What is great-expectations?
Data validation using Great Expectations. Expectation suites, checkpoints, and data docs for pipeline monitoring. Source: majesticlabs-dev/majestic-marketplace.
Data validation using Great Expectations. Expectation suites, checkpoints, and data docs for pipeline monitoring.
Quickly install great-expectations AI skill to your development environment via command line
Source: majesticlabs-dev/majestic-marketplace.
Goal: Provide GX patterns for expectation-based validation and monitoring.
| Table | ExpectTableRowCountToBeBetween | Row count range | | Existence | ExpectColumnToExist | Column must exist | | Nulls | ExpectColumnValuesToNotBeNull | No null values | | Range | ExpectColumnValuesToBeBetween | Value bounds | | Set | ExpectColumnValuesToBeInSet | Allowed values | | Pattern | ExpectColumnValuesToMatchRegex | Regex match |
| Pipeline monitoring | ✓ | - | | Data warehouse validation | ✓ | - | | Automated data docs | ✓ | - | | Simple DataFrame checks | - | Pandera | | Record-level API validation | - | Pydantic |
Data validation using Great Expectations. Expectation suites, checkpoints, and data docs for pipeline monitoring. Source: majesticlabs-dev/majestic-marketplace.
Stable fields and commands for AI/search citations.
npx skills add https://github.com/majesticlabs-dev/majestic-marketplace --skill great-expectationsBrowse more skills from majesticlabs-dev/majestic-marketplace
Data validation using Great Expectations. Expectation suites, checkpoints, and data docs for pipeline monitoring. Source: majesticlabs-dev/majestic-marketplace.
Open your terminal or command line tool (Terminal, iTerm, Windows Terminal, etc.) Copy and run this command: npx skills add https://github.com/majesticlabs-dev/majestic-marketplace --skill great-expectations Once installed, the skill will be automatically configured in your AI coding environment and ready to use in Claude Code, Cursor, or OpenClaw
https://github.com/majesticlabs-dev/majestic-marketplace