Repeatability
High
The structure is consistent: connect to two databases, compare schemas and row counts, sample records, emit a report. This pattern is the same regardless of which tables or types are involved, making it highly automatable.
Ambiguity Tolerance
High
Success criteria are concrete — row counts match, schema definitions align, data type mappings are correct, sample records are equivalent, and mismatches are flagged in HTML. There is little room for subjective interpretation.
Data & Tool Availability
Medium
The agent needs read credentials and network access to both the legacy MySQL and new PostgreSQL instances, which may require human setup. Once access is granted, all needed data is queryable programmatically.
Error Cost
Low
This is a read-only validation script — it writes nothing to either database and produces only a report. The worst realistic outcome is a false negative (missed mismatch), which a human reviewer of the report can catch before cutover.
Human Judgment Required
Low
Most decisions are deterministic: counts match or they don't, types map correctly or they don't. A human should review the final report, but generating it requires no intuition or taste.