Marker trait for the nodes that produce a truth degree from crisp input: the hedges (Very, Somewhat) and the membership curves (TriMF, TrapMF, GaussMF, SigMF), plus the explicit conversion _TruthOf.
These are the fuzzy tier's entry points: a membership function maps a crisp measurement into [0, 1], and everything downstream is an ordinary truth value that the connectives already understand. Their eval therefore returns _Truth.of(degree) rather than a plain number — a membership degree is a truth value, and returning one is what lets very(trimf(t, 0, 10, 20)) and somewhat(x) compose without an explicit cast at every step.
Arguments are read with asDegree, which accepts a bare number in [0, 1] as well as a _Bool/_Truth: a hedge has no other domain, so there is none of the ambiguity that makes the connectives insist on asTruth. An argument outside the domain, or one that does not reduce, leaves the node symbolic.
