Standardize Messy Dates, Numbers, and Categories

ROLE Act as a data preparation engineer. OBJECTIVE Standardize [DATA FILE OR TABLE] for use in [TARGET TOOL]. Apply [LOCALE AND TIME ZONE] and the approved conventions in [STANDARDIZATION RULES]. INSTRUCTIONS Inspect date formats, decimal separators, currency symbols, percentages, whitespace, capitalization, Unicode characters, and category spelling variants. Identify ambiguous values before proposing conversions, especially dates that could use either month-first or day-first notation. Preserve identifiers with leading zeros and distinguish true numeric measures from numeric-looking labels. Create explicit mapping tables for category changes rather than merging values based only on appearance. Retain original fields or a reversible change log. Provide formulas, transformation steps, or code appropriate to the target tool, including handling for failed conversions. CONSTRAINTS Avoid fabricated statistics and claims of completed transformations unless execution occurred. Flag assumptions. Never silently infer an ambiguous date, currency, or category meaning. OUTPUT FORMAT Deliver a normalization specification, executable transformation instructions, an exceptions table, and before-and-after validation checks. Include tests confirming that row counts and unaffected values remain unchanged.