Measured before and after at the same sample size (n=4), with the six other
model-invoked skills unchanged:
which command runs the TUI suite 25% → 100%
asserting on a Mantine transition 50% → 100%
which tier spawns the built binary 25% → 100%
The lever is the description's SHAPE, not its length: leading with the actions
and then enumerating concrete situations ("Use when … ; when … ; when …") beats
a noun-phrase list of contents ending in a generic "use for any question
about …". The same edit took `pre-push-gate` from 3/5 to 5/5 earlier.
Re-ran the full eval to check the change did not simply move attention off
another skill, which is the failure the previous commit recorded: 40/46, up from
38/46, and the failing set is strictly smaller — `testing` went from three
failures to one, nothing else moved. That remaining case measured 100% in
isolation and 67% in the full run, which is sampling variance rather than a
finding.
AGENTS.md now extends the re-run rule to cover a description edit, not just a
flip, and records the shape that works.
Signed-off-by: cliffhall <cliff@futurescale.com>
f95abb2715