Build a synthetic database seed generator that reads a supplied database schema and produces realistic, internally consistent test datasets for development and QA. Understand relationships, constraints, enums, date dependencies, financial totals, and business rules. Generate ordinary cases, boundary cases, rare scenarios, and intentionally invalid records for validation testing. Allow developers to specify dataset size and scenario types, preserve referential integrity where required, and export repeatable seed scripts. Use fictional data only, never copy production personal information, and explain which business assumptions were inferred rather than explicitly defined.
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