dbt

Plan, build, test, and debug dbt projects across models and semantic layers.

Updated Aug 23, 2026
One-click install
npx skills add https://github.com/piyushmal13/kandhogaya --skill dbt-piyushmal13
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: dbt
Source: https://github.com/piyushmal13/kandhogaya/tree/main/.kilocode/skills/dbt
Command: npx skills add https://github.com/piyushmal13/kandhogaya --skill dbt-piyushmal13

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

dbt Analytics Engineering Skills bundle provides a unified toolkit for planning, building, testing, discovering data, debugging errors, and integrating with the dbt semantic layer and MCP server.

Core Features & Use Cases

  • Comprehensive set of skills including building dbt models, writing tests, semantic layer integration, and MCP configuration.
  • Practical use cases span model development, test-driven validation, data discovery via dbt show, semantic-layer queries, and troubleshooting dbt Cloud jobs.

Quick Start

Start by loading the bundled sub-skills such as using-dbt-for-analytics-engineering to begin planning and implementing dbt projects.

Frequently Asked Questions about dbt

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

FAQPage Schema
How do I build and test dbt models for analytics engineering?

To build and test dbt models, you load the analytics engineering sub-skills to plan model development, write SQL transformations, and apply test-driven validation to ensure data quality and documentation across your dbt project.

Can I query the dbt semantic layer and configure the MCP server?

Yes, you can query the dbt semantic layer and configure the dbt MCP server by following the bundled integration sub-skills, enabling multiple clients to discover data and interact with semantic definitions seamlessly.

What is the best way to troubleshoot and debug dbt Cloud jobs?

The best way to troubleshoot dbt Cloud jobs is to use the debugging sub-skills, which guide you through identifying errors, resolving model failures, and validating test-driven outputs within your dbt project environment.

Do I need any prior tools to start planning a dbt project?

You do not need external dependencies to start planning a dbt project, but you should load the bundled sub-skills like using-dbt-for-analytics-engineering to guide your environment setup and implementation workflow.

How does data discovery work with dbt show?

Data discovery with dbt show allows you to preview model outputs and validate transformations directly, serving as a practical use case within the analytics engineering skills to inspect data before full execution.