  We introduce a framework for fault-tolerant post-selection (FTPS) of
fault-tolerant codes and channels -- such as those based on surface-codes --
using soft-information metrics based on visible syndrome and erasure
information. We introduce several metrics for ranking configurations of
syndromes and erasures. In particular, we introduce the \emph{logical gap} (and
variants thereof) as a powerful soft-information metric for predicting logical
error rates of fault-tolerant channels based on topological error-correcting
codes. The logical gap is roughly the unsigned weight difference between
inequivalent logical corrections and is adaptable to any tailored noise model
or decoder. We deploy this framework to prepare high-quality surface code magic
states with low overhead under a model of independent and identically
distributed (\emph{i.i.d.}) Pauli and erasure errors. Post-selection strategies
based on the logical gap can suppress the encoding error rate of a magic state
preparation channel to the level of the physical error rate with low overhead.
For example, when operating at $60\%$ the bulk threshold of the corresponding
surface code, an overall reduction of the encoding error rate by a factor of
$15$ is achievable with a relative overhead factor of ${< 2}$ (approximately
$23$ times less than that of simple syndrome-counting rules). We analyze a
schematic buffer architecture for implementing post-selection rules on magic
state factories in the context of magic state distillation. The FTPS framework
can be utilized for mitigating errors in more general fault-tolerant logical
channels.
