What problem does it solve?
Turning Sigma BI workspace content into reusable warehouse knowledge is manual and error-prone. This Skill converts staged Sigma data model specs and workbook summaries into durable ktx wiki candidates, so agents can query the warehouse using accurate business definitions.
Core Features & Use Cases
- Data model extraction: Reads staged
data-models/<id>.json specs and captures metric definitions, domain conventions, and business semantics from element names and column descriptions, skipping hidden elements.
- Workbook knowledge capture: Derives business domain knowledge from workbook names, descriptions, and folder paths, writing one candidate per distinct concept.
- Identifier verification: Verifies warehouse identifiers via
entity_details and sql_execution probes using connection mappings before writing anything, marking unverifiable references as unverified.
- Use Case: After a Sigma ingest run stages 60 data models and hundreds of workbooks, run this Skill on the
sigma-data-models and sigma-workbooks WorkUnits to produce wiki candidates for concepts like Net ARR and churn cohorts without touching the already-projected semantic-layer sources.
Quick Start
Load the sigma_ingest skill for the sigma-data-models WorkUnit and write wiki candidates for the business concepts found in the staged Sigma files.