What problem does it solve? Writing Snowflake queries that run correctly on Windmill requires knowing the platform's parameter binding syntax, S3 integration patterns, and the right CLI commands to preview or deploy scripts without accidentally overwriting deployed versions. ## Core Features & Use Cases - Parameterized Snowflake Queries: Declare named parameters with -- ? name (type) comments and ? placeholders, including default values. - S3 Integration: Receive S3Object parameters parsed via PARSE_JSON and LATERAL FLATTEN, or stream large result sets directly to S3 with the -- s3 directive to bypass the 10000-row return cap. - Safe CLI Workflow: Distinguishes wmill script preview for local iteration from wmill script run and wmill sync push for deployed versions, preventing accidental deploys of untested changes. - Use Case: Write a Snowflake script that accepts an uploaded CSV file from S3, flattens it into rows, and exports a large aggregated result set back to S3 as Parquet. ## Quick Start Write a Snowflake script that queries the users table with a name filter parameter and preview it locally with sample arguments.