Agent classes / Data and ETL agent / SQL warehouse as agent context
SQL warehouse as agent context for a data and etl agent
Updated 2026-10-27 (newest stored date on this page) · score asOf 2026-10-19
The class: Moves or reshapes records between files, tables, and documents, and reports rows that did not match the schema.
- A schema for the destination
- A row-level error report
Depot Pick: MotherDuck
When not to use it: Snowflake is already the system of record — Cortex; Databricks lakehouse standard — Mosaic; local/embedded only — DuckDB OSS.
Runner-up: Snowflake Cortex.
No single-unit sourced price comparison for this job (no_comparable_unit_for_job).
Failure modes this class and job share (6)
- Schema drift: Validate every tool call and every loaded table against the current schema. Quarantine mismatches instead of coercing them.
- Collateral side effects: Snapshot the workspace or app state, then diff it against an allowlist. A passing check plus an unexpected diff is a failure.
- Hallucinated tool arguments: Reject a call that fails the current schema or names an unknown id, and do that before the tool runs a side effect.
- Partial tool success: Require a per-item status and a failure count. Success for the task requires the failed count to be zero or explicitly handed to a retry queue.
- Silent truncation: Tools must return whether the payload was truncated and how long the original was. Fail the task if the answer depends on the missing span.
- Stale retrieval: Store the source URL and the time it was fetched. If a newer canonical page exists, or two stored sources disagree, do not answer from the older one.
Free options this class uses (0)
No free row lists this job with a kind this class needs.