Intercom Automation logo

Intercom Automation

Organization
claude-office-skills
Intercom Automation

Automate Intercom customer messaging, support workflows, user engagement, and product tours

Overview

Publisherclaude-office-skills
Repositoryskills
Skill nameIntercom Automation
Stars
514
Forks
97
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by claude-office-skills on GitHub. Read the source before you install it.

Installation

Install the Intercom Automation AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/claude-office-skills/skills/tree/main/intercom-automation
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/claude-office-skills/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/intercom-automation .claude/skills/claude-office-skills-intercom-automation
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Intercom Automation in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Intercom Automation on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Intercom Automation is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Intercom Automation

Comprehensive skill for automating Intercom customer communication and support workflows.

Core Workflows

1. Conversation Flow

CUSTOMER CONVERSATION FLOW:
┌─────────────────┐
│  User Message   │
│   (Inbound)     │
└────────┬────────┘
         ▼
┌─────────────────┐
│   Bot Triage    │
│  - Intent       │
│  - Route        │
└────────┬────────┘
         │
    ┌────┴────┐
    ▼         ▼
┌───────┐ ┌───────┐
│  Bot  │ │ Human │
│ Reply │ │ Agent │
└───┬───┘ └───┬───┘
    │         │
    └────┬────┘
         ▼
┌─────────────────┐
│   Resolution    │
│  - Close        │
│  - Follow-up    │
└─────────────────┘

2. Automation Rules

yaml
automations:
  - name: welcome_new_users
    trigger:
      event: user.created
      conditions:
        - signed_up_at: within_last_hour
    action:
      send_message:
        type: chat
        delay: 5_minutes
        message: |
          Hey {{first_name}}! 👋
          
          Welcome to {{company_name}}! I'm here to help you 
          get started. What brings you here today?
        buttons:
          - "Explore features"
          - "I have a question"
          - "Just looking around"
          
  - name: trial_expiring
    trigger:
      event: user.attribute_changed
      attribute: trial_days_remaining
      value: 3
    action:
      send_message:
        type: email
        template: trial_expiring
        
  - name: feature_announcement
    trigger:
      segment: power_users
      event: feature_released
    action:
      send_message:
        type: in_app
        message: "🎉 New Feature: {{feature_name}}"

User Segmentation

Segment Definitions

yaml
segments:
  - name: trial_users
    filter:
      subscription_status: trial
      
  - name: power_users
    filter:
      sessions_count: "> 50"
      last_seen: "< 7 days"
      features_used: "> 5"
      
  - name: at_risk_users
    filter:
      subscription_status: active
      last_seen: "> 30 days"
      
  - name: enterprise_prospects
    filter:
      company_size: "> 100"
      plan: free
      
  - name: feature_requesters
    filter:
      tag: feature_request
      conversations_count: "> 0"

Dynamic Attributes

yaml
custom_attributes:
  - name: health_score
    type: number
    compute: |
      (sessions_last_30_days * 2) +
      (features_used * 3) +
      (team_members_active * 5)
      
  - name: lifecycle_stage
    type: string
    rules:
      - condition: signed_up_at < 7_days
        value: "onboarding"
      - condition: subscription_status == "trial"
        value: "trial"
      - condition: subscription_status == "active"
        value: "customer"
      - condition: subscription_status == "cancelled"
        value: "churned"
        
  - name: account_tier
    type: string
    source: company.plan

Messaging Campaigns

Onboarding Series

yaml
onboarding_campaign:
  name: "New User Onboarding"
  audience: 
    segment: new_signups
    
  messages:
    - day: 0
      channel: in_app
      content: |
        Welcome to {{company}}! 🎉
        
        Let me show you around. Click below to take a 
        quick 2-minute tour.
      cta: "Start Tour"
      
    - day: 1
      channel: email
      subject: "Quick tip: {{feature_1}}"
      content: |
        Hi {{first_name}},
        
        Did you know you can {{feature_1_benefit}}?
        
        Here's how: {{feature_1_tutorial_link}}
        
    - day: 3
      channel: in_app
      trigger: 
        not_completed: "setup_wizard"
      content: |
        Hey {{first_name}}, I noticed you haven't 
        finished setting up. Need any help?
        
    - day: 7
      channel: email
      subject: "How's it going?"
      content: |
        Hi {{first_name}},
        
        You've been using {{company}} for a week now.
        
        Any questions or feedback? Just reply to this email!

Product Tours

yaml
product_tours:
  - name: "Welcome Tour"
    trigger:
      event: first_login
    steps:
      - element: "#dashboard"
        title: "Your Dashboard"
        body: "This is where you'll see your key metrics"
        position: bottom
        
      - element: "#create-button"
        title: "Create New"
        body: "Click here to create your first project"
        position: left
        
      - element: "#help-menu"
        title: "Need Help?"
        body: "Find docs and contact support here"
        position: bottom
        
  - name: "Feature Tour: Reports"
    trigger:
      event: page_viewed
      url: "/reports"
      first_time: true
    steps:
      - element: "#date-picker"
        title: "Date Range"
        body: "Select your reporting period"

Support Workflows

Conversation Routing

yaml
routing_rules:
  - name: vip_priority
    conditions:
      - company.plan: enterprise
    actions:
      - set_priority: urgent
      - assign_team: enterprise_support
      - send_notification: slack_vip
      
  - name: billing_issues
    conditions:
      - message_contains: ["billing", "charge", "invoice", "refund"]
    actions:
      - add_tag: billing
      - assign_team: billing_support
      
  - name: technical_support
    conditions:
      - message_contains: ["error", "bug", "not working", "broken"]
    actions:
      - add_tag: technical
      - assign_team: tech_support
      - create_ticket: jira

Bot Responses

yaml
bot_responses:
  - intent: greeting
    patterns: ["hi", "hello", "hey"]
    response: |
      Hi there! 👋 How can I help you today?
      
  - intent: pricing
    patterns: ["pricing", "cost", "how much", "plans"]
    response: |
      Great question! Here's our pricing:
      
      • **Starter**: $29/mo
      • **Growth**: $79/mo
      • **Enterprise**: Custom
      
      Would you like me to connect you with sales?
    buttons:
      - "Yes, talk to sales"
      - "See full comparison"
      
  - intent: password_reset
    patterns: ["forgot password", "reset password", "can't login"]
    response: |
      No problem! You can reset your password here:
      {{password_reset_link}}
      
      The link will expire in 24 hours.
    auto_close: true

Analytics & Reporting

Conversation Metrics

SUPPORT METRICS - THIS WEEK
═══════════════════════════════════════

Conversations:
New:          234 (+12%)
Closed:       256 (+8%)
Open:         45

Response Times:
First Reply:  2.3 min (target: 5 min) ✓
Median:       8 min
Resolution:   2.4 hours

CSAT Score:   4.7/5 ⭐ (+0.2)

BY CHANNEL:
Chat      ████████████░░░░ 156
Email     ██████░░░░░░░░░░ 58
In-App    ████░░░░░░░░░░░░ 20

TOP TOPICS:
┌────────────────────┬───────┐
│ Topic              │ Count │
├────────────────────┼───────┤
│ Billing questions  │ 45    │
│ Feature requests   │ 38    │
│ Bug reports        │ 32    │
│ How-to questions   │ 28    │
└────────────────────┴───────┘

Engagement Dashboard

yaml
engagement_metrics:
  - name: message_open_rate
    formula: opened / sent * 100
    target: 40%
    
  - name: click_through_rate
    formula: clicked / opened * 100
    target: 10%
    
  - name: tour_completion_rate
    formula: completed / started * 100
    target: 60%
    
  - name: bot_resolution_rate
    formula: resolved_by_bot / total * 100
    target: 30%

Integration Workflows

CRM Sync

yaml
crm_integration:
  salesforce:
    sync_fields:
      - intercom: company.name
        salesforce: Account.Name
      - intercom: user.email
        salesforce: Contact.Email
      - intercom: custom.mrr
        salesforce: Account.MRR__c
        
    events:
      - trigger: conversation_closed
        action: log_activity
        type: "Support Interaction"
        
      - trigger: user.tag_added
        tag: "sales_qualified"
        action: create_lead

Slack Integration

yaml
slack_integration:
  notifications:
    - trigger: new_conversation
      channel: "#support-inbox"
      conditions:
        - priority: urgent
      message: "🚨 Urgent: {{user.name}} needs help"
      
    - trigger: conversation_assigned
      notify: assignee_dm
      message: "New conversation assigned to you"
      
  commands:
    /intercom:
      - lookup_user
      - send_message
      - add_tag

API Examples

Create or Update User

javascript
// Create/Update User
const user = await intercom.users.create({
  user_id: "12345",
  email: "user@example.com",
  name: "John Doe",
  signed_up_at: Math.floor(Date.now() / 1000),
  custom_attributes: {
    plan: "pro",
    team_size: 10,
    onboarding_complete: true
  }
});

// Send Message
await intercom.messages.create({
  message_type: "inapp",
  body: "Hey! New feature alert 🎉",
  from: {
    type: "admin",
    id: "admin_id"
  },
  to: {
    type: "user",
    user_id: "12345"
  }
});

// Search Conversations
const conversations = await intercom.conversations.search({
  query: {
    field: "state",
    operator: "=",
    value: "open"
  }
});

Best Practices

  1. Personalize Messages: Use user attributes
  2. Time Appropriately: Consider user timezone
  3. Don't Over-Message: Respect frequency limits
  4. Bot + Human: Know when to escalate
  5. Track Everything: Measure message effectiveness
  6. Segment Thoughtfully: Target the right users
  7. A/B Test: Optimize message content
  8. Quick Resolution: Minimize response time

Frequently asked questions

What does the Intercom Automation AI skill do?

Automate Intercom customer messaging, support workflows, user engagement, and product tours

Why use Intercom Automation on TypingMind?

Because you install it once and use it with any model. Intercom Automation is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Intercom Automation in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/claude-office-skills/skills/tree/main/intercom-automation. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Intercom Automation?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Intercom Automation?

As many as you like. As long as a model supports skills, you can use Intercom Automation with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Intercom Automation AI skill free?

Yes. It is published on GitHub by claude-office-skills under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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