Context Engineering Studio Private Preview

✦TL;DR

Bootstrap, test, and ship the business context every AI agent needs to produce accurate, trustworthy answers.

||

|Connect

A Context Repo is a versioned, domain-scoped unit of context any AI agent can consume. It bundles skills (how the agent should reason), a semantic model (what your metrics mean), and deploy and eval configs into one governed package.

• Generated from your data graph. Context Engineering Studio reads your catalog, BI lineage, and query history to generate metrics, filters, and relationships automatically.
• Evaluated before deployment. Run evals against the repository to surface gaps with specific fix recommendations before it goes live.
• Deploy to any agent or engine. One certified repository serves MCP-compatible agents, Snowflake Cortex, and Databricks Genie, with live query traces for continuous iteration.

Read the concept

context-repo

v3.1.2 · domain repository · MCP-ready

Verified

Contents

semantic-model.yaml

skills

finance-compliance.md

analyst.md

deploy

databricks.json

quality-report.md

skills/finance-compliance.md

Finance Compliance

Role & context

Guides the agent when a question touches regulated or sensitive data — enforcing approved sources, masking, and disclosure rules before any answer is returned.

Guardrails

• Only use certified, governed tables as sources
• Never expose PII or restricted columns in answers
• Cite the source asset for every figure returned

Applies to

Restricted tagsPII, Confidential

Scopefinance domain

2 skills1 semantic model1 deploy targetquality 82%

1

Enable

Enable CES on your tenant, assign access to your team, and connect your query engine.

→

2

Build

Describe your domain, generate a semantic model, refine definitions, and simulate with a question set to see where to improve.

→

3

Deploy

Certify your context repository and deploy it to Snowflake Cortex Analyst or Databricks Genie.