Checks each incoming file for errors, cleans it up, saves it to GitHub, and emails your team the results.
It branches. Exactly one path is taken; runs once per each incoming file.
Pattern: Exclusive Choice (4) · Simple Merge (5) · Multiple Instances with a priori Design-Time Knowledge (13)
Every time a new batch of files comes in, someone has to check them for errors, clean up the formatting, and keep a version history in case something goes wrong. Skipping that step means bad data can slip into your systems unnoticed. And if a file fails, you often don't find out until much later.
Operations or data teams who receive regular file drops and need a reliable, auditable way to process them.
Incoming files get checked, cleaned, and archived to GitHub automatically, with a summary emailed to your team.
The hard question is not how to build it. It is whether this is the right thing to build first.
That is what a Fractional Chief AI Officer figures out with you, before anyone writes a line of code.
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