Does this skill support complex filtering logic?

Absolutely. It supports nested AND/OR logic, string matching (contains, startsWith), numeric comparisons, and specialized date range operators.

What is the naming convention for fields in Drizzle Cube queries?

All fields must follow the 'CubeName.fieldName' format (e.g., 'Sales.totalRevenue') to ensure they are correctly mapped to the semantic layer.

How does the MultiQueryConfig handle multiple data sets?

It provides two strategies: 'concat' which appends results with a query index, and 'merge' which aligns results from different queries by a common dimension.

Can I preview the SQL generated by these queries?

Yes, the skill documentation includes patterns for a 'dry run' using the cubeClient.sql(query) method to inspect the generated SQL before execution.

Can I perform period comparisons like Year-over-Year analysis?

Yes, the skill supports the compareDateRange property within time dimensions, allowing you to compare current data against previous periods easily.

Drizzle Cube Query Builder

Name: Drizzle Cube Query Builder
Author: cliftonc

bycliftonc

分析と監視

Constructs semantic queries for Drizzle Cube applications including measures, dimensions, and complex time-series analysis.

概要

The Drizzle Cube Query Building skill empowers developers to programmatically generate structured CubeQuery objects for querying semantic data layers. It provides a standardized framework for defining aggregations (measures), groupings (dimensions), and time-based filtering with support for advanced features like period comparisons, missing date filling, and complex nested filter logic. By automating the query construction process within Claude Code, it ensures adherence to naming conventions and schema requirements, reducing errors in data retrieval and analytics workflows.

主な機能

Multi-query merging and concatenation strategies
Automated field naming validation for Cube schemas
Advanced time-series analysis with granularity control
Complex nested filtering with AND/OR logic
0 GitHub stars
Specialized Funnel and Flow query pattern generation

ユースケース

Building real-time analytics dashboards with Drizzle Cube
Developing user conversion funnels and behavioral flow analysis
Performing Year-over-Year (YoY) financial performance comparisons

概要

主な機能

Multi-query merging and concatenation strategies
Automated field naming validation for Cube schemas
Advanced time-series analysis with granularity control
Complex nested filtering with AND/OR logic
0 GitHub stars
Specialized Funnel and Flow query pattern generation

ユースケース

Building real-time analytics dashboards with Drizzle Cube
Developing user conversion funnels and behavioral flow analysis
Performing Year-over-Year (YoY) financial performance comparisons