Data Quality Frameworks

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.

AGI Framework Integration

Adapted for @techwavedev/agi-agent-kit Original source: antigravity-awesome-skills

Memory-First Protocol

Retrieve prior test strategies, known flaky tests, and coverage gaps. Cache test infrastructure setup to avoid re-configuring test environments.

# Check for prior testing/QA context before starting
python3 execution/memory_manager.py auto --query "test patterns and coverage strategies for Data Quality Frameworks"

Storing Results

After completing work, store testing/QA decisions for future sessions:

python3 execution/memory_manager.py store \
  --content "Testing strategy: integration tests hit real DB (no mocks), 85% line coverage, mutation testing on critical paths" \
  --type technical --project <project> \
  --tags data-quality-frameworks testing

Multi-Agent Collaboration

Share test results and coverage reports with code review agents so they can verify adequate coverage on changed code.

python3 execution/cross_agent_context.py store \
  --agent "<your-agent>" \
  --action "QA complete — test suite expanded with 12 new integration tests, all passing" \
  --project <project>

TDD Enforcement

This skill integrates with the framework's iron-law RED-GREEN-REFACTOR cycle. No production code without a failing test first.

Agent Team: QA

Dispatch qa_team to generate tests and verify they pass before marking implementation complete.