Repeatability
High
The transformation logic is fully deterministic: parse dates, standardize format, deduplicate by order ID keeping the latest, flag rows missing critical fields. This structure is identical every run and scales trivially to any row count.
Ambiguity Tolerance
Medium
Most success criteria are crisp, but the MM/DD vs DD/MM ambiguity for dates like '01/05/2024' is a genuine edge case with no self-evident answer. The agent needs an explicit fallback rule (e.g., prefer MM/DD when ambiguous, or flag for QA) to avoid silent errors.
Data & Tool Availability
High
The agent only needs the CSV file and a Python or pandas environment — both are trivially available. No external APIs, credentials, or live data sources are required.
Error Cost
Low
The original CSV is unchanged; outputs are new files. Errors are easily caught by spot-checking the QA sheet or re-running the script. No irreversible downstream damage is likely from a cleaning mistake.
Human Judgment Required
Low
There are no taste, ethics, or relationship calls here. The only judgment-adjacent decision is the date ambiguity tiebreaker, which can be resolved by a one-line rule from the user before the agent runs.