Bring SkillOpt's epoch-wise slow/meta update (paper §3.6) into the sleep engine
as skillopt/sleep/slow_update.py — import-light, driven through the Backend
abstraction (mock/claude/codex):
- Reuses the main repo's protected-field markers
<!-- SLOW_UPDATE_START --> ... <!-- SLOW_UPDATE_END --> so the artifact is
compatible; step-level edits never touch this field.
- run_slow_update compares behavior under the first-night vs final skill across
the val tasks, groups into improved/regressed/persistent/stable, and asks the
optimizer to distill durable longitudinal guidance (refining prior text).
- Wired into run_gbrain.run_seed AFTER the nights loop, gated by slow_update=True
and run REGARDLESS of gate_mode — this is what preserves long-term memory even
when the user turns the hard gate OFF (the user's slot_date=slow-update intent).
2 new tests (protected-field round-trip, stub-backend synthesis). 23 tests pass.
Co-Authored-By: Claude Opus 4 <noreply@anthropic.com>
Yifan Yang