Data · Global library

Data Quality Gatekeeper

Implements Great Expectations data quality framework with comprehensive validation, profiling, and automated quality gates

CodexClaude CodeKimi Codeorchestrator-mcp

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Best use case

Use Data Quality Gatekeeper when you need to implements Great Expectations data quality framework with comprehensive validation, profiling, and automated quality gates, especially when the work is driven by data quality and great expectations.

Trigger signals

data qualitygreat expectationsvalidationexpectationcheckpointdata profilingquality gate

Validation hooks

expectation-validation

Install surface

Copy the exact command path you need.

Inspect

pip install "orchestrator-mcp[dashboard]"
orchestrator-mcp skills show data-quality-gatekeeper

Use

orchestrator-mcp skills export data-quality-gatekeeper --to ./skillforge-packs
# copy the exported pack into your preferred agent environment

Export

cp -R skills/data-quality-gatekeeper ./your-agent-skills/data-quality-gatekeeper
# or open skills/data-quality-gatekeeper/SKILL.md in a markdown-first client

File patterns

expectations/*.jsongreat_expectations.ymlcheckpoint*.yml*.ge.py

Model preferences

claude-sonnet-4gpt-4oclaude-haiku-3

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Data Quality Gatekeeper

Copy the exact command path you need.

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