Finch's operations analyst needs a monthly merge suitable for a workbook handoff.
Read /Input/january.json and /Input/february.json, convert their JSON text to structured arrays, merge the rows, retain Status Ready, convert Units to integers and write Cleaned. Save the cleaned-row count in /Output/summary.txt. Preserve source IDs and files.
Finch Services receives monthly JSON files from an older reporting app. The files contain original request IDs, text quantities and readiness statuses. You need one clean worksheet containing Ready records from both months, with Units converted to numbers and IDs preserved as text.
Build the file read, JSON conversion, merge and cleanup as separate actions. Convert JSON to custom object creates the row values, and Convert text to number gives Units its numeric type. The preparation steps check their intermediate outputs even before a write occurs, so a misleading fixed message won't pass. One hidden month has no rows; the other contains a known zero quantity. Both are valid input states. The final step writes the cleaned worksheet and a small text summary, leaving the source files unchanged. This is a local desktop flow over fictional files; it doesn't read folders on your computer or launch a real Excel instance.