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name	description	risk	source	date_added
data-quality-frameworks	Implement data quality validation with Great Expectations, dbt tests, and data contracts. Use when building data quality pipelines, implementing validation rules, or establishing data contracts.	unknown	community	2026-02-27

Data Quality Frameworks

Production patterns for implementing data quality with Great Expectations, dbt tests, and data contracts to ensure reliable data pipelines.

Use this skill when

Implementing data quality checks in pipelines
Setting up Great Expectations validation
Building comprehensive dbt test suites
Establishing data contracts between teams
Monitoring data quality metrics
Automating data validation in CI/CD

Do not use this skill when

The data sources are undefined or unavailable
You cannot modify validation rules or schemas
The task is unrelated to data quality or contracts

Instructions

Identify critical datasets and quality dimensions.
Define expectations/tests and contract rules.
Automate validation in CI/CD and schedule checks.
Set alerting, ownership, and remediation steps.
If detailed patterns are required, open resources/implementation-playbook.md.

Safety

Avoid blocking critical pipelines without a fallback plan.
Handle sensitive data securely in validation outputs.

Resources

resources/implementation-playbook.md for detailed frameworks, templates, and examples.

Limitations

Use this skill only when the task clearly matches the scope described above.
Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.