Asking whether the next name needs a word or a shape

tests/shapes.rs answers it. The trick is measuring against names the grammar did not find - harvested from module strings or seen in a trace - because the ones it did find are necessarily spellable and measuring against them measures the search.

Of 183 vendor-shaped independently-found names: 28 reachable, 121 needing a shape, 34 needing vocabulary. Shapes are the binding constraint by more than three to one, which confirms with numbers what the naming side predicted from the other direction (D261).

The first cut was wrong. Counting all 464 independently-found names gave a 68% vocabulary gap - but 276 of them are POSIX or libc names that every vendor pattern, all of which start with the sce prefix, structurally cannot spell. Scoped properly the ratio inverts. Worth remembering: a measurement over the wrong population is not a small error, it points the other way.

Three shapes cost almost nothing and spell fourteen names today: prefix-learned-verb at +0%, prefix-module-learned-learned-verb at +4%, prefix-learned-verb-learned-learned at +11%. The rest of the ranked list runs to +1862% and beyond, and those are names the generator should not be asked for.

And a consequence nobody had costed (D262): repeated learned positions were ruled out by D195 because squaring a big list is unaffordable. learned fell from 12,255 entries to 177 today for unrelated reasons, and that same shape went from 12.2 trillion candidates to 2.5 billion - 4,800 times cheaper. Shrinking a vocabulary list bought shapes that growing it never could, and nothing in the tooling would have said so.