snakemake-tutorial | head node of an HPC cluster running Slurm

I am trying to execute the workflow of the Snakemake's official tutorial via Tibanna on AWS.

As instructed here,

1. I have installed Tibanna and set up environment variables.
2. Then I deployed Tibanna Unicorn to a folder snakemake-tutorial in a specific S3 bucket specific-bucket.
3. I set up the default unicorn.
4. As a last step, I run the following command:

I would like to know all necessary criteria required for snakemake to decide that a job needs to be executed, but I couldn't find them in their documentation. The best source I have found is in snakemake author's slides from 2016, which says:

I'm a newbie using Snakemake and not an expert in Python neither so the answer might be quite obvious. Everything in my workflow worked fine in my tests until I tried to use glob_wildcards in order to turn all of my fastq.gz files from one directory (FASTQDIR) into fastqc files.

The samples names in the SAMPLES list are okay but I have an error saying that a string is expected instead of a list (I assume this is my SAMPLES list) and I don't really know where to act in my Snakefile in order to correct it. I understand that it is surely linked to my use of glob_wildcards but I don't understand where is the problem. Do you have an idea of how I can fix it ?

Here is my Snakefile code :

I am new to snakemake and have an issue with the following code that should take 9 fastq files one after another and apply fastqc.

smp should take the values:

UG1_S12 UG2_S13 UG3_S14 UR1_S1 UR2_S2 UR3_S3 UY1_S6 UY2_S7 UY3_S8

Which works when I run