LookML & Cortex

The semantic layer is a file, so moving in and out of it is a file conversion, not a migration project. Every import and export writes to stdout unless you pass --out, so you can review the conversion before committing it.

Import LookML

sqldash import lookml views/ --out .sqldash/metrics.yaml

Converts LookML views and measures into a metrics.yaml. Takes a single .lkml file or a directory, and needs the lookml install extra.

Import a Snowflake semantic view

sqldash import cortex semantic_view.yaml --out .sqldash/metrics.yaml

Converts a Snowflake semantic view into a metrics.yaml. Connection details it cannot know come out as placeholders, each with a warning, so fill them in or run sqldash setup.

Snowflake stores an unquoted name uppercased, so a view read back with SYSTEM$READ_YAML_FROM_SEMANTIC_VIEW says REVENUE. The import folds those names back to lowercase, which Snowflake treats as the same identifier, and keeps mixed-case names as written, since only a quoted identifier can produce one.

Export to LookML

sqldash export lookml --out views/sqldash.lkml

Exports the semantic layer as LookML views, so metrics defined in sqldash can be used from Looker.

Export a Snowflake semantic view

sqldash export cortex --out semantic_view.yaml

Emits a semantic-view YAML for SYSTEM$CREATE_SEMANTIC_VIEW_FROM_YAML, so the metrics your dashboards and agents use and the ones Cortex Analyst answers from are the same definitions, maintained once, in git. --name sets the view name, which defaults to the project directory’s name, and --description writes a description into it. A timezone: session time dimension exports as CAST(<expr> AS TIMESTAMP_LTZ), and import cortex reads that cast back.

What does not round-trip

Derived metrics and aggregates LookML has no measure type for still export, with a warning naming what was lost. Cumulative and window metrics warn too, because Looker computes the per-bucket sum itself, but they do round-trip, since the exported measure carries their meaning in tags: and import lookml reads it back. A metric’s title and format become LookML’s label: and value_format_name:, and descriptions and synonyms carry across both ways. owners, and formats Looker has no name for such as compact, are dropped with a warning. Merging per-metric filters onto shared tables can change meaning, and that is warned too. Read the warnings before committing the output.

Export a Cortex Agent

This needs an agent in agents.yaml whose metrics all come from one Snowflake account, in a single project. From a workspace, pass the project path after the agent name.

sqldash export cortex-agent finance_analyst --out finance.sql
sqldash export cortex-agent finance_analyst --schema ANALYTICS.AGENTS --model auto
sqldash export cortex-agent finance_analyst --spec-only --out agent.yaml --view-out view.yaml

The SQL creates a semantic view scoped to the agent’s allowed metrics and dimensions, named <agent>_metrics, then the agent itself with CREATE OR REPLACE AGENT. Instructions, response guidance, and sample questions carry over, and verified examples become verified queries in the view.

--schema DATABASE.SCHEMA defaults to the common schema of the agent’s Snowflake metrics, and destination names must be unquoted identifiers. --model defaults to auto. --spec-only writes the agent YAML instead of SQL, and then you create the exported view in that schema yourself before using the spec.

sqldash only generates the script. Review it and its warnings before running it in Snowflake, where it replaces the named objects. Data tools, external MCP servers, and evals are not exported as hosted capabilities and are omitted with warnings. Warehouse grants remain the access boundary.