data-context-extractor

To extract tribal knowledge for SQL warehouse documentation, this Skill systematically discovers schemas and asks targeted questions about entities, metrics, and data hygiene. It then generates structured reference files capturing essential company-specific context.

Yes, you can generate custom data analysis skills from scratch for new analysts. The bootstrap mode discovers your schema, asks key questions about metrics and terminology, and creates a tailored skill to accelerate onboarding productivity.

The best way to document data warehouse context for AI analysis is to systematically capture schema details, metrics, and common pitfalls into structured reference files. This ensures AI tools understand domain-specific terminology and data hygiene rules.

You add new domain context to an existing data analysis skill using iteration mode. This feature enhances your current skills by asking targeted questions and appending new entities, metrics, and terminology to the structured reference files.

Yes, this skill generation tool supports discovering schemas automatically. During the bootstrap process, it systematically inspects your data warehouse to identify tables and structures before prompting analysts for contextual details.

You should not use automated knowledge extraction when your data warehouse schema is incomplete or your analysts lack defined metrics and data hygiene rules. The tool relies on existing tribal knowledge to generate accurate structured reference files.