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.

1.46x

Quality

66%

Does it follow best practices?

Impact

97%

1.46x

Average score across 6 eval scenarios

Securityby

Passed

No known issues

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npx tessl skill review --optimize ./plugins/data-engineering/skills/data-quality-frameworks/SKILL.md

Evaluation results

82%

30%

Inventory Data Quality Setup

GX expectation suite and checkpoint config

Criteria

Without context

With context

GX library import

100%

ExpectationSuite class

37%

100%

Primary key dual check

100%

Schema check with exact_match False

100%

Categorical set expectation

100%

Strict minimum for price

100%

Dateutil parseable check

100%

Dynamic freshness check

Row count sanity

71%

Statistical distribution check

Checkpoint run_name_template

100%

Checkpoint standard actions

62%

100%

Fail on validation error

66%

100%

25%

Sales Analytics dbt Test Coverage

dbt test suite with custom and generic tests

Criteria

Without context

With context

dbt_utils.recency test

100%

dbt_utils.at_least_one test

100%

dbt_utils.expression_is_true for business rule

100%

FK relationships test

100%

Email regex validation

30%

100%

Generic test macro syntax

100%

Generic test returns 0 rows on pass

100%

Singular test location

100%

Singular test zero-row pass

100%

Primary key coverage

100%

accepted_values for status

100%

74%

Formalizing the Payments Data Asset

Data contract YAML and quality pipeline orchestration

Criteria

Without context

With context

Contract apiVersion

100%

Contract kind field

100%

Metadata owner field

100%

Metadata contact field

100%

Terms section

100%

SodaCL quality type

100%

Quality freshness check

100%

SLA section completeness

50%

100%

DataQualityPipeline class

100%

QualityResult dataclass

100%

Fail-fast ValueError

100%

Report before raise

50%

100%

Integrate Data Quality Alerting into Nightly ETL

GX checkpoint alerting and latest-batch config

Criteria

Without context

With context

Latest batch index

100%

run_name_template format

100%

StoreValidationResultAction present

100%

StoreEvaluationParametersAction present

100%

UpdateDataDocsAction present

100%

SlackNotificationAction class

100%

Slack notify_on failure

100%

Slack webhook env var

100%

SlackRenderer configured

100%

GX context creation

100%

Checkpoint run call

100%

ValueError on failure

100%

Build Custom Validation Tests for Sensor Time-Series Data

Custom dbt generic tests for sequential and bounded data

Criteria

Without context

With context

Generic test macro syntax

100%

row_count_in_range returns violating rows

100%

row_count_in_range accepts parameters

100%

sequential_values uses lag()

100%

sequential_values default interval

100%

sequential_values filters nulls

100%

Singular test in tests/singular/

100%

Singular test zero-row pass

100%

Generic tests referenced in YAML

100%

FK relationships test in YAML

100%

Primary key dual tests

100%

43%

Formalize a Data Contract for Customer Profile Dataset

PII-annotated data contract with versioned schema

Criteria

Without context

With context

apiVersion field

100%

kind field

100%

metadata owner

71%

100%

metadata contact

71%

100%

terms usage and limitations

100%

PII true annotation

100%

piiClassification field

100%

Non-PII field pii false

100%

SodaCL quality type

100%

Quality freshness check

100%

SLA availability

57%

100%

SLA freshness and latency

62%

100%

Schema version in metadata

83%

100%

Repository: wshobson/agents
Commit: 70444e5

Evaluated: 29 days ago
Agent: Claude Code
Model: Claude Sonnet 4.6

Table of Contents

Inventory Data Quality Setup Sales Analytics dbt Test Coverage Formalizing the Payments Data Asset Integrate Data Quality Alerting into Nightly ETL Build Custom Validation Tests for Sensor Time-Series Data Formalize a Data Contract for Customer Profile Dataset

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