multiAI Summary Pending
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.
231 stars
Installation
Claude Code / Cursor / Codex
$curl -o ~/.claude/skills/data-quality-frameworks/SKILL.md --create-dirs "https://raw.githubusercontent.com/aiskillstore/marketplace/main/skills/sickn33/data-quality-frameworks/SKILL.md"
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/data-quality-frameworks/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How data-quality-frameworks Compares
| Feature / Agent | data-quality-frameworks | Standard Approach |
|---|---|---|
| Platform Support | multi | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
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.
Which AI agents support this skill?
This skill is compatible with multi.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# 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.