sigma_ingest

Extracts durable wiki knowledge from staged Sigma data model specs and workbook summaries.

1.6k|101|Updated May 10, 2026
One-click install
npx skills add https://github.com/Kaelio/ktx --skill sigma-ingest
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: sigma_ingest
Source: https://github.com/Kaelio/ktx/tree/main/packages/cli/src/skills/sigma_ingest
Command: npx skills add https://github.com/Kaelio/ktx --skill sigma-ingest

SYSTEM DOCUMENTATION & REQUIREMENTS

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.

Frequently Asked Questions about sigma_ingest

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I ingest Sigma data models into ktx wiki knowledge?

Load this Skill for WorkUnits with unitKey sigma-data-models or sigma-workbooks. It reads each staged JSON file, extracts business semantics from element names and column descriptions, and writes wiki candidates with context_candidate_write.

Does Sigma ingest write semantic-layer sources?

No. The deterministic project() step writes all semantic-layer YAML for warehouse-table elements before this Skill runs. The Skill only reads existing SL sources via sl_read_source and references them in sl_refs.

How are warehouse identifiers verified before writing wiki pages?

The Skill maps the element's Sigma connectionId through connectionMappings in sigma-projection-config.json, then calls entity_details to confirm the identifier resolves. Unresolvable identifiers are probed with sql_execution or wrapped as unverified with the raw source path.

What happens when Sigma workbooks were fetched with an updatedSince filter?

The staged set is treated as a recent-changes slice, not the full workspace. The Skill does not infer that absent workbooks were deleted and keeps the workbookFilter settings in scope while processing.

Which Sigma elements are skipped during ingestion?

Hidden elements and hidden columns are skipped, along with visualization settings, owner names, version numbers, and workbooks with no durable business semantics such as Untitled Workbook. Derived table elements without a warehouse path are wiki-only.