Yes — a research loop that measures "better" with binary assertions, so
it can decide keep-or-revert without you. Here's the loop and the one
thing that makes it safe.

THE LOOP
  1. Claude reads the skill.md
  2. Proposes ONE change
  3. Runs 5 test prompts through the changed skill
  4. Scores each output against 25 true/false assertions (125 checks)
  5. ALL pass → git commit. ANY fail → git reset, try a different change
  6. Repeat until interrupted or a perfect score holds

WHY BINARY ASSERTIONS ARE THE WHOLE TRICK
"Is this output better" is subjective and un-loopable. "Does the output
contain a dated action item — true/false" is checkable, and 25 of those
give you a hard pass-rate the loop can act on without a human. Vague
scoring is what makes self-improvement drift; binary scoring is what
makes it converge.

THE SAFETY MECHANISM — git as the undo
Every kept change is a commit; every failed change is a reset. The skill
can NEVER end up worse than its last passing state, because a regression
is reverted before the next iteration. That's what makes it safe to run
overnight — the floor is fixed.

WHAT YOU GET
The read-propose-test-score-commit loop, a 25-assertion scoring
harness, git-gated keep/revert, and no-permission iteration until
interrupted.

THE INPUT THAT DECIDES QUALITY
The 25 assertions. Write them to capture what "good" actually means for
this skill and the loop optimizes toward it; write them loosely and it
optimizes toward nothing. Which skill, and what does a great output of
it contain?