I will audit your scientific github repo for reproducibility

Great scientific code is useless if nobody can understand, install, or reproduce it.

I am Maris, a chemist and researcher. I will review your scientific, data-analysis, or technical GitHub repository like a real scientist-user: can I understand what it does, what data it needs, how to run it, and whether the method is transparent enough to trust?

I check:

- README clarity

- installation and environment instructions

- dependencies and version information

- examples, notebooks, and run commands

- data availability and file path issues

- method transparency

- citation / license / documentation gaps

- what a new user would find confusing

- practical steps to improve the repo

You receive a clear audit report with what works, what is unclear, what is missing, and what to fix first.

This is not a cybersecurity audit, penetration test, or full code rewrite. I do not guarantee execution of unsafe or very large codebases. The focus is clarity, scientific reproducibility, documentation, and user trust.