GET /tools → confirm namespaces/tools are visible.

• Dry-run: run reddit.search with a safe subreddit (e.g., r/Entrepreneur) and limit=3.

2) Register & Verify Each API (once per connector)

Reddit

1. Create a script app; set redirect

http://localhost

1. if asked.

2. Save client_id, client_secret, user_agent.

3. Test: search site:substack.com "newsletter", ensure 200 OK.

Substack

1. Generate token (if enabled) or use export endpoint.

2. Test: list subscribers; compare count to dashboard.

Google Sheets/Gmail

1. Create OAuth client (Desktop).

2. Capture client_id, client_secret, refresh_token.

3. Test: create a “Prospects (MCP)” sheet; append 1 row.

Slack

1. Create bot, add chat:write, channels:history, app_mentions:read.

2. Install to workspace; note bot and app tokens.

3. Test: post a message to a test channel.

HubSpot

1. Private App → scopes: crm.objects.contacts.read/write, engagements.

2. Test: upsert one dummy contact by email; verify in UI.

Smartlead

1. Create API key.

2. Test: list sender accounts; verify the correct pool appears.

3) Build the 5 Core Workflows (copy-paste templates)

Convention: Each workflow YAML declares: trigger → sources → filters → enrich → actions → log.

3.1 Reddit → CRM (workflows/reddit_to_crm.yaml)

name: reddit_to_crm
schedule: "cron(*/20 * * * *)"  # every 20 min
trigger:
  type: timer
params:
  subreddits: ["Entrepreneur", "SaaS"]
  query: ["lead gen", "outbound", "tool recommendations"]
steps:
  - id: fetch_posts
    use: reddit.search
    with:
      subreddits: ${params.subreddits}
      query: ${params.query}
      limit: 25
  - id: fetch_comments
    use: reddit.fetch_comments
    with:
      post_ids: ${steps.fetch_posts.ids}
      limit_per_post: 20
  - id: pick_prospects
    use: filter.expression
    with:
      input: ${steps.fetch_comments.items}
      where: |
        (score >= 1) and not is_op and not contains(text, "hire me")
  - id: enrich
    use: clay.enrich
    with:
      input: ${steps.pick_prospects.items}
      fields: [name, company, email, linkedin_url, role]
  - id: upsert_hubspot
    use: hubspot.upsert_contact
    with:
      contacts: ${steps.enrich.results}
      unique_key: email
  - id: log
    use: sheets.append_rows
    with:
      sheet: "Prospects (MCP)!A:F"
      rows: ${steps.enrich.results}

3.2 Substack → Lead Sheet (workflows/substack_to_sheet.yaml)

name: substack_to_sheet
schedule: "cron(5 6 * * *)"  # 06:05 UTC daily ≈ 11:35 IST
steps:
  - id: pull
    use: substack.list_subscribers
    with:
      since_days: 2
  - id: dedupe
    use: sheets.dedupe
    with:
      sheet: "Subscribers (MCP)!A:D"
      key: email
      incoming: ${steps.pull.items}
  - id: write
    use: sheets.append_rows
    with:
      sheet: "Subscribers (MCP)!A:D"
      rows: ${steps.dedupe.unique}

3.3 Warm Email Funnel (workflows/warm_email_funnel.yaml)

name: warm_email_funnel
schedule: "cron(0 7,13 * * 1-6)"  # 07:00 & 13:00 UTC Mon–Sat
steps:
  - id: signals
    use: aggregator.join
    with:
      reddit: reddit.engagers_last_48h
      linkedin: sheets.read_range   # maintained by separate job
      substack: substack.opens_last_48h
  - id: score
    use: scorecard.linear
    with:
      weights:
        reddit_comment: 3
        linkedin_profile_view: 2
        substack_open: 1
      threshold: 3
  - id: prep_email
    use: template.render
    with:
      template: |
        Subject: Quick idea for {{company}}
        Body:
        Hey {{firstName}} — noticed {{signal}}. 
        Built a tiny workflow that {{benefit}}. 
        Worth a 7-line note? If yes, I’ll send.
      variables: ${steps.score.passed}
  - id: send
    use: smartlead.send_email
    with:
      messages: ${steps.prep_email.messages}
      campaign: "Warm MCP Intros"
  - id: attach
    use: hubspot.attach_engagement
    with:
      items: ${steps.prep_email.messages}

3.4 Slack Q&A Agent (workflows/slack_qa.yaml)

name: slack_qa
trigger:
  type: event
  source: slack_connect
  event: app_mention
steps:
  - id: lookup
    use: sheets.lookup_faq
    with:
      sheet: "FAQ (MCP)!A:B"
      key: ${event.text}
  - id: reply
    use: slack.reply
    with:
      channel: ${event.channel}
      thread_ts: ${event.ts}
      text: ${steps.lookup.answer or "I’ll DM you the doc in a sec."}

3.5 Content Distribution (workflows/content_distribution.yaml)

name: content_distribution
trigger:
  type: filewatch
  path: ./data/drafts/
steps:
  - id: parse
    use: content.parse_frontmatter
  - id: schedule_posts
    use: publisher.multi
    with:
      linkedin: { when: "best_time_today", text: ${steps.parse.linkedin_copy} }
      twitter:  { when: "best_time_today", text: ${steps.parse.twitter_copy} }
      substack: { when: "immediate", title: ${steps.parse.title}, body: ${steps.parse.body} }
  - id: log
    use: sheets.append_rows
    with:
      sheet: "Content Log (MCP)!A:E"
      rows: ${steps.schedule_posts.summary}

4) Access Control & Safety (copy these patterns)

• Least privilege by agent: All sends go through warmoutreach; scraping goes through lead_scout.

• Scoped tokens: one token per agent (daily-sweep-agent, ops-console).

• Namespace isolation: sales vs. marketing separated to prevent tool bleed.

• Rate limits: set explicit RPM caps per API (see config).

• Audit & immutability: log all requests/events to append-only NDJSON.

• Outbound approvals (optional): require ops-console approval for large send batches (>50).

5) The Daily Lead Sweep (IST-aware)

Target windows (IST):

• 01:00–03:00 scrape (low API contention)

• 05:00 enrich + dedupe

• 11:00 & 18:30 outreach windows (human-like timing)

Checklist

1. Run reddit_to_crm (pull + enrich + HubSpot + sheets log)

2. Run substack_to_sheet (append + dedupe)

3. Score signals → queue warm emails (reviewable batch)

4. Send via Smartlead with throttling (e.g., 12/min per sender)

5. Post summary to #mcp-daily Slack channel (new contacts, emails queued/sent, errors)

One-liner status (ops):

agentpass-mcp status --since 24h --workflows reddit_to_crm,substack_to_sheet,warm_email_funnel

6) Scaling Without Headaches

• Queues: switch queueing.type to redis and set concurrency: 16+.

• Idempotency: dedupe on (source, external_id) before upserts/sends.

• Backoff: exponential retry on 429/5xx; circuit break after 5 fails.

• Shard by market: run separate MCP instances by geo or business unit.

• Observability:

  • Errors: <1% per 24h

  • Time-to-lead: <10 min from capture → CRM

  • Outreach latency: <30 min from signal → first touch

7) Troubleshooting Quick Guide

• 401/403: token mismatch or policy deny → check default.policy.yaml.

• 429 (rate limit): lower rpm, add jitter, widen cron intervals.

• HubSpot upsert fails: missing email or invalid property → validate schema before send.

• Smartlead bounce spike: pause sender, warm IP/domain, verify DNS (SPF/DKIM/DMARC).

• Slack bot silent: missing scope or wrong channel ID → reinstall + reauth.

8) QA Checklist Before “Go”

• Secrets present (.env), no placeholders left.

• GET /tools shows only needed tools per agent.

• Dry-run on each workflow with 1–3 records.

• Rate limits tested using a burst (no bans).

• Logs streaming to logs/ and retained for 30 days.

• Emergency stop: agentpass-mcp pause warm_email_funnel.

9) Metrics & Review Cadence

• Daily (Slack digest): new leads, sends, replies, errors.

• Weekly: conversion to meeting (%), list health (open/click), bounce rate.

• Monthly: SQL/Sheets audit of dedupe hits, domains, persona coverage.

10) Copy Blocks (use in UI/Docs)

Warm intro template

Subject: Quick idea for {{company}}

Hey {{firstName}} — I noticed {{signal}}.
We built a tiny workflow that {{benefit in 1 line}}.
If relevant, I’ll send a 7-line breakdown and leave it there.

Slack auto-reply (fallback)

Got it. I’m pulling the doc now and will drop it in this thread.
(If you need a human: @Divyanshi.)

11) Security Notes (non-negotiable)

• Rotate all tokens every 90 days.

• Separate senders for prospecting vs. customer comms.

• Restrict ops token to VPN/office IPs.

• Keep PII in CRM + Sheets only; avoid logs beyond email/name.

40+ carefully organized categories covering every stage of your sales funnel:

• Lead generation & prospecting tools

• Email automation & personalization

• CRM integrations & pipeline management

• Sales analytics & forecasting

• Conversation intelligence platforms

🎯 Top-Performing Categories

Lead Generation Powerhouses

These AI tools are finding qualified prospects faster than ever before:

• LinkedIn automation platforms with 90%+ connection rates

• Email finder tools with real-time verification

• Website visitor identification and retargeting systems

Conversation Intelligence Game-Changers

Transform every sales call into actionable insights:

• Real-time coaching suggestions during calls

• Automatic deal risk identification

• Competitor mention tracking across conversations

Pipeline Optimization Champions

AI-powered forecasting that actually works:

• Revenue prediction with 95%+ accuracy

• Deal scoring based on historical patterns

• Next best action recommendations for each prospect

⚡ Quick Implementation Guide

Week 1: Start with lead generation

• Pick 2-3 prospecting tools from our top-rated list

• Set up automated sequences

• Begin building your qualified pipeline

Week 2: Layer in conversation intelligence

• Install call recording and analysis tools

• Create custom scorecards for your sales process

• Train your team on AI-generated insights

Week 3: Optimize with analytics

• Integrate forecasting tools with your CRM

• Set up revenue dashboards

• Begin A/B testing different approaches

💡 Pro Tips from Top Sales Teams

Stack Integration Strategy:

• Choose tools that play well together (check our compatibility matrix)

• Start with 3-5 core tools before expanding

• Always measure ROI within 30 days

Data Quality First:

• Clean your CRM before connecting AI tools

• Set up proper tracking from day one

• Create feedback loops between tools

🎁 Exclusive Bonuses Inside

✅ Detailed comparison charts for each category
✅ Pricing breakdown and ROI calculators
✅ Implementation checklists for rapid deployment
✅ Integration guides for popular CRM platforms
✅ Video demos of top-performing tools

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Limited time: Use code AISALES20 for 20% off

Questions? Hit reply - we read every email and love helping sales teams succeed with AI.

Stop guessing who to target. Use these prompts to define who’s most likely to buy.

• Generate 5 buyer personas (pain points, objections, and best channels).
  

• Break down pain points for one persona and map them to your solution.
  

• Identify common objections and how to overcome them.
  

• Find the best marketing channels for your ICP — with arguments why.
  

• Get a list of the 10 top LinkedIn influencers to collaborate with.
  

🔗 2. Optimize Your LinkedIn Profile

Before outreach, make sure your profile attracts.

• Rewrite your headline → 10 versions (funny, value-driven, with emojis).
  

• Rewrite your About section → storytelling style, <150 words, keyword-rich.
  

📝 3. Content That Converts

Turn content into your best lead magnet.

• Get 5–10 content topics tailored to your audience.
  

• Create a full content plan around ICP pain points.
  

• Write engaging LinkedIn posts (storytelling + humor + emojis).
  

• Repurpose your blogs into LinkedIn-ready posts.
  

📊 4. Scraping & Enrichment

Speed up research with automation.

• Google Apps Script: find LinkedIn profiles from name + company.
  

📑 5. Clean Your Lead Database

Messy data = wasted time. These prompts fix that.

• Formula to extract clean company names from URLs.
  

• Replace unusual Latin letters with English equivalents.
  

• Find company domains from names using APIs.
  

📧 6. Cold Email Prompts

Get AI to draft personalized, non-robotic cold emails.

• 100-word cold email using event attendee data.
  

• Casual intro emails with personalization.
  

• 10 subject lines that get 70%+ open rates.
  

• Follow-ups that use FOMO + scarcity (without sounding spammy).
  

• Personalization ideas: job title, recent posts, events joined.
  

💬 7. LinkedIn Outreach Prompts

Warm up leads before the pitch.

• Personalized icebreakers (with localized greetings).
  

• Authority-building comments on LinkedIn posts.
  

• Connection requests <300 chars (no robotic tone).
  

• Engaging follow-ups → friendly, casual, no direct selling.
  

• Cold call scripts that feel human (permission-based + objection handling).
  

✅ Wrap-Up

Outbound lead gen doesn’t need to be guesswork.
With these 40 ready-to-use ChatGPT prompts, you can:

• Find the right buyers.
  

• Personalize at scale.
  

• Close deals faster.
  

👉 Want the full prompt library in a ready-to-use template?

Every great personalization prompt needs:

• Function → clear, specific instruction or question
  

• Context → related context + “act as…” framing
  

• Modifier → words to refine or adjust the output
  

👀 Framework in Action (Agency Owner Example)

You’re a marketing agency owner making $40k/mo with SEO for local businesses. You want to scale to $100k/mo.

AI Prompt Example:

“What are the 3 main reasons why I haven’t scaled yet, and what client acquisition methods I’ve tried that failed? Explain why.”

This produces insights on:

• Bottlenecks holding you back
  

• Failed tactics (and why)
  

• Next-step strategies
  

🎨 Personalization Tricks That Work

Here are tested templates that keep things human (not salesy):

• Compliment:
  “I love how you [XYZ].”
  

• Assumption:
  “You do help with [XYZ], right?”
  

• Ads Angle:
  “Are you running ads for [XYZ]?”
  

• Playful Relevancy:
  “My FBI-level detective work suggests you provide [XYZ].”
  

🛠️ Why Some Methods Don’t Work

Tried blasting LinkedIn DMs? Running generic ads? Cold lists? Yeah… those flop.

Why?

• Too cookie-cutter → prospects sniff it out instantly
  

• Too long → nobody reads walls of text
  

• Too salesy → feels automated, not personal
  

AI personalization fixes this by making each message feel written for them.

📩 Example Outreach Line

“Came across one of your ads for XYZ. (Lovely product btw.) Makes sense you’d go for that campaign angle.”

✅ Takeaway

Cold outreach that works is:

• Short + playful
  

• Pain-aware (hit time, money, status)
  

• Personalized with context
  

Stop guessing. Start using frameworks + AI to scale conversations that actually convert.

⚡ CTA

Want to see how AI could personalize cold outreach in your own niche?
👉 Hit reply and I’ll drop you a few live examples.

Json file (click to download)

Overview of nodes

• 1. Trigger (Cron or Manual)

  2. Fetch Leads (HTTP Request to Clay OR Google Sheets/CSV)

  3. Clean/Validate (Function)

  4. Create Personalized Video (HTTP Request → Tavus API)

  5. Wait/Status Poll (IF + HTTP Request loop)

  6. Build Email Payload (Function)

Detailed Tutorial: Clay → Tavus → Lemlist (→ HubSpot)

Environment setup (vars)

Set these in n8n Environment Variables (or Credentials):

• TAVUS_API_KEY

• TAVUS_TEMPLATE_ID (your Tavus video template)

• LEMLIST_API_KEY (optional, if pushing to Lemlist)

• LEMLIST_CAMPAIGN_ID (optional, if adding to a campaign)

• N8N_WEBHOOK_TAVUS_STATUS (optional, if you use Tavus webhooks)

• SMTP_POOL (JSON array of SMTP credential names for rotation, e.g. ["SMTP1","SMTP2"])

Lead input schema (minimum)

firstName, lastName, email, companyName, role, fundingEvent (or trigger), linkedinUrl, timezone

You can source this from Clay (export or webhook), Google Sheets, or CSV.

Node‑by‑Node Configuration (copyable)

1) Trigger (Cron or Manual)

• Node: Cron → every weekday at 09:00 local (or Manual for testing)

2) Fetch Leads

Pick one of the below patterns.

A. Google Sheets

• Node: Google Sheets — Read

• Operation: Lookup → Range: Leads!A1:Z

B. CSV

• Nodes: Read Binary File → CSV to JSON

C. Clay → Webhook (recommended when scoring inside Clay)

• Node: Webhook (Testable) → Method POST

• In Clay, set “Send to Webhook” step to this n8n URL.

3) Clean / Validate

Node: Function

// Require essentials
return items
  .filter(i => i.json.email && i.json.firstName && i.json.companyName)
  .map(i => {
    i.json.fundingEvent = i.json.fundingEvent || i.json.trigger || '';
    return i;
  });

4) Create Personalized Video (Tavus)

Node: HTTP Request

• Method: POST

• URL: https://api.tavus.io/v2/videos

• Headers: Authorization: Bearer {{$env.TAVUS_API_KEY}}, Content-Type: application/json

• Body (JSON):

{
  "template_id": "{{$env.TAVUS_TEMPLATE_ID}}",
  "variables": {
    "firstName": "{{$json.firstName}}",
    "companyName": "{{$json.companyName}}",
    "fundingEvent": "{{$json.fundingEvent}}"
  },
  "webhook_url": "{{$env.N8N_WEBHOOK_TAVUS_STATUS}}",
  "metadata": {
    "lead_email": "{{$json.email}}",
    "source": "n8n"
  }
}

Output mapping (Function Item):

// Save IDs/URLs for later steps
item.json.tavus = {
  id: $json.id || $json.video_id || null,
  url: $json.video_url || $json.url || null,
  status: $json.status || 'processing'
};
return item;

5) Wait / Status Poll (until video is ready)

Pattern: HTTP Request (GET) → IF (status !== completed) → Wait 20s → Loop back

HTTP Request (check):

• Method: GET

• URL: https://api.tavus.io/v2/videos/{{$json.tavus.id}}

• Headers: Authorization: Bearer {{$env.TAVUS_API_KEY}}

IF condition: ={{$json.status}} !== 'completed'

Wait: 20 seconds

On completion (Function Item):

// Normalize final video URL
item.json.video_url = $json.video_url || $json.url || item.json.tavus?.url || '';
return item;

Tip: If you configured webhooks in Tavus, you can skip polling and route the webhook → Update Lead → continue flow.

6) Build Email Payload (Function)

const first = $json.firstName;
const comp = $json.companyName;
const trig = $json.fundingEvent || 'recent update';
const video = $json.video_url;

item.json.subject1 = `Quick note on ${comp}`;
item.json.e1 = `Hi ${first},
Saw ${comp}'s ${trig}.
I recorded a 45s walkthrough showing exactly how teams like yours handle it without adding headcount:
${video}
If useful, reply \"yes\" and I’ll send the 3‑step plan.
— {{yourName}}`;

item.json.subject2 = 'Following up';
item.json.e2 = `${first} — did the 45s video land? Covers the pattern we’re seeing post‑${trig}. Want the 3‑step plan?`;

item.json.subject3 = 'Last note';
item.json.e3 = `Happy to share the checklist we use to fix this in < 2 weeks. Worth a look?`;

return item;

7) Send via Lemlist (optional) or SMTP

Option A — Lemlist: Add/Update Lead with custom fields

• Node: HTTP Request

• Method: POST

• URL: https://api.lemlist.com/api/leads

• Headers: Authorization: Bearer {{$env.LEMLIST_API_KEY}}, Content-Type: application/json

• Body (JSON):

{
  "email": "{{$json.email}}",
  "firstName": "{{$json.firstName}}",
  "lastName": "{{$json.lastName}}",
  "companyName": "{{$json.companyName}}",
  "customFields": {
    "tavusVideo": "{{$json.video_url}}",
    "role": "{{$json.role}}",
    "fundingEvent": "{{$json.fundingEvent}}"
  }
}

(Optional) Add Lead to Campaign

• Method: POST

• URL: https://api.lemlist.com/api/campaigns/{{$env.LEMLIST_CAMPAIGN_ID}}/leads

• Body (JSON):

{
  "emails": ["{{$json.email}}"],
  "deduplicate": true
}

Option B — Send directly via n8n SMTP

• Node: Function Item (pick SMTP)

const pool = JSON.parse($env.SMTP_POOL || '["SMTP1"]');
item.json.smtpAlias = pool[Math.floor(Math.random()*pool.length)];
return item;

• Node: Email Send (for Email 1)

  • To: ={{$json.email}}

  • Subject: ={{$json.subject1}}

  • Text: ={{$json.e1}}

  • Credentials: ={{$json.smtpAlias}}

• Add Wait 2d → Email Send (Bump 1) → Wait 3d → Email Send (Bump 2)

8) HubSpot (optional, log the video + outreach)

Create/Update Contact then create Note with the Tavus link.

A) Search Contact (HTTP Request)

• POST https://api.hubapi.com/crm/v3/objects/contacts/search

• Headers: Authorization: Bearer {{HUBSPOT_PRIVATE_APP_TOKEN}}, Content-Type: application/json

• Body:

{
  "filterGroups": [{
    "filters": [{"propertyName": "email", "operator": "EQ", "value": "{{$json.email}}"}]
  }],
  "properties": ["email"]
}

B) Create if missing (HTTP Request)

• POST https://api.hubapi.com/crm/v3/objects/contacts

• Body:

{"properties": {"email": "{{$json.email}}", "firstname": "{{$json.firstName}}", "lastname": "{{$json.lastName}}", "company": "{{$json.companyName}}"}}

C) Create Note (HTTP Request)

• POST https://api.hubapi.com/crm/v3/objects/notes

• Body:

{
  "properties": {
    "hs_note_body": "Tavus video generated: {{$json.video_url}}
Sequence prepared for {{companyName}}",
    "hs_timestamp": "={{$now}}"
  }
}

Associate the note with the contact using the Associations API if needed.

Error handling & guardrails

• Missing email or video URL → route to “Review” list (Google Sheet row append)

• Tavus status = failed → skip sending, log reason

• API rate limits → add Wait jitter between requests (200–800ms)

• Unsubscribe handling → check suppression list before send

QA checklist

• Run on 3–5 test leads

• Confirm: video URL renders, subject/body under 90 words, merge fields resolve

• Verify: time‑zone send windows, SMTP rotation, reply monitor halts bumps

Copy‑paste prompts

Research (Perplexity):

Research {{companyName}} ({{domain}}). Return bullet points:
- Top 3 initiatives or changes (last 90 days)
- Likely gaps tied to {{yourProductOneLiner}}
- 2 credible source URLs
Limit 120 words.

Pain Synthesis (GPT‑4):

From LinkedIn + research, list 3 pains with:
Pain → Why now → Evidence (their post/news) → Angle (how {{yourProduct}} helps).
Max 80 words total.

Sequence (GPT‑4):

Write 3 emails (<90 words each) for {{firstName}} at {{companyName}} ({{role}}). Reference {{evidence}} and include {{video_url}}. Tone: specific, plain, zero fluff. CTA: reply “yes” for the exact 3‑step plan.

Visual of the workflow (text map)

Cron/Manual → Fetch Leads → Clean/Validate → Tavus Create Video → [Poll until completed]
→ Build Email Payload → (A) Lemlist: create/update + add to campaign → (B) SMTP: send seq
→ (Optional) HubSpot: log note/associate → Logging/Review

The way you write prompts can make or break your AI results. A clear structure = sharper, faster, and more useful outputs. Let’s break it down.

🔑 Prompt Formula

Function → What you want (instruction, question, task)
Context → Background info (act as…, role, key elements)
Modifier → Adjust tone, style, depth, or format

👉 Example:
“You’re a marketing agency owner making $40k/month through SEO. You want to scale to $100k. What are 3 main issues blocking growth and why past acquisition methods failed?”

🎯 Personalization Tips

Make your prompts feel human and natural:

• Start casual: “I love how you…”

• Ask like a friend: “You do help with XYZ, right?”

• Keep playful, short, and real
  

  👉 Examples:

• “Are you running ads for local gyms?”

• “Noticed you help with branding (Lovely designs btw). I know you spend a lot of time on strategy.”

🛠️ Multi-Layered Prompts

Layer instructions for different tones, outputs, and use cases:

• Assumptions → “I love how your product helps with XYZ”

• Compliments → “It’s interesting how your product simplifies XYZ”

• Niche → “coffee” / “health & beauty” / “safety”

✂️ Clean Data Prompts

Keep titles, companies, and cities human-friendly:

• Job Titles: “Founder Chief Executive Officer” → Founder and CEO

• Company Names: “Apple LLC” → Apple

• City Names: “Chengdu, Sichuan, China” → Chengdu

✅ Takeaway

Writing better prompts = getting AI that works like a teammate, not a robot.

✨ Start small: add function + context + modifier to every prompt.
✨ Personalize: make it sound human.
✨ Clean: keep data simple.

So I made an account on BotRoom LTD and plugged it into my LinkedIn → Newsletter funnel.

Here’s What Happened:

• Visitors landed on my site

• AI Sales Agent ran real-time demos + answered questions

• Personalized offers triggered automatically

• Calls started booking on autopilot

Result: 30 qualified calls in just 7 days.

Why It Works Better Than the Old Way

The Old Way:

• ❌ Reps repeating the same walk-throughs

• ❌ Prospects dropping off without instant answers

• ❌ Follow-ups dragging out sales cycles

The AI Flip:

• ✅ 24/7 interactive product demos

• ✅ Personalized offers for every visitor

• ✅ Conversion tracking → no guesswork

• ✅ Predictable, repeatable growth

Results You Can Expect

• 📈 Up to 300% more lead conversions

• ⚡ 50% shorter sales cycles

• 🎯 Personalized engagement at scale

Step-by-Step Setup Guide

Step 1: Create Your BotRoom LTD Account

• Go to the BotRoom LTD site

• Sign up for a free account

• Complete your profile and connect your business details

Step 2: Connect to Your Funnel

• Integrate BotRoom LTD with your LinkedIn → Newsletter funnel

• Add the AI widget to your website or landing page

Step 3: Set Up Real-Time Demos

• Upload your product demo script or materials

• Configure the AI to answer FAQs instantly

Step 4: Automate Personalized Offers

• Define your visitor segments (ex: role, industry, behavior)

• Assign unique offers for each segment

• Trigger automatic delivery through the AI agent

Step 5: Track & Optimize

• Enable conversion tracking inside BotRoom LTD

• Review visitor interactions daily

• Optimize offers and scripts for higher conversion

Step 6: Scale the System

• Add more funnel entry points (ads, posts, email)

• Expand personalization rules

• Use performance data to shorten sales cycles further

The Best Part?

You can try it for free.

I’ve put together:

• A step-by-step setup breakdown

• A free demo link you can use today

💬 Comment “Send” and I’ll DM you the link of the AI sales agent and how I used it!

Step-by-Step Setup Guide

Prerequisites

• Website builder access (Webflow, Framer, WordPress, custom).

• Calendar tool (Calendly, TidyCal, HubSpot Meetings).

• Email platform (Omnisend, ConvertKit, Brevo, MailerLite).

• CRM (HubSpot, Pipedrive, Airtable) and optional Zapier/Make for glue.

• Clear ICP + 3–5 core FAQs you want the agent to answer.

1) Create Your BotRoom Agent

1. Sign up at BotRoom LTD and create a new agent.

2. Pick a template: Product Demo or Lead Capture.

3. Connect knowledge: your docs URL, pricing page, FAQs, Notion/help center.

4. Tone & guardrails: concise, value-first; block legal/medical investment topics; add handoff phrase (e.g., “Let me connect you to a human”).

5. Qualification form: set 3–5 fields (name, work email, company, role, use-case).

2) Install the Widget on Your Site

1. Copy the widget snippet from BotRoom.

2. Paste into your site-wide header/footer (before </head> or via integrations).

3. Publish and hard refresh. Verify the chat bubble appears on all target pages.

4. Create a dedicated /demo landing page to drive LinkedIn + Newsletter traffic.

3) Connect Calendar & Routing

1. Link your Calendly/TidyCal URL or use native calendar integration.

2. Booking rules: buffer (15–30 min), min notice (2–4 hrs), time blocks.

3. Round-robin or territory routing for teams; fallback to a generic slot if reps are busy.

4. Post-booking actions: auto-send calendar invite + confirmation email.

4) Personalization & Offer Rules

1. Define segments: utm_source=linkedin, utm_medium=newsletter, new vs returning, geo, device, page depth.

2. Offers by segment:

   • LinkedIn traffic → Free interactive demo

   • Newsletter traffic → Exclusive audit or checklist

   • Returning visitor → Skip intro and show Book a call CTA

3. Dynamic tokens: {first_name}, {company}, {industry} in messages.

5) Build the Real-Time Demo Flow (High-Intent Path)

1. Opener: “Want a 60‑sec interactive tour tailored to your role?”

2. Qualifiers (max 3): role, team size, primary goal.

3. Demo payload: short GIF/loom or interactive steps; add 2–3 objection handlers.

4. Strong CTA: “Book 15 min to see your use-case live.”

5. Human handoff: Slack/Email alert to your team when the user asks for help.

6) Tracking & Measurement

1. Enable GA4/Pixel events in BotRoom (or fire custom events through GTM):

   • agent_opened, question_answered, offer_shown, cta_clicked, call_booked.

2. Mark call_booked as a conversion in GA4/Ads; build audiences from agent_opened.

3. UTM discipline on all links from LinkedIn & newsletter.

7) LinkedIn → Newsletter → Site Funnel

A. LinkedIn post (capture intent):

• CTA: Comment “Send” and I’ll DM the setup + demo link.

• Reply to comments quickly; avoid automation that breaks LinkedIn’s TOS.

B. DM template:

Hey {{first_name}} — here’s the AI Sales Agent demo + setup I used. Walkthrough + free demo: {{short_link}}. If you want, I can share my offer rules too.

C. Newsletter capture:

1. Landing page with a single field (email) + clear promise.

2. Use NeverBounce (or equivalent) via Zapier to verify before adding to your list.

3. Auto-email (“Day 0”) with the /demo link + what to click first.

8) CRM Sync & Lead Scoring

1. Push every qualified chat to CRM with fields: name, email, company, UTM, pages viewed, questions asked, agent score.

2. Score examples:

   • +10 opened agent, +20 finished demo, +30 booked call, +15 pricing page view.

3. Lifecycle rules: if score ≥60 and no booking → trigger human outreach.

9) Launch Checklist (15-Min Pass)

• Widget visible on /, /pricing, /features, /demo

• Calendar connected + time zones correct

• UTM links tested from LinkedIn & newsletter

• Events firing in GA4 (realtime view)

• Demo GIF loads <2s on mobile

• Copy proofed; no dead links

10) Optimization Cadence (Week 1 → Week 4)

• Week 1: A/B test opener; target ≥45% agent open rate.

• Week 2: Shorten qualifiers to 2–3; aim ≥25% demo completion.

• Week 3: Tighten offer rules; push for ≥8–12% click-to-book from demo.

• Week 4: Route by ICP; add objection micro-copy; review top missed intents.

Swipe Files (Copy-Paste)

LinkedIn Post CTA (end):

Comment “Send” and I’ll DM you my setup + free demo link.

Newsletter Welcome (Subject lines):

• “Your AI Sales Agent (Free Demo Inside)”

• “The exact playbook behind 30 calls in 7 days”

Landing Page Hero:

Ship 24/7 product demos that book calls while you sleep.

Troubleshooting

• Widget not showing: publish site, clear cache, ensure snippet before </head>, disable ad blockers, check console.

• Bookings not creating invites: reconnect calendar or replace expired token.

• Low demo completion: reduce steps, compress media, remove jargon.

• Few bookings from demo: strengthen CTA, add alternative CTA (email me), add incentive.

Advanced Automations (Optional)

• Zapier: New call_booked → create CRM deal → Slack alert → add to onboarding sequence.

• Verify emails with NeverBounce before adding to newsletter.

• Create Lookalike audiences from agent_opened for paid campaigns.

Last week, I set myself a challenge:

Spin up an MCP server + hack my lead gen workflow via AI agents… in under 15 minutes.

Here’s the exact step‑by‑step I followed so you can replicate it.

What You’ll Need (5 mins prep you can do beforehand)

• Account on Agentpass.ai

• OpenAPI specs (YAML/JSON) for the services you want agents to call — e.g., a Reddit/search API, a newsletter/subscriber source, your email provider, a B2B data source, and your CRM

• API keys / OAuth client IDs for those services

Tip: Put all specs in a folder like specs/ and your keys in a .env or secrets vault.

The 14‑Minute Build — Minute‑by‑Minute

⏱️ Minute 0–1: Create the Server

1. Log in to Agentpass → Create new MCP server.

2. Name it leadgen-mcp, description: Lead gen automations for Reddit, Substack, CRM, email.

3. Choose Private visibility for now.

⏱️ Minute 2–4: Import Your APIs (OpenAPI → MCP)

4. Go to Tools → Import and drop in your OpenAPI specs:

   • reddit-search.yaml (or the search API you use)

   • newsletter-source.yaml (Substack/feeds provider)

   • email-service.yaml (e.g., transactional email)

   • b2b-prospects.yaml (data provider)

   • crm.yaml (HubSpot/Pipedrive/Salesforce)

5. Agentpass autogenerates MCP tool definitions from each spec (no hand‑coding schemas).

⏱️ Minute 5–6: Wire Up Auth (No backend scripts)

6. For each tool, open Auth:

   • Choose OAuth2 or API Key as required.

   • Paste client ID/secret or API keys.

   • Set token scopes (read/write) and enable auto‑refresh.

7. Save all credentials to the built‑in secrets store.

⏱️ Minute 7: Access Control

8. Create roles:

   • reddit-agent → only Reddit/search tools

   • email-agent → only email tools

   • crm-agent → only CRM endpoints

   • prospects-agent → only B2B data endpoints

9. Assign your agents/users to roles so no one has more access than they need.

⏱️ Minute 8: Quick Sanity Tests

10. In Tools → Test, run sample calls:

    • reddit.search({ query: "(looking for|recommend) CRM", subs: ["Entrepreneur","SaaS","Startups"], limit: 25 })

    • Expect JSON posts with title, url, author, text.

11. Verify the email tool (email.templates.list) and CRM tool (crm.contacts.upsert) both respond without errors.

⏱️ Minute 9–12: Build the Automations (Pipelines)

12. Create five pipelines (Schedules → New Pipeline). Example declarative config:

pipeline: reddit_buying_intent
schedule: "0 9 * * *"   # 09:00 Asia/Kolkata daily
steps:
  - tool: reddit.search
    input:
      query: "(looking for|recommend|best) (CRM|outreach|lead gen)"
      subs: ["Entrepreneur","SaaS","Startups","sales"]
      timeframe: "last_24h"
  - tool: prospects.enrich
    input:
      from: "$.results[*].author, $.results[*].domain"
  - tool: crm.contacts.upsert
    input:
      map:
        email: "$.enrich.email"
        name: "$.enrich.name"
        source: "reddit"
  - tool: email.sequence.create
    input:
      template_id: "warm-nurture-v1"
      variables_from: "$.enrich.*"

pipeline: substack_lists
schedule: "30 9 * * 1"  # Mondays 09:30 IST
steps:
  - tool: newsletter.lists.search
    input: { topic: "B2B sales" }
  - tool: prospects.enrich { input: { from: "$.lists[*].author" } }
  - tool: crm.segments.upsert { input: { name: "Substack_B2B_Sales" } }

pipeline: warm_email_funnel
trigger: crm.event("prospect_engaged_but_not_converted")
steps:
  - tool: email.sequence.create { input: { template_id: "warm-7-step", tags: ["engaged"] } }
  - tool: email.sequence.schedule { input: { send_window: "IST 10:00–18:00" } }

pipeline: daily_lead_pulls
schedule: "0 8 * * *"  # Every morning 08:00 IST
steps:
  - tool: b2b.prospects.search { input: { filters: { industry: "SaaS", size: "2-50", geo: "IN,US,EU" }, limit: 100 } }
  - tool: crm.contacts.upsert { input_from: "$.prospects[*]" }

pipeline: realtime_crm_sync
trigger: email.event("reply|link_click|bounce")
steps:
  - tool: crm.activities.log { input_from: "$.email_event" }
  - tool: crm.deals.stage.update { input: { rule: "on_reply → move to Qualified" } }

All of the above are just declarative examples — the exact keys/fields come from your imported specs.

⏱️ Minute 13: Deploy

13. Click Deploy (or CLI: agentpass deploy --server leadgen-mcp).

14. Copy the MCP endpoint + credentials and paste into your agent runtime (e.g., your AI agent framework or desktop client) under External Tools → MCP.

⏱️ Minute 14: Go Live & Observe

15. Turn on schedules. Watch first runs in Runs/Logs. Fix mappings if any field names mismatch.

Example MCP Tool Mappings (Auto‑Generated from OpenAPI)

Below is a sample of how an imported endpoint becomes an MCP tool your agent can call:

{
  "name": "crm.contacts.upsert",
  "description": "Create or update a contact by email",
  "input_schema": {
    "type": "object",
    "properties": {
      "email": { "type": "string" },
      "name": { "type": "string" },
      "company": { "type": "string" },
      "source": { "type": "string" }
    },
    "required": ["email"]
  },
  "output_schema": {
    "type": "object",
    "properties": { "id": { "type": "string" }, "status": { "type": "string" } }
  }
}

{
  "name": "reddit.search",
  "description": "Search posts/comments for buying intent",
  "input_schema": {
    "type": "object",
    "properties": {
      "query": { "type": "string" },
      "subs": { "type": "array", "items": { "type": "string" } },
      "timeframe": { "type": "string", "enum": ["last_24h","last_7d"] },
      "limit": { "type": "integer" }
    },
    "required": ["query"]
  },
  "output_schema": { "type": "array", "items": { "type": "object" } }
}

The Lead Gen Hacks (Now as Concrete Flows)

• Reddit Lead Gen → Daily scheduled search → enrich → upsert to CRM → auto‑enroll in warm sequence.

• Substack/Newsletter → Weekly discovery of niche authors → enrich → segment in CRM.

• Warm Email Funnel → Event‑driven, triggered by engagement but no conversion → start 5–7 step nurture.

• Daily Lead Pulls → Morning prospect fetch → enrich → CRM.

• CRM Sync → Real‑time updates from email events (replies, clicks, bounces) to contacts/deals.

Prompts I Use for the Agents

Prospect parser (Reddit):

"Find posts/comments that express buying intent for CRM/outreach tools. Return JSON with: title, url, author, inferred company/domain, problem statement, and evidence snippet."

Personalizer (Email):

"Given {prospect_json}, generate 3‑line opener referencing their post and problem, then map them to template warm-7-step variables."

Qualifying rule:

"If no company/email found, enrich via prospects.enrich with LinkedIn/GH handles before CRM upsert."

Governance & Safety (2 mins)

• Use role‑based access and least‑privilege scopes.

• Log every tool call with inputs/outputs (PII redaction where needed).

• Respect site & API Terms of Service; use official endpoints or authorized data sources.

💡 The Result

My outreach engine now runs on autopilot — all triggered from one MCP server. Daily buyer‑intent capture, automatic enrichment, instant CRM updates, and warm sequences without manual effort.

If you want, I can adapt these pipelines to your exact tools (HubSpot vs Pipedrive, Mailgun vs Gmail, etc.) and drop in ready‑to‑run configs.

This is the complete, step‑by‑step playbook for how I automated daily lead flow, GTM triggers, and content production using Agentpass MCP servers. It includes architecture, exact agent setups, tool definitions, prompts, schedules, QA gates, and troubleshooting.

📌 Table of Contents

1. Quickstart (2 minutes)

2. System Architecture (at a glance)

3. Lead Gen Automation (deep dive)

4. GTM Automation (deep dive)

5. Content Automation (deep dive)

6. Agent & Tool Setup (MCP configs)

7. Schedules, Alerts & QA

8. Data Model & Dashboards

9. Templates (emails, prompts, checklists)

10. Compliance, Limits & Troubleshooting

11. Maintenance Cadence

1) ⚡ Quickstart (2 Minutes)

Prereqs

• Agentpass account with MCP servers enabled

• API access for: your CRM (e.g., HubSpot/Pipedrive), Outreach tool (e.g., Smartlead/Apollo), Data/enrichment (your choice), Docs (Google Drive/Notion)

• OAuth/API keys handy

The 2‑minute path

1. Create MCP Server → Agentpass › MCP Servers › New.

2. Import OpenAPI specs for the tools you’ll use (CRM, Outreach, Enrichment, Docs). Agentpass auto‑generates MCP tool definitions.

3. Connect Auth → add OAuth/API keys in Secrets.

4. Provision 3 core agents (templates below):

   • LeadHarvester (find + enrich + verify)

   • GTMWatcher (monitor competitors + detect triggers)

   • ContentStudio (generate + queue content in your voice)

5. Set default schedules (see §7): daily for LeadHarvester, hourly for GTMWatcher, daily for ContentStudio.

6. Run “Dry Test” (see QA checks) on a sandbox list before you go live.

Result: daily fresh leads in CRM + segmented by GTM triggers, outreach auto‑queued, content ideas/posts drafted, and KPI logging turned on.

2) 🧱 System Architecture (at a glance)

[Signals/APIs]
   ├─ Funding/Hiring/Tech tags
   ├─ Competitor sites/PR pages
   └─ Social & trend feeds
        │
        ▼
[MCP Tools via Agentpass]
   ├─ leads.search / leads.enrich / email.verify
   ├─ gtm.detect_triggers / web.diff
   ├─ outreach.create_sequence / send / pause
   ├─ crm.upsert_contact / upsert_company / dedupe
   ├─ docs.write / slides.update / storage.put
   └─ analytics.track
        │
        ▼
[Agents]
   ├─ LeadHarvester → segmented CRM + verified contacts
   ├─ GTMWatcher → trigger events → campaigns/decks
   └─ ContentStudio → ideas → drafts → queue
        │
        ▼
[Destinations]
   ├─ CRM & Outreach
   ├─ Docs (Notion/Drive)
   └─ BI/Dashboard (Sheets/DB)

3) 🔍 Lead Gen Automation (deep dive)

Goal: Daily net‑new, enriched, verified contacts/accounts, segmented by GTM triggers.

3.1 Sources (choose any)

• ICP lookalikes from your prospecting tool

• Funding & hiring feeds

• Tech‑stack signals (public tags, partner directories)

• Inbound signups and webinar/lead‑magnet downloads

3.2 Enrichment Waterfall (example order)

1. company_enrich.v1 → website, size, industry, tech tags

2. contact_enrich.v1 → title, department, seniority

3. email_locator.v1 → work email discovery

4. email_verify.v1 → deliverability check (only valid proceed)

Policy: fail fast on missing domain/role; dedupe by (email || domain+title); cap daily adds to stay compliant.

3.3 Segmentation by GTM Triggers

• Funding (Seed–Series D) → route to “Momentum” sequence

• Hiring Spike (≥3 relevant roles in 14 days) → “Capacity” sequence

• Tech Change (added/removed category) → “Toolswap” sequence

• New Leader (C‑level/VP joined ≤90 days) → “New Charter” sequence

3.4 Push to Outreach + CRM Sync

• Create/Upsert Company → Upsert Contact → Attach Trigger tags

• Set owner, source, sequence_id, unsub_status=false

• Write analytics.track event: lead_created, sequence_assigned

3.5 QA Gates

• Block if: unverified email, role mismatch, personal email only

• Human review bucket for ambiguous titles and strategic accounts

4) 🛰️ GTM Automation (deep dive)

Goal: Detect market & competitor changes → trigger personalized actions.

4.1 Monitored Assets

• Pricing page, changelog, product pages, status/roadmap, docs/SDK pages

• Press/Newsroom, job posts of rivals, partner listings

4.2 Change Detection

• web.fetch → hash content → web.diff

• Parse diffs → classify: pricing, packaging, feature, ICP, positioning

• Emit gtm.trigger_detected with metadata (URL, old→new, confidence)

4.3 Automations Fired

• Campaigns: call outreach.create_sequence with variant copy tailored to the detected change

• Decks: slides.update to refresh comparison tables, pricing screenshots, proof points

• CRM Notes: append concise insight to open opps where competitor = X

• Alerts: Slack/email summary every hour with top‑priority diffs

4.4 Performance Tracking

• Attribute replies/meetings to originating trigger; compare baseline vs post‑change uplift

5) 📝 Content Automation (deep dive)

Goal: Idea → Draft → Review → Schedule, in your voice.

5.1 Idea Engine

• Inputs: trigger feed (from §4), audience FAQs, campaign calendar, product milestones

• content.generate.ideas → 10 hooks/day with angle, proof, CTA

5.2 Draft Factory

• content.generate.post with Voice Profile (tone, cadence, phrases to use/avoid)

• Variants: LinkedIn post, email, ad, carousel script

• Auto‑insert live stats, fresh screenshots, and namedrops (when permitted)

5.3 Review & Scheduling

• Queue to Notion/Docs → status = Needs Review

• On approval, push to scheduler (or manual post) and log content.published

5.4 ROI Loop

• Pull post/email metrics → analytics.track (views, clicks, replies, meetings)

• Weekly report: best hooks, channels, and formats

6) 🧩 Agent & Tool Setup (MCP Configs)

6.1 Example MCP Tool (OpenAPI excerpt)

openapi: 3.0.1
info: {title: CRM Upsert, version: 1.0.0}
paths:
  /crm/upsert_contact:
    post:
      operationId: upsertContact
      parameters: []
      requestBody:
        required: true
        content:
          application/json:
            schema:
              type: object
              properties:
                email: {type: string}
                first_name: {type: string}
                last_name: {type: string}
                company_domain: {type: string}
                title: {type: string}
                tags: {type: array, items: {type: string}}
      responses:
        '200': {description: ok}

6.2 Agent Definitions (conceptual)

agent: LeadHarvester
goal: Daily net-new ICP leads, enriched, verified, segmented
allowed_tools:
  - leads.search
  - leads.enrich
  - email.verify
  - crm.upsert_contact
  - outreach.create_sequence
guardrails:
  - never add unverified emails
  - respect daily_add_cap=200
schedule: RRULE:FREQ=DAILY;BYHOUR=8;BYMINUTE=0;BYSECOND=0
---
agent: GTMWatcher
goal: Detect competitor & market changes and trigger actions
allowed_tools: [web.fetch, web.diff, gtm.detect_triggers, slides.update, outreach.create_sequence, analytics.track]
schedule: RRULE:FREQ=HOURLY;BYMINUTE=5
---
agent: ContentStudio
goal: Generate ideas/drafts in my voice and queue for review
allowed_tools: [content.generate.ideas, content.generate.post, docs.write, analytics.track]
schedule: RRULE:FREQ=DAILY;BYHOUR=9

6.3 RBAC & Secrets

• Create roles: builder, operator, viewer

• Secrets policy: scoped tokens per tool; rotate monthly

• Tool access matrix: only agents that need a tool can call it

7) ⏱️ Schedules, Alerts & QA

Default Schedules

• LeadHarvester: daily 08:00 local

• GTMWatcher: hourly (5th minute)

• ContentStudio: daily 09:00 local

Alerts

• Failure → immediate notification with error + last payload

• Threshold alerts: bounce rate > 3%, reply rate < baseline − 30%, daily lead adds > cap

QA Checkpoints

• Pre‑production: 100‑lead sandbox → verify fields, sequences, dedupe

• Weekly sampling: 50 leads, 10 posts, 3 trigger diffs

8) 📊 Data Model & Dashboards

Core Entities

• account(id, domain, industry, size, tech_tags)

• contact(id, email, role, seniority, owner)

• trigger_event(id, type, source_url, detected_at, metadata)

• campaign_action(id, sequence_id, contact_id, status)

• content_asset(id, type, status, url)

• engagement_event(id, kind, ref_id, metric, value)

Sample KPIs

• New verified contacts/day

• Reply & meeting rates by trigger type

• Content → meetings attribution

9) 🧩 Templates

9.1 Email Sequence Starters

Email 1 — Pattern Disrupt + Social Proof

Subject: Probably not for you

Saw the {{trigger}} at {{company}}. If GTM is recalibrating, we just helped a peer cut ramp time by 37% using an agent‑powered workflow. Worth a 7‑min walk‑through?

Email 2 — Reverse Psychology

If the team already solved this with internal tooling, ignore me. If not, happy to share the checklist we used to get reply rates from 1.8% → 6.4% after a {{trigger}}.

Email 3 — Value Drop

Here’s the 3‑step play we run when a competitor changes pricing: (1) capture diffs, (2) swap talking points in deck, (3) re‑target affected accounts. Steal it?

9.2 Content Prompts (Voice Profile)

You are my writing co‑pilot. Tone: concise, credible, a bit playful. Avoid hype words. Use concrete numbers and process. Output LinkedIn post: 120–180 words, 1 hook, 3 bullets, 1 CTA.

9.3 MCP Runbook Checklist

• Secrets added & scoped

• Tools imported from OpenAPI

• Agents provisioned with guardrails

• Schedules + alerts set

• Sandbox test passed

• Go‑live with caps

10) 🛡️ Compliance, Limits & Troubleshooting

Compliance

• Respect regional email & data laws. Honor unsubscribes. Only process business‑relevant data.

Rate Limits

• Stagger calls; batch writes; exponential backoff on 429s.

Common Issues

• High bounces → tighten email verification, reduce catch‑all domains

• Low replies → tighter ICP, rewrite first lines around triggers, test 2 CTAs

• Bad diffs → improve selectors, ignore layout‑only changes, raise confidence threshold

• Content off‑voice → refine Voice Profile with do/don’t examples

11) 🧼 Maintenance Cadence

• Weekly: QA samples, refresh sequences, archive stale triggers

• Monthly: Rotate tokens, audit permissions, retrain prompt examples

• Quarterly: Review ICP, adjust scoring/AI priorities, prune tools not in use

🚀 Why MCP Should Be on Your Radar
Model Context Protocol (MCP) is the missing layer between LLMs and tools.
It’s what allows an AI agent to:

• Talk to any API

• Use any tool

• Do it safely & consistently

If you’ve ever struggled with brittle API integrations or hacky prompt workarounds, MCP is your way out.

Your 30-Day MCP Roadmap

📅 Week 1 — Fundamentals

• Read the MCP spec (lightly—just enough to get the overview)

• Understand how MCP defines resources and capabilities

• Learn the difference between MCP “tools” vs. OpenAI function calling
  🎯 Goal: Know what MCP is and the problems it solves

📅 Week 2 — Deploy Free MCP with AgentPass.ai

• Create a free account at AgentPass.ai

• Import your OpenAPI spec (or build tools visually from scratch)

• Add authentication (OAuth, API keys, custom flows — all managed in one dashboard)

• Organize tools by function (CRM, billing, comms)

• 1-click deploy with auto-scaling & 99.99% uptime
  💡 Make a model call a tool through MCP at least once — you’ll “get it” instantly.

📅 Week 3 — Real Integrations

• Wrap a real API you actually use (Notion, Slack, Google Sheets)

• Handle authentication fully inside MCP

• Add parameters & validation so the model can’t break things
  🎯 Goal: Build a reliable integration you could actually use tomorrow.

📅 Week 4 — Production-Ready

• Add error handling & retries

• Test with different LLMs (OpenAI, Claude, local models)

• Deploy your MCP server so it’s accessible from anywhere
  🎯 Goal: Ship an MCP integration you trust in production.

By Day 30, You’ll Be Able To:
✅ Understand MCP spec basics
✅ Have 1–2 real tools wrapped
✅ Connect them to any LLM agent

💡 Master MCP now, and you’ll be ahead of 95% of AI builders.

Blueprint

• Lead Generation

  • Persuasive Written Content (Actionable, Personal & Growth) - (Platforms like X (Twitter) & Linkedin Are good platforms to test ideas and get feedback rapidly before recording and commissioning videos.)

  • Persuasive Video Content (Actionable, Personal & Growth)

Flow:

-> (X)Twitter/Linkedin

-> Youtube Long-form,

-> Shorform (Youtube Shorts , TikTok, IG Reels)

-> Traffic (Organic/Paid)

-> Optin/Lead Magnet

-> Offer/Product

-> Community

-> Email sequence 5-10 Day Sequence

-> Hard Sell

-> Newsletter

How do we bulletproof our email marketing to ensure we get the highest open rates and CTR?

This is where Zapier comes in. When we collect the email with our lead magnet and then we’ll have a trigger in Zapier that verifies if the email is legit (Neverbounce) before they are added to our email sequence.

Having a community allows them to get direct access to you, community members (Social Proof) and more transformative courses.

Day 0

Email 1: Welcome Email with a High-Value Bonus (Something that moves them closer to their goal)

Day 1

Email 2: Value Content (Video that directs them to a publish)

Email 3: Invite to a free exclusive community (Skool/Discord)

Email 4: Value Content

Day 2

Email 5: Actionable Content

Day 3

Email 6: Value Content

Email 7: Actionable Content

Email 8: Value Content

Day 4

Email 9:Transformations/Case Study + Offer

Day 5

Email 10: Hard Sell

Day 6

Email 11: Offer expiering

Day 7

Email 12: Last chance offer.

Begin Automated Newsletter

If they buy use Zapier to remove them from the sequence & add them to your automated newsletter.

If they don’t buy but are engaged with your email sequence drop them in your automated newsletter.

Automated Newsletter (You are able to sell your offer organically without it feeling like you’re selling)

Tools

• ChatGPT (Content Gen)

• Stack AI (AI Persona)

• Zapier - Bulletproofing our email marketing & Publishing content

• Make - Automating Newsletter with OpenAI, Midjourney

• Landing Pages - Carrd, Kartra, Thrivecart, ClickFunnels

• Email/CRM - Kartra, Kajabi, Convertkit, Mailchimp

• Automated Newsletter - Make/Zapier, Notion, OpenAI, Cluade 2, Midjourney

• Course - Discord, Skool, Kartra, Kajabi

• Midjourney

• Generating thumbnails, newsletter images, memes

• Skool

An open membership that builds trust and sells products & services to you. This is a better option than using Discord because the lead doesn’t have to download or sign in to an application to get to your content. It removes friction.

Lead Generation

• Organic Content

• A call to action in every written post that performs well.

• A call to action on every long-form and short-form video.

• A call to action in every newsletter

• Paid Ads

• Run proven organic content as ads because they are.

Because of the traffic coming from platforms where people watched and like your content, your community becomes a mega mind of like-minded individuals that creates a wave of social proof.

This is how I build and automated my publishing business that helps 300+ writers and storytellers automate 90% of their writing while maintaining a human touch,

Adding Fuel with Conversation AI Bots That Sell.

You can add these bots to your funnel, and community, that's available 24/7 to guide your visitors & qualify them.

Conversation AI Bots vs Chatbots.

Both Conversation AI Bots and traditional Chatbots have their own strengths and weaknesses, especially when applied to service-based businesses, high-ticket coaches, and educators.

Here's a breakdown:

Conversation AI Bots:

Pros:

Deep Learning: Conversation AI bots, like those based on the GPT architecture, utilize deep learning. This means they can understand the context better and provide more human-like responses.

Adaptive Learning: They can adapt and learn from user interactions over time, improving the quality of their responses.

Personalization: They can offer personalized interactions based on user input, making the conversation feel more tailored to individual users.

Versatility: They can handle a wide range of topics and can be used for various purposes, from answering FAQs to providing detailed explanations on complex topics.

Reduced Training Time: Unlike rule-based chatbots, they don't require extensive manual input for every possible question and can generate answers to questions they've never seen before.

Cons:

Cost: Advanced AI models can be expensive to implement.

Dependence on Data: Their effectiveness is highly dependent on the quality and quantity of training data.

Traditional Chatbots:

Pros:

Deterministic Responses: They provide consistent answers every time, based on predefined rules.

Low Overhead: They are generally less resource-intensive than AI-driven bots.

Easy to Implement: Many platforms offer easy-to-use tools for setting up rule-based chatbots.

Control: Businesses have complete control over the responses, ensuring that the bot won't provide unexpected or off-brand answers.

Cons:

Limited Flexibility: They can only answer questions they've been specifically programmed to handle.

Lack of Context Understanding: They can't understand the context or nuance in a conversation, leading to potential misunderstandings.

Time-Consuming Setup: Each potential question and answer must be manually inputted, which can be time-consuming for complex topics.

Less Engaging: They might come off as robotic or impersonal, which can be off-putting to some users.

Application to Service-Based Businesses, High-Ticket Coaches & Educators:

Engagement: For high-ticket coaches and educators, engagement is crucial.

Conversation AI bots can provide a more engaging and personalized experience, making potential clients or students feel more valued.

Information Dissemination: Service-based businesses often have to answer a lot of similar queries. While traditional chatbots can handle FAQs efficiently, Conversation AI bots can provide detailed, personalized answers, enhancing the user experience.

Trust Building: Especially for high-ticket items, trust is paramount. A bot that can understand and respond to nuanced queries can help in building that trust.

Cost Consideration: For smaller businesses or individual coaches, the cost might be a significant factor. In such cases, a well-implemented traditional chatbot might be more feasible than a sophisticated AI bot.

The choice between Conversation AI bots and traditional chatbots depends on the specific needs, budget, and goals of the service-based business, coach, or educator.

Do you need AI Bots? Of course not.

This is only an extra layer for coaches and consultants who are generating large amounts of traffic and want to eliminate ~60% of lost leads.

Bot Builders & Container.

• Botpress (www.botpres.com)

• Manychat (Instagram & Messenger) (www.manychat.com)

• Chatfuel (chatfuel.com)

• Whatsapp

• Telegram

• SMS (Twilio)

AI Integration

• Dialogflow AI (https://dialogflow.cloud.google.com/)

• Janis AI (

https://www.janis.ai/

• )

• Stack AI (www.stack-ai.com)

• GPT-4

Training Conversation AI Bot

Training a Conversational AI Chatbot involves a systematic approach to ensure that the bot is effective, accurate, and provides a seamless user experience. Here are the 10 most important steps in training such a bot:

Define the Purpose and Scope:

Determine what you want the chatbot to achieve. Is it for customer support, sales inquiries, general information, or something else?

Decide on the topics and areas the chatbot should cover and what it should avoid.

Gather Data:

Collect conversational data relevant to the bot's purpose. This could be chat logs, customer support transcripts, FAQs, etc.

Ensure the data is diverse and covers various user intents and phrasings.

Choose the Right Model and Platform:

Depending on your needs, decide whether to go for a rule-based, retrieval-based, or generative model.

Select a platform or framework that supports your chosen model and offers the tools you need for training and deployment.

Pre-process the Data:

Clean the data by removing irrelevant or sensitive information.

Tokenize and format the data to make it suitable for training.

Initialize the Model:

If available, start with a pre-trained model that has a general language understanding.

This can speed up training and improve performance, especially if your dataset is limited.

Train the Model:

Feed your processed data into the model.

Monitor the training process for signs of overfitting or other issues.

Evaluate and Test:

Once training is complete, evaluate the model's performance on a separate test dataset.

Conduct user testing sessions to see how real users interact with the bot and gather feedback.

Iterate and Fine-tune:

Based on evaluations and user feedback, identify areas where the bot falls short.

Fine-tune the model or retrain it with additional data to address these shortcomings.

Implement a Feedback Loop:

Once deployed, allow users to provide feedback on the bot's responses.

Use this feedback to continuously improve the bot's performance and accuracy.

Monitor and Update Regularly:

Language and user needs evolve over time. Regularly monitor the bot's interactions to identify new trends or topics.

Update the training data and retrain the model as needed to keep it relevant and effective.

Remember, training a Conversational AI Chatbot is an ongoing process. Regular updates and iterations are crucial to ensure that the bot remains effective and provides users with the best possible experience.

Prompt 1

I'm selling a {solution} that helps people achieve {benefit/outcome}. Give me 5 buyer persona I can target in my cold outreach. Include their pain pint, content I should create to overcome their objections, and what channel I can find them on.

Prompt 2

(continue in the same chat)

Give me 7 pain points for buyer persona {#1}. Based on that, how can they use {solution}?

Prompt 3

I sell {solution} to {target audience} Give me 5 objections they might have and how I can overcome them in my marketing.

Prompt 4

My target audience is {audience}. What marketing channels Should I focus on to reach them? And argue

about why I Should choose them.

Prompt 5

I'm interested in promoting {}, and I believe that collaborating with {LinkedIn outreach} influencers

can be a great way to reach a wider audience. Can you please provide me with the top {10} {LinkedIn

outreach} influencers, along with the links to their profiles, and a brief explanation of why they are great

choices? Organize all data into the table.

#2. Prepare your Linkedin account for cold outreach

Prompt 6 (for headline)

I'm {X}, {occupation}. My current headline is:{ "Y"}Come up with {10} different texts for the headline of my Linkedin Profile based on the current version but make it more {funny}. The target audience is

{Saas founders}. Add emojis.

Prompt 7 (Summary)

Come up with 5 options for the Linkedln About section text based on my resume. Use my work experience and include {my total years of experience}, the keyword {'marketing manager'}, and keep it shorter than {150 words}. Make in a {storytelling style}. Include bullet points to increase readability.

#3 Content creation

Prompt 8

Name {5} relevant topics I can create content around for a {LinkedIn automation SaaS} to inform users {so they

can make a purchase}

Prompt 9

• My target audience is {persona} and I help them achieve {outcome}. Give me 10 posts I can create to

generate leads.

Prompt 10

• I'm the CEO of {solution}. Create a content plan based on {the target audience's} pain points. The goal is to get them to message me and sign up for a free consultation. So, I want you to give me topics that are relevant when it comes to decision-making.

Prompt 11

What topic would help {the audience} want to make a purchase or get on a call with me? Give me 5 post-topic ideas.

Prompt 12

Can you help me write a LinkedIn post about {growth hack1 for LinkedIn cold outreach}? I want to share some tips and tricks for reaching out to potential clients through LinkedIn, but I'm not sure where to start. Please provide a post that is informative, engaging, and helpful for my network. Make this text up to {400} words.

Made it in {storytelling} style. Make it {funny and practical}. Add emoji1 and bullet points if need be.

Prompt 13

My writing style is based on {influence} and I run a company {URL}. Can you create a LinkedIn post under 250 words on {topic} to achieve {outcome} for {target audience}?

Prompt 14

The {following URL} is a blog post I wrote. Can you go through it and tell me what the writing tone of voice is

like? Then, create a similar post about {topic}.

Prompt 15

The following text is a blog post I wrote on {topic}. Can you emulate this writing style and repurpose the article into a 200 word LinkedIn post.Now you’re ready for your Linkedin outreach game.

#4. Scraping and enriching your lead database

Prompt 16

I need a Google Apps Script function that utilizes the Google Custom Search API to find a {Person's name} and {Linkedin profile} from a {company name} and {job title}.

#5. Prepare your contacts Database before outreach

Prompt 17

Create a Google Sheets formula that extracts a clean company name from a cell containing a URL or domain name, which may include 'www', 'https://', and other prefixes. Additionally, remove common suffixes like 'LTD', 'LLC', and 'Inc' from the extracted company name.

Prompt 18

Develop a Google Sheets formula that replaces unusual Latin letters in a list of names with their English

counterparts. Ensure the formula covers multiple Latin characters, such as 'ø', 'à', 'é', and others, converting them to the closest English equivalents.

Prompt 19

(imagine you have a list of company names, but you need to find their domains for better research. GPT can help you with it)

Create a Google Sheets solution to find the company domain from a given company name using external

search engine APls, such as Bing Web Search API. Ensure that the formula returns the most relevant domain for each company name while taking into account any limitations and terms of service associated with the chosen API.

#6. ChatGPT prompts for cold emails

Prompt 20

Write a cold email to a prospect in the {Sales Industry}. Their main pain points are {not generating enough qualified leads at scale, and manually trying to reach leads on Linkedln one by one which is proving to be time-consuming}. The solution we offer is {Linkedin outbound software}. Keep the email within 100 words. I scraped {Linkedln event attendees}. So I know their {emails}, {Names}, and {Event name they will attend}. Add

variables based on this data.

Prompt 21

I'm writing a cold Linkedin message to {} from {}. Could you create a quick message using some news or articles published in the media about {} to hook the attention in the first few lines.

Prompt 22

Use this email opening example: {"Yamini, I notice that you've been the CEO of HubSpot since 2021 and I wanted to reach out"} to write a casual email that is 50-100 words, consider that the person we're reaching out to is named {full_name} and they are the {title} of {company_name} since {formatted_date}. Include a 1-2

sentence case study of how we (case study example) and end with a CTA to book a 10-minute call.

Prompt 23

What are some of the best email subject lines that consistently get 70% open rates? Give me 10 examples. Exclude ones that sound robotic or bland.

Prompt 24

I'm following up with a prospect who hasn't replied for 8 days. Give me 5 different subject lines I can say.

Prompt 25

What elements can I include in my subject line so that it stands out in a lead's inbox?

Prompt 26

Give me an email follow-up template for a lead who hasn't replied after 7 days. Don't sound robotic and don't mention "I hope this email finds you well". Use FOMO and scarcity but don't make it sensational.

Prompt 27

The following is an email I sent to a prospect who hasn’t replied yet. Write a follow-up email with a similar writing style. Don’t sound robotic. Keep the tone casual and friendly.

Prompt 28

A Give me an email follow-up that incentivizes the prospect to reply. Keep it casual and friendly.

Prompt 29

What are some elements I can include in my follow-up to convince a lead to reply? I can give them a longer than usual free trial for my SaaS tool, give me more examples. I am the head of marketing and SEO at (company).

Prompt 30

I'm writing a cold email targeting agency owners. Give me 5 examples of personalization placeholders I can research and personalize for my campaign. Exclude {first name}.

Prompt 31

Give me 5 examples of personalization placeholders I can use for my target audience {persona}.

Prompt 32

Where can I look to personalize my emails based on (placeholders)?

Prompt 33

The following is a cold email I wrote for {persona}. Give me pointers on how I can make this more

personalized. Use placeholders if needed.

#7. ChatGPT prompts for LinkedIn outreach

Prompt 34

I want to reach out to {}{}. Could you please create a personalized outreach icebreaker (max 250 characters). It should start with "Hi" but in the language that is common in the location of this person (for example if Ukraine hi = Привіт, Italy hi= ciao, and so on), the whole text after it should be in English. The outreach should use "Common connection the real Person's

Name" as a reference to the reason why I'm reaching out to. Common connections: {info}

Prompt 35

Visit the post {Link to the Linkedin post}. Create a personalized comment I could leave that would show off my topic authority. Don’t sound robotic.

Prompt 36

Create a Linkedin connection request under 300 characters. Don't say how you came across their profile and don't sound robotic. Include a pain point agency owners face and why they should connect with me.

Prompt 37

I connected with {persona} on LinkedIn. Send a follow-up message to get on a call.Remember I am {persona}.

Prompt 38

Send a friendly, engaging message to a new connection called {name}. Don’t sound robotic and don’t sell

anything. Ask an engaging question in an attempt to establish a relationship.

Prompt #39

Imagine I'm cold calling marketing agency owner in my area Create a potential script making sure to:

-Ask for their permission to hear the pitch without coming across as too salesy

-Come across as casual and friendly

- Overcome any potential objection they might have

- Don't make it all about me

Prompt 40

Imagine you're a {marketing agency owner} that provide {lead generation service for B28 Company} I'm

pitching yu a {LinkedIn automation SaaS} you can {ues to automate certain action on Linkedin (such as

pending connection request, follow-up, and even email all from one platform)} What are some objections you might have? Phrasing them as questions?Then, explain to me 1-3 angles of how I could overcome the objections.