Migrate data between formats and systems with confidence. Convert data, validate transformations against schemas, and generate tests that verify data integrity throughout the pipeline. No more "it worked on my machine" migrations.
Validate your source data against expected schemas and quality rules. Catches missing fields, type mismatches, encoding issues, and data anomalies before you start the migration.
Convert data between formats with powerful transformation capabilities. Map fields, apply filters, reshape structures, and handle type coercions -all through natural language instructions.
Review any custom migration scripts for correctness and edge cases. The code-auditor's parallel agents catch common pitfalls like missing null handling, incorrect date parsing, character encoding bugs, and security issues.
Create automated tests that verify data integrity after migration. Tests check record counts, validate key field values, ensure referential integrity, and confirm no data was lost or corrupted.
Always validate your source data before converting. Running /data-validator first catches encoding issues, missing fields, and inconsistencies that would cause silent failures downstream.
Use /json-query to inspect and clean your data before migration. Filtering out invalid records upfront is much easier than debugging them in the target system.
Generate integrity tests that compare source and target record counts, check for data loss, and verify that transformations preserved meaning -not just structure.