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Implement data quality validation with Great Expectations, dbt tests, and data contracts.
Passed 19 of 22 test cases with the skill, and 16 of 22 without it.
and 1 more in the full report
3 fixed16 passed either way3 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 3 test cases the skill fixed. Same model, same prompt, with and without the skill.
Can you create a Data Contract specification file in YAML format for an e-commerce orders pipeline? The document needs to follow the datacontract.com schema version 1.0 standard, including metadata, server connection context, usage terms, column definitions with PII flags, quality rules, and SLA guarantees.
| Checked | Without skill | With skill |
|---|---|---|
| Declares apiVersion as datacontract.com/v1.0.0 and kind as DataContract. | Missed | Passed |
| Defines quality checks using type SodaCL under the top-level quality section. | Passed | Passed |
The instructions your model reads when the skill loads.
Production patterns for implementing data quality with Great Expectations, dbt tests, and data contracts to ensure reliable data pipelines.
| Dimension | Description | Example Check |
|---|---|---|
| Completeness | No missing values | expect_column_values_to_not_be_null |
| Uniqueness | No duplicates | expect_column_values_to_be_unique |
| Validity | Values in expected range | expect_column_values_to_be_in_set |
| Accuracy | Data matches reality | Cross-reference validation |
| Consistency | No contradictions | expect_column_pair_values_A_to_be_greater_than_B |
| Timeliness | Data is recent | expect_column_max_to_be_between |
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/ \ Integration Tests (cross-table)
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/ \ Unit Tests (single column)
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/ \ Schema Tests (structure)
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test cases passed, vs 16 / 22 without
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