data-context-extractor

To extract tribal knowledge and build a data context, use a bootstrapping skill that captures company-specific schemas and domain references to produce a complete SKILL.md and reference files.

The best way to bootstrap a data analytics skill for a warehouse is to extract company-specific metrics and entity definitions into structured templates, generating a ready-to-package skill with validated frontmatter.

Yes, you can expand an existing data context skill using iteration mode to add domain-specific references and extend metrics without rebuilding the core schema from scratch.

Frontmatter validation ensures that the generated SKILL.md and reference files meet structural requirements, verifying that entity, metric, and table definitions are correctly formatted for packaging.

Yes, reference file templates are required to guide the extraction of domain knowledge and accelerate the discovery of entities, metrics, and table definitions for the new data context.

Use bootstrap mode to create a brand-new data context skill from scratch for a warehouse, and use iteration mode to expand an existing skill with additional domain references and metrics.