ycql

Design and validate YCQL data models and queries for YugabyteDB.

6|4|Updated Mar 4, 2026
One-click install
npx skills add https://github.com/yugabyte/yugabytedb-skills --skill ycql
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: ycql
Source: https://github.com/yugabyte/yugabytedb-skills/tree/main/skills/ycql
Command: npx skills add https://github.com/yugabyte/yugabytedb-skills --skill ycql

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Designing and validating effective YCQL data models and queries for YugabyteDB's Cassandra-compatible API can be error-prone and time-consuming, leading to schema misfits and inefficient queries.

Core Features & Use Cases

  • Partition keys and clustering design for even data distribution and performant range queries.
  • Global secondary indexes and TTL and LWT support to optimize read/write patterns and data lifecycle.
  • Query optimization and best practices for prepared statements, batching, and transactional semantics on YCQL.

Quick Start

Ask YCQL to review your table definitions and suggest optimal keys, indexes, TTL settings, and batching strategies.

Frequently Asked Questions about ycql

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

FAQPage Schema
How do I design partition keys and clustering for YCQL tables on YugabyteDB?

Designing partition keys and clustering for YCQL tables on YugabyteDB involves structuring keys for even data distribution and performant range queries. Proper clustering ensures ordered sorting within partitions, optimizing read patterns across distributed microservices workloads.

What is the best way to optimize YCQL queries using global secondary indexes and TTL?

Optimizing YCQL queries with global secondary indexes and TTL improves read patterns and manages data lifecycle. Global secondary indexes enable efficient non-key lookups, while TTL automatically expires data, ensuring efficient query patterns and data retention on YugabyteDB.

How do I use batching and prepared statements for YCQL transactional semantics?

Using batching and prepared statements for YCQL transactional semantics groups multiple modifications into atomic operations. Prepared statements parse queries once for repeated execution, while batching ensures transactional integrity and reduces round trips across YugabyteDB's Cassandra-compatible API.

Does YugabyteDB's Cassandra-compatible API support lightweight transactions (LWT) in YCQL?

YugabyteDB's Cassandra-compatible API supports lightweight transactions (LWT) in YCQL for strong consistency. LWT allows conditional updates using compare-and-set operations, ensuring safe concurrent writes and read-after-write consistency across distributed analytics workloads.

How do I validate YCQL data models to prevent schema misfits and inefficient queries?

Validating YCQL data models prevents schema misfits and inefficient queries by reviewing table definitions against access patterns. Analyzing partition key selection, indexing strategies, and TTL settings ensures optimal schema design for YugabyteDB applications.