ck:databases

Automate MongoDB and PostgreSQL schema design, migrations, and performance analysis.

Updated Aug 23, 2026
One-click install
npx skills add https://github.com/tarang-tj/syllabus-ai --skill ck-databases-tarang-tj
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: ck:databases
Source: https://github.com/tarang-tj/syllabus-ai/tree/main/.claude/skills/databases
Command: npx skills add https://github.com/tarang-tj/syllabus-ai --skill ck-databases-tarang-tj

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pymongo, psycopg2, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This skill provides a unified toolkit to design, migrate, and optimize databases across MongoDB and PostgreSQL, helping developers and DBAs avoid fragile hand-coding and inconsistencies.

Core Features & Use Cases

  • Schema design guidance for OLTP/OLAP, migrations orchestration, and performance optimization using a curated set of references and scripts.
  • Indexing, performance analysis, backups, and automated migrations with CLI-like tooling.
  • Use case: A team migrating from one database engine to another, designing a new MongoDB collection with proper indexes, and running incremental migrations and performance checks.

Quick Start

Describe a plan to design a MongoDB/PostgreSQL schema, apply incremental migrations, and run performance checks using the provided scripts.

Frequently Asked Questions about ck:databases

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

FAQPage Schema
How do I automate database migrations across MongoDB and PostgreSQL?▼

This toolkit automates database migrations across MongoDB and PostgreSQL by applying incremental migration scripts. It orchestrates schema changes and ensures consistent database schema evolution across both engines without fragile hand-coding.

What is the best way to design schemas and indexing strategies for MongoDB and PostgreSQL?▼

The best way to design schemas and indexing strategies is using curated references that guide OLTP/OLAP schema design. This approach ensures proper indexing strategy for MongoDB collections and PostgreSQL tables for development and production contexts.

Do I need PyMongo and psycopg2 to run PostgreSQL and MongoDB performance analysis?▼

Yes, you need PyMongo and psycopg2 installed for full functionality to run database performance analysis and backups. Optional support for additional features is available based on installed database clients.

Can I use a single toolkit for both MongoDB backups and PostgreSQL performance optimization?▼

Yes, you can use this single toolkit for both MongoDB backups and PostgreSQL performance optimization. It provides CLI-like tooling to execute performance checks and manage backups across both database engines.

When should I use an automated database migration workflow instead of manual schema changes?▼

You should use an automated database migration workflow when migrating between database engines or applying incremental schema updates in production. It prevents inconsistencies and fragile hand-coding that occur during manual schema changes.