ck:databases

Name: ck:databases
Availability: InStock
Author: weihung

Design schemas and write queries for MongoDB and PostgreSQL.

Updated Aug 27, 2026

Search Tags:#query optimization #schema design #database #postgresql #sql #mongodb

Ready to run

npx skills add https://github.com/weihung0831/claudekit --skill ck-databases-weihung0831

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: ck:databases
Source: https://github.com/weihung0831/claudekit/tree/main/.opencode/skills/databases
Command: npx skills add https://github.com/weihung0831/claudekit --skill ck-databases-weihung0831

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill streamlines database interactions, from designing efficient schemas to writing complex queries for both relational and NoSQL databases.

Core Features & Use Cases

Schema Design: Create optimal table structures for OLTP and OLAP workloads.
Query Writing: Generate SQL, MongoDB queries, and aggregation pipelines.
Performance Tuning: Optimize indexes and analyze slow queries.
Use Case: Design a PostgreSQL schema for an e-commerce order system, including indexes for fast lookups, and then write a query to find the top 10 customers by total spending.

Quick Start

Use the ck:databases skill to design a PostgreSQL schema for a blog with posts and users.

Frequently Asked Questions about ck:databases

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

FAQPage Schema

How do I design a PostgreSQL schema optimized for both OLTP and OLAP workloads?▼

PostgreSQL schema design for mixed workloads involves structuring normalized tables for OLTP transactional integrity while applying denormalization and indexing strategies to accelerate OLAP analytical queries and reporting.

What's the best way to write a MongoDB aggregation pipeline for complex data filtering?▼

Writing a MongoDB aggregation pipeline involves chaining stages like match, group, and project to filter and transform documents, enabling complex multi-stage data processing and reporting directly within the database.

Why does my SQL query run slowly and how can I optimize index performance?▼

Slow SQL query performance often stems from missing or inefficient indexes. Query optimization requires analyzing execution plans and applying targeted indexing strategies to reduce table scans and accelerate data retrieval.

Can I use Python scripts to automate database migration and backup tasks?▼

Python scripts can automate database migration and backup tasks by executing structured commands to transfer schemas and data, ensuring consistent state management across different database environments during deployment.

Does this approach work for managing both relational SQL and NoSQL database structures?▼

Yes, this approach supports both relational SQL and NoSQL database structures by providing specific design patterns for PostgreSQL schemas and MongoDB document models, alongside tailored query syntax and indexing strategies for each.