SQL Translate

Requirements

Agent: builder or migrator (may write translated SQL to files) Tools used: sql_translate, read, write, altimate_core_validate

Translate SQL queries from one database dialect to another using sqlglot's transpilation engine.

Workflow

1. Determine source and target dialects — If the user did not specify both dialects, ask which source and target dialects to use. Common dialects: snowflake, bigquery, postgres, mysql, tsql, hive, spark, databricks, redshift, duckdb.

2. Get the SQL to translate — Either:

   • Read from a file path provided by the user (use read)
   • Accept inline SQL from the user's message
   • Read from clipboard or stdin if mentioned

3. Call sql_translate with:

   • sql: The SQL query text
   • source_dialect: The source dialect
   • target_dialect: The target dialect

4. Review the result:

   • If success is true, present the translated SQL
   • If there are warnings, explain each one and what may need manual adjustment
   • If success is false, explain the error and suggest fixes

5. Format the output showing:

   • Original SQL (labeled with source dialect)
   • Translated SQL (labeled with target dialect)
   • Any warnings about lossy translations or features that need manual review

6. Offer next steps if applicable:

   • Suggest running altimate_core_validate on the translated SQL to verify syntax
   • Offer to write the translated SQL to a file
   • Offer to translate additional queries

Usage

The user invokes this skill with optional dialect and SQL arguments:

• /sql-translate — Interactive: ask for source dialect, target dialect, and SQL
• /sql-translate snowflake postgres — Translate from Snowflake to PostgreSQL (will ask for SQL)
• /sql-translate snowflake postgres SELECT DATEADD(day, 7, CURRENT_TIMESTAMP()) — Full inline translation

Supported Dialects

Use the tools: sql_translate, read, write, altimate_core_validate.