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crm-database-management

Manages PostgreSQL CRM database operations including Alembic migrations, identity resolution, ticket lifecycle, and pgvector search.

11|2|Updated Apr 30, 2026
Search Tags:#database management#crm#identity resolution#alembic#pgvector#ticket lifecycle
One-click install
npx skills add https://github.com/NaveedTechLab/skills-library --skill crm-database-management
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: crm-database-management
Source: https://github.com/NaveedTechLab/skills-library/tree/main/skills/crm-database-management
Command: npx skills add https://github.com/NaveedTechLab/skills-library --skill crm-database-management

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires psycopg2-binary, SQLAlchemy, redis, cryptography, PyJWT, numpy, alembic, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill automates common CRM database management tasks using Python scripts and Alembic migrations, helping users save time and maintain a secure and optimized CRM system.

Core Features & Use Cases

  • Schema Management & Migrations: Automates the process of setting up, managing, and upgrading a PostgreSQL schema with Alembic migrations.
  • Customer Identity Resolution: Streamlines customer data handling, resolving customer identities across different channels and detecting duplicates.
  • Ticket Lifecycle Management: Manages support tickets' entire lifecycle, including categorization, tracking, and closure.
  • Vector Search: Implement semantic search using the pgvector extension, allowing users to find and search content more efficiently.
  • Use Case: Imagine you're setting up a new CRM for a support team. Use this Skill to quickly set up the database schema, manage customer identities, and implement vector search for efficient knowledge base querying.

Quick Start

Use the crm-database-management skill to manage your CRM database operations. To begin, follow these steps:

  1. Set up PostgreSQL with pgvector extension.
  2. Initialize the CRM database schema using the provided DDL.
  3. Run the CRM database manager script: python scripts/crm_database_manager.py

Frequently Asked Questions about crm-database-management

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate PostgreSQL schema migrations for a CRM database?▼

To automate PostgreSQL schema migrations for a CRM, you use Alembic to manage and upgrade database schema versions. This streamlines the setup process and ensures your CRM database structure remains consistent and optimized.

What is customer identity resolution and how does it work in a CRM?▼

Customer identity resolution in a CRM streamlines data handling by resolving customer identities across different channels and detecting duplicates. This process ensures a unified customer view within your PostgreSQL database.

Do I need the pgvector extension to implement vector search in PostgreSQL?▼

Yes, implementing vector search in PostgreSQL requires the pgvector extension. It enables semantic search capabilities, allowing users to find and query content efficiently within the CRM database.

Can I manage support ticket lifecycle operations using SQLAlchemy and Python?▼

Yes, you can manage support ticket lifecycle operations using SQLAlchemy and Python. This includes handling ticket categorization, tracking, and closure directly within your PostgreSQL CRM database.

What are the prerequisites for setting up a CRM database with Redis and PostgreSQL?▼

Setting up a CRM database requires PostgreSQL 12+ with the pgvector extension, Python 3.8+, and a Redis server. You also need to initialize the CRM database schema using the provided DDL.

Does Alembic work with SQLAlchemy for CRM database migrations?▼

Yes, Alembic works with SQLAlchemy for CRM database migrations. Alembic handles the schema version control and upgrade process, while SQLAlchemy provides the ORM layer for database operations.

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