ck:databases

Design and optimize MongoDB and PostgreSQL schemas, queries, and indexes.

Updated May 10, 2026

Search Tags:#query optimization #postgresql #migrations #backup #sql #mongodb #databases

Ready to run

npx skills add https://github.com/dthuy62/kollet-app --skill ck-databases-dthuy62

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: ck:databases
Source: https://github.com/dthuy62/kollet-app/tree/main/.opencode/skills/databases
Command: npx skills add https://github.com/dthuy62/kollet-app --skill ck-databases-dthuy62

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pymongo, psycopg2, pytest, pytest-cov, pytest-mock, mongomock, and includes scripts (resource) and references (resource) components.

What problem does it solve?

It helps you design, query, migrate, back up, and troubleshoot MongoDB and PostgreSQL systems without juggling separate playbooks.

Core Features & Use Cases

Schema Design: Plan transactional, analytics, and ETL-friendly database structures with clear naming, constraints, and indexes.
Querying & Optimization: Write and refine PostgreSQL SQL, MongoDB CRUD queries, aggregation pipelines, and performance-focused indexes.
Operations & Maintenance: Generate migrations, create and restore backups, and analyze slow queries and index usage with the provided scripts.
Use Cases: Build a new app schema, review an existing database for performance issues, or automate backup and migration workflows.

Quick Start

Ask the skill to design a PostgreSQL or MongoDB schema, write the needed query or migration, and recommend the safest index and backup strategy.

Frequently Asked Questions about ck:databases

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

FAQPage Schema

How do I optimize slow PostgreSQL queries and analyze index usage?▼

To optimize slow PostgreSQL queries, you can analyze slow queries and index usage using the included Python utilities and references. The skill helps refine SQL, apply performance-focused indexes, and generate deterministic maintenance scripts.

What is the best way to design a MongoDB schema for application and analytics workloads?▼

Designing a MongoDB schema for analytics requires index-aware data modeling. The skill helps you plan transactional and ETL-friendly structures with clear naming, constraints, and optimized aggregation pipelines.

Can I automate database migrations and backup verification for PostgreSQL?▼

Yes, you can automate database migrations and backup verification for PostgreSQL. The skill provides scripts to generate migrations, create and restore backups, and verify them deterministically.

Do I need pymongo and psycopg2 to run the included database scripts?▼

Yes, you need pymongo and psycopg2 installed. These dependencies allow the Python utilities to execute MongoDB CRUD operations, aggregation pipelines, and PostgreSQL SQL queries within your environment.

How does index-aware data modeling improve MongoDB aggregation pipelines?▼

Index-aware data modeling improves MongoDB aggregation pipelines by ensuring queries use performance-focused indexes. This approach reduces scan times and optimizes CRUD operations for application workloads.