Give agents governed semantic data context with Wren Engine
Give agents governed semantic data context so data questions map to trusted metrics and schemas.
npx skills add agentskillexchange/skills --skill give-agents-governed-semantic-data-context-with-wren-engine
Use this skill when an operator needs agents to answer data questions against governed metrics, schemas, and SQL-ready semantic context instead of guessing table joins or business definitions. The workflow is to connect approved data sources, define semantic models, expose the context layer, and have the agent retrieve or query through that governed layer with outputs checked against source definitions. Invoke it instead of giving an agent raw database credentials or asking it to infer business logic from schema names. Do not treat it as a generic BI dashboard or database listing. The scope boundary is semantic context and query planning for agent-facing data workflows using the upstream Wren Engine project.
What this skill actually does
Inputs and prerequisites: Docker or local runtime supported by Wren Engine, configured data source credentials, modeled semantic definitions and query access controls.
Setup notes: Follow Wren Engine documentation to deploy the service, connect approved data sources, model semantic context, and expose the documented context/query surface to agent workflows.
Source and verification boundary: use https://docs.getwren.ai as the canonical reference before running the workflow; keep commands, API calls, CLI usage, and generated outputs reviewable against that upstream source.
Framework fit: publish this as a MCP workflow only when the operator can invoke the documented toolchain directly, rather than treating the upstream project as a generic product listing.