DataHub
Official@datahub-project · United States of America
AI & Data Context Management: DataHub’s metadata platform gives context for AI to safely use and manage data.
Agent Skills by DataHub
Showing 3 vetted skills indexed across 1 GitHub repositories.
datahub-projectdatahub-connector-pr-review
Review DataHub connector code against 22 golden standards.
datahub-projectload-standards
Load 22 DataHub connector golden standards from markdown files into context.
datahub-projectdatahub-connector-planning
Plan DataHub connectors by classifying sources and generating a _PLANNING.md blueprint.
Frequently Asked Questions About DataHub
FAQPage SchemaWhat specific tasks can engineers perform using DataHub's connector skills?▼
Engineers can validate connector code against 22 golden standards, load technical documentation into metadata context, and generate structured blueprints for new data source integrations. These capabilities ensure consistent quality and architectural alignment across all data ingestion points within the enterprise ecosystem.
Which technical personas benefit most from these connector management capabilities?▼
Data engineers, metadata architects, and platform reliability engineers benefit most from these capabilities. These personas utilize the platform to enforce rigorous development standards, maintain documentation parity, and streamline the planning phase of complex data integration projects.
What are the primary prerequisites for implementing these connector planning and review skills?▼
Implementation requires existing DataHub infrastructure and a repository of connector specifications formatted as markdown files. Users must have their connector source code accessible for the review process and maintain the 22 golden standards within their environment to enable automated validation.