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Crm Automation

Organization
claude-office-skills
crm-automation

CRM workflow automation for HubSpot, Salesforce, Pipedrive - lead management, deal tracking, and multi-CRM synchronization

Overview

Publisherclaude-office-skills
Repositoryskills
Skill namecrm-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 Crm 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/crm-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/crm-automation .claude/skills/crm-automation
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Crm 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 Crm 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 Crm 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.

CRM Automation

Automate CRM workflows for HubSpot, Salesforce, and Pipedrive including lead management, deal tracking, pipeline automation, and multi-CRM synchronization. Based on n8n workflow templates.

Overview

This skill covers:

  • Lead capture and enrichment automation
  • Deal stage progression workflows
  • Multi-CRM data synchronization
  • Automated follow-up sequences
  • Sales analytics and reporting

Core Workflow Patterns

1. Lead Capture → Enrichment → Assignment

┌─────────────┐    ┌─────────────┐    ┌─────────────┐    ┌─────────────┐
│ Lead Source │───▶│ Enrich Data │───▶│ Score Lead  │───▶│ Route to    │
│ (Form/API)  │    │ (Clearbit)  │    │ (AI/Rules)  │    │ Sales Rep   │
└─────────────┘    └─────────────┘    └─────────────┘    └─────────────┘
                                                                │
                         ┌─────────────┐    ┌─────────────┐    │
                         │ Start       │◀───│ Create in   │◀───┘
                         │ Sequence    │    │ CRM         │
                         └─────────────┘    └─────────────┘

n8n Configuration:

yaml
workflow: "Lead Capture to CRM"

trigger:
  - type: webhook
    event: form_submission
    source: [website, landing_page, calendly]

steps:
  1. capture_lead:
      fields: [email, name, company, phone, source]
  
  2. enrich_data:
      provider: clearbit
      lookup_by: email
      append: [company_size, industry, title, linkedin]
  
  3. score_lead:
      model: ai_scoring  # or rule-based
      factors:
        - company_size: {1-50: 10, 51-200: 20, 201+: 30}
        - industry_fit: {high: 30, medium: 20, low: 10}
        - title_seniority: {c-level: 30, director: 20, manager: 10}
      threshold: 50  # MQL threshold
  
  4. route_lead:
      rules:
        - if: score >= 80 AND industry == "tech"
          assign_to: "Enterprise Team"
        - if: score >= 50
          assign_to: "SMB Team"
        - else:
          assign_to: "Marketing Nurture"
  
  5. create_in_crm:
      platform: hubspot
      object: contact
      properties:
        email: "{email}"
        firstname: "{first_name}"
        company: "{company}"
        lead_score: "{score}"
        lead_source: "{source}"
  
  6. start_sequence:
      if: score >= 50
      sequence: "New Lead Welcome"
      delay: 1_hour

2. Deal Stage Automation

yaml
workflow: "Deal Stage Progression"

trigger:
  - type: hubspot_deal_updated
    property: dealstage

stages:
  appointment_scheduled:
    actions:
      - create_task: "Prepare for meeting"
        due: 1_day_before_meeting
      - notify_slack: "#sales-pipeline"
      - update_property: last_activity_date
  
  qualified_to_buy:
    actions:
      - create_task: "Send proposal"
        due: 3_days
      - notify_manager: true
      - add_to_forecast: true
  
  presentation_scheduled:
    actions:
      - create_task: "Prepare demo environment"
      - send_reminder: 1_hour_before
      - log_activity: "Presentation scheduled"
  
  contract_sent:
    actions:
      - set_close_date: 14_days_from_now
      - create_task: "Follow up on contract"
        due: 7_days
      - notify_legal: if amount > 50000
  
  closed_won:
    actions:
      - notify_slack: "#wins"
      - trigger_onboarding: true
      - update_forecast: remove
      - celebrate: confetti  # Slack celebration
  
  closed_lost:
    actions:
      - log_loss_reason: required
      - add_to_nurture: true
      - schedule_reengagement: 90_days

3. Multi-CRM Synchronization

yaml
workflow: "HubSpot + Salesforce + Pipedrive Sync"

sync_rules:
  contacts:
    master: hubspot
    sync_to: [salesforce, pipedrive]
    frequency: real_time
    fields:
      - email (unique_key)
      - name
      - company
      - phone
      - owner
    conflict_resolution: most_recent_wins
    deduplication: 
      provider: openai
      similarity_threshold: 0.85
  
  deals:
    master: salesforce
    sync_to: [hubspot, pipedrive]
    frequency: every_15_minutes
    field_mapping:
      salesforce.Opportunity.Amount → hubspot.deal.amount
      salesforce.Opportunity.CloseDate → hubspot.deal.closedate
      salesforce.Opportunity.StageName → hubspot.deal.dealstage
  
  activities:
    aggregate_to: google_sheets
    types: [calls, emails, meetings, notes]
    columns: [date, contact, type, summary, outcome]

n8n Implementation:

javascript
// Multi-CRM Sync Node
{
  "nodes": [
    {
      "name": "Get HubSpot Contacts",
      "type": "n8n-nodes-base.hubspot",
      "parameters": {
        "operation": "getAll",
        "limit": 100,
        "additionalFields": {
          "propertiesToInclude": ["email", "firstname", "lastname", "company"]
        }
      }
    },
    {
      "name": "Get Salesforce Contacts",
      "type": "n8n-nodes-base.salesforce",
      "parameters": {
        "operation": "getAll",
        "sobject": "Contact"
      }
    },
    {
      "name": "Deduplicate with OpenAI",
      "type": "n8n-nodes-base.openAi",
      "parameters": {
        "operation": "message",
        "model": "gpt-4",
        "prompt": "Compare these contacts and identify duplicates: {{$json}}"
      }
    },
    {
      "name": "Sync to Master Sheet",
      "type": "n8n-nodes-base.googleSheets",
      "parameters": {
        "operation": "append",
        "sheetId": "your-sheet-id"
      }
    }
  ]
}

Lead Scoring Model

Rule-Based Scoring

yaml
lead_score_rules:
  demographic:
    job_title:
      - C-Level|VP|Director: +30
      - Manager|Head: +20
      - Individual Contributor: +10
    
    company_size:
      - 1-50: +10
      - 51-200: +20
      - 201-1000: +25
      - 1000+: +30
    
    industry:
      - Technology|SaaS: +30
      - Finance|Healthcare: +25
      - Manufacturing|Retail: +15
  
  behavioral:
    website_visits:
      - 1-2: +5
      - 3-5: +10
      - 6+: +20
    
    content_downloads:
      - Whitepaper: +15
      - Case Study: +20
      - Pricing Page: +25
    
    email_engagement:
      - Opened: +5
      - Clicked: +10
      - Replied: +20

thresholds:
  - MQL: 50
  - SQL: 75
  - Hot Lead: 90

AI-Based Scoring

yaml
ai_scoring_model:
  provider: openai
  prompt: |
    Score this lead from 0-100 based on:
    - Fit with our ICP (ideal customer profile)
    - Buying intent signals
    - Budget authority
    - Timeline urgency
    
    Lead Data: {lead_data}
    ICP: B2B SaaS companies, 50-500 employees, Series A+
    
    Return JSON: {"score": X, "reasoning": "...", "next_action": "..."}

Automated Sequences

Sequence 1: New Lead Welcome

yaml
sequence: "New Lead Welcome"
trigger: lead_created AND score >= 50

steps:
  - day_0:
      type: email
      template: "welcome_intro"
      subject: "Welcome to {Company} - Here's what's next"
  
  - day_2:
      type: email
      template: "value_prop"
      subject: "How {Similar_Company} achieved {Result}"
      condition: not_replied
  
  - day_4:
      type: task
      action: "LinkedIn connection request"
      assign_to: owner
  
  - day_7:
      type: email
      template: "case_study"
      subject: "Quick case study for {Lead_Company}"
      condition: not_replied
  
  - day_10:
      type: email
      template: "meeting_request"
      subject: "15 min to discuss {Pain_Point}?"
      include: calendly_link
  
  - day_14:
      type: task
      action: "Phone call attempt"
      assign_to: owner
      condition: not_responded

Sequence 2: Deal Follow-Up

yaml
sequence: "Proposal Follow-Up"
trigger: deal_stage == "contract_sent"

steps:
  - day_3:
      type: email
      template: "contract_check_in"
      subject: "Any questions about the proposal?"
  
  - day_7:
      type: task
      action: "Phone call - contract follow-up"
  
  - day_10:
      type: email
      template: "deadline_reminder"
      subject: "Pricing valid until {deadline}"
      condition: not_responded
  
  - day_14:
      type: alert
      notify: sales_manager
      message: "Deal stuck in contract stage"

Integration Recipes

Recipe 1: Calendly → HubSpot

yaml
trigger: calendly.booking_created

actions:
  1. search_contact:
      hubspot.search: email == calendly.invitee_email
  
  2. create_or_update:
      if: contact_exists
        hubspot.update_contact:
          last_meeting_booked: calendly.start_time
      else:
        hubspot.create_contact:
          email: calendly.invitee_email
          firstname: calendly.invitee_name
          lifecycle_stage: "salesqualifiedlead"
  
  3. create_meeting:
      hubspot.create_engagement:
        type: MEETING
        scheduled_time: calendly.start_time
        title: calendly.event_name
  
  4. notify:
      slack.send:
        channel: "#sales"
        message: "Meeting booked: {name} at {time}"

Recipe 2: LinkedIn → HubSpot

yaml
trigger: linkedin.connection_accepted

actions:
  1. enrich:
      linkedin.get_profile: connection_id
  
  2. create_contact:
      hubspot.create:
        email: linkedin.email
        firstname: linkedin.first_name
        lastname: linkedin.last_name
        jobtitle: linkedin.title
        company: linkedin.company
        linkedin_url: linkedin.profile_url
        lead_source: "LinkedIn"
  
  3. add_to_sequence:
      if: title contains ["CEO", "CTO", "VP"]
      sequence: "LinkedIn C-Level Outreach"

Reporting Templates

Weekly Sales Report

markdown
# Sales Pipeline Report - Week {week_number}

## Pipeline Summary
| Stage | Deals | Value | Change |
|-------|-------|-------|--------|
| New | 15 | $150K | +5 |
| Qualified | 8 | $120K | +2 |
| Proposal | 5 | $85K | -1 |
| Negotiation | 3 | $45K | +1 |
| **Total Pipeline** | **31** | **$400K** | **+7** |

## This Week's Activity
- New leads: 45
- Meetings held: 12
- Proposals sent: 4
- Deals closed: 2 ($35K)

## Team Performance
| Rep | Meetings | Proposals | Closed |
|-----|----------|-----------|--------|
| Alice | 5 | 2 | 1 |
| Bob | 4 | 1 | 1 |
| Carol | 3 | 1 | 0 |

## Forecast
- Commit: $45K (3 deals)
- Best Case: $85K (5 deals)
- Pipeline: $400K (31 deals)

## Actions Needed
- [ ] Follow up on 3 stale deals (>14 days no activity)
- [ ] Schedule demo for Enterprise Lead X
- [ ] Send revised proposal to Company Y

Best Practices

Data Hygiene

yaml
data_hygiene_rules:
  - deduplicate: weekly
    method: email_match + company_fuzzy_match
  
  - validate_emails: on_create
    action: remove_invalid
  
  - enrich_missing: daily
    fields: [company, title, linkedin]
  
  - archive_stale: monthly
    criteria: no_activity > 180_days
    action: move_to_archive

Security

yaml
security_practices:
  - api_keys: rotate_quarterly
  - access_control: role_based
  - audit_log: all_changes
  - pii_handling: encrypt_at_rest
  - gdpr_compliance: consent_tracking

CRM Automation Skill - Part of Claude Office Skills

Frequently asked questions

What does the Crm Automation AI skill do?

CRM workflow automation for HubSpot, Salesforce, Pipedrive - lead management, deal tracking, and multi-CRM synchronization

Why use Crm Automation on TypingMind?

Because you install it once and use it with any model. Crm 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 Crm Automation in TypingMind?

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

Which AI models can use Crm 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 Crm Automation?

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

Is the Crm 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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