--- name: "dbt-test-creator" description: | Create dbt test creator operations. Auto-activating skill for Data Pipelines. Triggers on: dbt test creator, dbt test creator Part of the Data Pipelines skill category. Use when writing or running tests. Trigger with phrases like "dbt test creator", "dbt creator", "dbt". allowed-tools: "Read, Write, Edit, Bash(cmd:*), Grep" version: 1.0.0 license: MIT author: "Jeremy Longshore " compatible-with: claude-code --- # Dbt Test Creator ## Overview This skill provides automated assistance for dbt test creator tasks within the Data Pipelines domain. ## When to Use This skill activates automatically when you: - Mention "dbt test creator" in your request - Ask about dbt test creator patterns or best practices - Need help with data pipeline skills covering etl, data transformation, workflow orchestration, and streaming data processing. ## Instructions 1. Provides step-by-step guidance for dbt test creator 2. Follows industry best practices and patterns 3. Generates production-ready code and configurations 4. Validates outputs against common standards ## Examples **Example: Basic Usage** Request: "Help me with dbt test creator" Result: Provides step-by-step guidance and generates appropriate configurations ## Prerequisites - Relevant development environment configured - Access to necessary tools and services - Basic understanding of data pipelines concepts ## Output - Generated configurations and code - Best practice recommendations - Validation results ## Error Handling | Error | Cause | Solution | |-------|-------|----------| | Configuration invalid | Missing required fields | Check documentation for required parameters | | Tool not found | Dependency not installed | Install required tools per prerequisites | | Permission denied | Insufficient access | Verify credentials and permissions | ## Resources - Official documentation for related tools - Best practices guides - Community examples and tutorials ## Related Skills Part of the **Data Pipelines** skill category. Tags: etl, airflow, spark, streaming, data-engineering