Instead of traceplot we recommend using rank histogram plots [1903.08008] Rank-normalization, folding, and localization: An improved $\widehat{R}$ for assessing convergence of MCMC. The online appendix has some examples comparing traceplots and rank histogram plots. Traceplots are not good for long tailed distributions and get fuzzy with long chains.
See the paper [1903.08008] Rank-normalization, folding, and localization: An improved $\widehat{R}$ for assessing convergence of MCMC. We recommend minimum neff of about 100 per chain, so that the needed quantities for convergence diagnostic are estimated reliably. Given that, then instead of focusing to neff, you should figure out what is the needed accuracy for the quantity of interest (for reporting usually 2 significant digits is enough) and then you can check that mcse is sufficient (mcse computation uses neff, but it’s enough to focus on mcse for the quantity of interest).