Automates data validation and impact analysis for dbt projects using the Recce framework.
The Recce dbt Data Validation skill enhances Claude's capability to assist with analytics engineering workflows by integrating Recce's powerful data diffing tools. It automatically detects dbt environments and provides contextual guidance for comparing data changes between branches, analyzing pull request impacts, and performing schema or row count comparisons. By leveraging specialized MCP tools, this skill helps data engineers ensure data quality, visualize lineage changes, and catch breaking modifications before they reach production, directly within the Claude interface.
Key Features
01Statistical profile and row count comparisons between data environments
021 GitHub stars
03Integrated documentation search for Recce features and CI/CD integration
04Automated dbt project detection and context-aware suggestions
05One-click environment setup and interactive validation shortcuts
06Comprehensive PR impact analysis including lineage and schema diffs
Use Cases
01Comparing statistical profiles between development and production environments to ensure consistency
02Debugging data quality issues by performing SQL query diffs across different git branches
03Validating data changes and downstream impact during dbt pull request reviews
