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1.1 · Connect the ontology repo to Ana

This is the key step. In TextQL, add a Git connector and point it at your fork of the starter repo (TextQLLabs/ontology-starter-kits/tree/main/healthcare — no fork yet? Ask your TextQL contact; it takes minutes). Because the ontology is git-backed, Ana now has the entire model — every metric definition, every note, every coding rule — as a reference she reads on demand.
No second source of truth —You don’t copy anything into Ana. She reads the repo live; when the repo changes, Ana sees the change.
Git connector pointed at the starter repo

The ontology repo connected — Ana reads it as ground truth.

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1.2 · Connect your data warehouse

Add the connector for the warehouse holding your claims/clinical data (Redshift, BigQuery, Snowflake, …). Read-only access is enough.
BAA first —A BAA must be in place before any PHI flows. Use your enterprise, BAA-covered warehouse — see ontology/notes/governance-phi.md.

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1.3 · (Optional) Bring in your documents

Your real-world context — SOPs, metric definitions, plan documents, policies — often lives in messy files. Upload them in chat, connect Google Drive, or connect SharePoint/OneDrive. Ana reads them alongside the ontology and can fold what she learns into the model.

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1.4 · Say hello

Prompt
You’ll see: Ana describe the model from the repo itself — proof the Git connector works and the ontology is being read as ground truth.

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✅ Checkpoint

  • Ana described the starter’s entities and metrics from the connected repo
  • Your warehouse connector is attached, read-only, and BAA-covered
  • You know which of your documents you’ll bring in (or that you’re skipping this)