CSV Cleanup with Exact IDs and Review Reports

I prepared a small CSV-only command-line sample that handles quoted commas, escaped quotes and multiline fields, preserves exact string IDs and leading zeros, and normalizes only agreed fields. It saves the original bytes, separates identical duplicates, sends conflicting or invalid records to review, and reports counts and changes.

The synthetic eight-record example produces four cleaned records, one identical duplicate and three records for review. Those three include one ID conflict and two invalid records. The sample includes six core regression tests and documented limits. All data is synthetic. This is original self-initiated work developed with AI assistance, not paid client work or a claim about client outcomes.

Deliverables: Python CLI, synthetic CSV, generated cleaned CSV, original byte backup, review/duplicate reports, tests and README.

Six core tests and six independent audit checks passed.