Antigravity-skills 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.
install
source · Clone the upstream repo
git clone https://github.com/rmyndharis/antigravity-skills
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/rmyndharis/antigravity-skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/data-quality-frameworks" ~/.claude/skills/rmyndharis-antigravity-skills-data-quality-frameworks && rm -rf "$T"
manifest:
skills/data-quality-frameworks/SKILL.mdsource content
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
for detailed frameworks, templates, and examples.resources/implementation-playbook.md