1. I assume you are talking about high coverage data? Then yes, ad hoc, but pretty standard. Ideally one examines the coverage of the assay over many samples and understands why some regions have low coverage. Then understand how this impacts your variant calling.
2. Should be fine.
3. Depends what you want to accomplish with this filter. But yes, 2-5% is fairly standard for baseline tissue samples, mainly to filter variants that are potentially cross-contaminated or so sub-clonal that they are unlikely functional. If cross-contamination is no concern and this is for artifact filtering, then rather filter by supporting reads if you don't trust the caller's likelihood model for borderline calls.
4. This will at some point filter variants in amplifications and in regions of LOH (see also 7). To filter homozygous private germline variants, I would require a minimum number of reference reads to keep and <0.95 to 0.98 allelic fraction, again mainly to deal with cross-sample contamination.
5. Add ExAC if you can, especially non-caucasian populations.
6. This will filter truncating mutations in tumor suppressor genes. So keep truncating mutations, frame-shifts etc.
7. If you want to use allelic fractions, then you need to do it properly, ideally also using copy number adjusted for purity and ploidy (heterozygous SNPs are rare, but you have lots of coverage information close by). But this is hard (see here, here and here - disclaimer, the latter is work by us). Since you filter everything that is not in COSMIC anyways, I guess your goal of 7) is mainly to ignore germline variants in COSMIC? Then maybe require a higher number of COSMIC hits (3-5), especially in difficult genomic regions of low mappability.

I did not see a pool of normals filter in your list, that is usually extremely helpful in removing noise.