playbooks

home / skills / zpankz / mcp-skillset / lindy-expert

lindy-expert skill

/lindy-expert

This skill helps you implement Lindy expert workflows for email, CRM, and automation across Google Workspace and HubSpot.

npx playbooks add skill zpankz/mcp-skillset --skill lindy-expert

Review the files below or copy the command above to add this skill to your agents.

Files (4)
SKILL.md
2.9 KB
---
name: lindy-expert
description: Lindy is an AI agent creation and management platform focused on business process automation. It enables organizations to build sophisticated AI-powered assistants that can handle communication across...
license: Complete terms in LICENSE.txt
---

# Lindy Expert

Lindy is an AI agent creation and management platform focused on business process automation. It enables organizations to build sophisticated AI-powered assistants that can handle communication across multiple channels, execute complex workflows, and integrate with major business tools like Google Workspace and HubSpot.

The platform distinguishes itself through its comprehensive approach to automation, combining voice capabilities, data management, and deep integration features with popular business platforms. It appears designed for teams seeking to implement AI-driven automation while maintaining control and visibility over their processes.

## Core Capabilities

This skill provides specialized knowledge and workflows for:

- Email automation and management
- Marketing automation and focus group simulation
- Voice/Phone call automation
- Data enrichment and management
- CRM automation via HubSpot
- Document and spreadsheet automation
- Complex workflow orchestration
- Automated business communications

## When to Use This Skill

Use this skill when:
- You need to work with lindy expert
- You're implementing features that involve these use cases
- You need guidance on best practices and patterns

## Ecosystem & Alternatives

**Category**: AI Agent Management Platforms, Business Process Automation, Workflow Automation Tools, Communication Automation Systems

**Alternatives**:
- Note: Specific alternatives not provided in source documentation
**Works well with**:
- Google Workspace
- HubSpot
- People Data Labs
- Voice/Phone Systems

## Integration Patterns

### Common Patterns

- Google Workspace integration for document/sheet management
- HubSpot integration for CRM automation
- Timer-based workflow triggers
- Variable-based state management
### Advanced Patterns

- Voice system integration
- Multi-step workflow orchestration
- Custom trigger implementation
- Data enrichment pipelines

## Best Practices

- Implement proper monitoring using Observability Utilities
- Structure workflows modularly for reusability
- Use Set Variables skill for temporary data storage
- Implement appropriate authentication flows
- Leverage built-in integrations when available
- Monitor agent performance regularly

### Common Pitfalls to Avoid

- Note: Specific pitfalls not provided in source documentation, but likely include:
- Insufficient error handling
- Improper permission management
- Poor workflow structure
- Inadequate monitoring

## References

- [Official Documentation](https://docs.lindy.ai/fundamentals/lindy-101/computer-use)

### Reference Files

See the `references/` directory for:
- Complete API documentation
- Detailed examples
- Configuration guides

Overview

This skill encapsulates expert knowledge for building and managing AI agents on the Lindy platform, focused on business process automation. It highlights integrations, workflow patterns, and practical capabilities for automating communication, CRM tasks, data enrichment, and voice interactions. It is designed to help teams implement reliable, maintainable automation that connects to tools like Google Workspace and HubSpot.

How this skill works

The skill documents common and advanced integration patterns, modular workflow design, and operational guidance for Lindy agents. It inspects use cases such as email and marketing automation, voice/phone call flows, CRM synchronization, and document or spreadsheet automation. It also recommends observability, variable management, and authentication practices to ensure robust execution and monitoring.

When to use it

  • Building AI assistants that automate customer communication across email, voice, and messaging channels.
  • Orchestrating multi-step business workflows that require integrations with HubSpot or Google Workspace.
  • Implementing data enrichment pipelines or CRM automation tied to People Data Labs or similar services.
  • Setting up recurrent or timer-triggered processes for operational tasks and marketing campaigns.
  • Designing modular workflows that need reusable components, state management, and observability.

Best practices

  • Modularize workflows into reusable components to reduce duplication and simplify testing.
  • Use Set Variables for transient state and keep persistent data in external systems or CRM.
  • Implement comprehensive observability: logs, metrics, and alerts for long-running or multi-step flows.
  • Follow least-privilege authentication patterns and rotate credentials used by integrations.
  • Leverage built-in integrations (Google Workspace, HubSpot) to reduce custom connector maintenance.

Example use cases

  • Automated lead qualification: gather form data, enrich with People Data Labs, and push qualified leads into HubSpot.
  • Email campaign orchestration: compose, schedule, and monitor delivery and engagement using workflow timers.
  • Voice-driven support flows: route inbound calls, collect context, and create CRM tickets automatically.
  • Document processing: extract spreadsheet data, perform transformations, and update shared Google Sheets or Docs.
  • Cross-channel follow-ups: coordinate email, SMS, and call attempts based on CRM state and engagement signals.

FAQ

What integrations does this skill cover?

It covers Google Workspace, HubSpot, People Data Labs, voice/phone systems, and common auth and data pipelines used in Lindy deployments.

How should I structure complex workflows?

Break workflows into modular steps with clear inputs/outputs, use variables for transient state, and add observability hooks for each stage to aid debugging and monitoring.