Along the same line as what Mensur Dlakic proposes is to look at the average %GC content per sequence. Plotting that will also allow you to quickly inspect whether there might be contamination (especially euk vs pro will work well ). Keep in mind though that this is also a quite crude (but easy/quick) approach that in no way competes with a real FCS analysis.
EDIT: the above is simply an approach you could use. For sure don't take it as an obligation to run such an analysis!! In most cases or unless you have complicated samples this will not be necessary as contamination will be low to non-existing.
I would say no. There should be no contamination if the experimental component of study was rigorously done. There is little chance you added contamination during the analysis phase. If there is possibility of contamination in your data then that should have been addressed before you started assembling the data.
Thank you for clarification.
One other question a bit unrelated. Everytime i post a question i wait for your response. I personally believe that you have more knowledge and experience in genome assemblies. Is there any way i can follow and look at your work. may be os other platforms like Google scholar or anywhere else. If you feel ok in sharing.
I agree that generally you shouldn't need to do a contamination analysis. I added one into a pipeline for my last lab because the quality of samples we received from partners varied a lot. So, if you notice your assemblies are more fragmented than anticipated or find unexplained patterns in data then it can be useful to try and clean up that mess.
I liked using metagenomic tools like Kraken2 for contamination.