data-quality
Provides concrete examples for implementing data quality tests using dbt and Great Expectations. Covers completeness, uniqueness, validity, consistency, and timeliness checks with specific code snippets for schema tests, custom SQL tests, and relationship validations.
Packaged view
This page reorganizes the original catalog entry around fit, installability, and workflow context first. The original raw source lives below.
Install command
npx @skill-hub/cli install timequity-plugins-data-quality
Repository
Skill path: craft-coder/data/data-quality
Provides concrete examples for implementing data quality tests using dbt and Great Expectations. Covers completeness, uniqueness, validity, consistency, and timeliness checks with specific code snippets for schema tests, custom SQL tests, and relationship validations.
Open repositoryBest for
Primary workflow: Analyze Data & AI.
Technical facets: Data / AI, Testing.
Target audience: Data teams looking for install-ready agent workflows..
License: Unknown.
Original source
Catalog source: SkillHub Club.
Repository owner: timequity.
This is still a mirrored public skill entry. Review the repository before installing into production workflows.
What it helps with
- Install data-quality into Claude Code, Codex CLI, Gemini CLI, or OpenCode workflows
- Review https://github.com/timequity/plugins before adding data-quality to shared team environments
- Use data-quality for data workflows
Works across
Favorites: 0.
Sub-skills: 0.
Aggregator: No.