great-expectations-validator
Data quality validation skill using Great Expectations for schema validation, expectation suites, data documentation, and automated data quality checks in ML pipelines.
npx skills add a5c-ai/babysitter --skill great-expectations-validator --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Great Expectations Validator Validate data quality using Great Expectations for comprehensive data testing, documentation, and quality monitoring. ## Overview This skill provides capabilities for data quality validation using Great Expectations (GX), the leading open-source library for data quality. It enables creation and execution of expectation suites, data documentation generation, and integration with ML pipelines. ## Capabilities ### Expectation Suite Management - Create and configure expectation suites - Define expectations for columns and tables - Validate data against expectations - Store and version expectation suites ### Data Validation - Schema validation (column presence, types) - Statistical validation (distributions, ranges) - Referential integrity checks - Custom SQL-based expectations - Regex pattern matching ### Data Documentation - Generate data documentation (Data Docs) - Create profiling reports - Document validation results - Build data dictionaries ### Pipeline Integration - Checkpoint configuration and execution - Batch request management - Action-based workflows (notifications, storage) - Integration with Airflow, Prefect, Dagster ### Custom Expectations
- Overview
- Capabilities
- Expectation Suite Management
- Data Validation
- Data Documentation
- Pipeline Integration
- Custom Expectations
- Prerequisites
- Installation
- Optional Connectors
- Usage Patterns
- Initialize Great Expectations Project
- Create Expectation Suite from Profiler
- Validate Data with Checkpoint
pip install great_expectations>=0.18.0 Database connectors pip install great_expectations[sqlalchemy] Cloud storage pip install great_expectations[s3] # AWS pip install great_expectations[gcs] # GCP pip install great_expectations[azure] # Azure Spark support pip install great_expectations[spark] Initialize GX project
What does the great-expectations-validator skill do?
Data quality validation skill using Great Expectations for schema validation, expectation suites, data documentation, and automated data quality checks in ML pipelines.
How do I install it?
Run `npx skills add a5c-ai/babysitter --skill great-expectations-validator --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From a5c-ai/babysitter, a repository with 1,642 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.