Wires two consolidation mechanisms into the shipped nightly cycle, both default
OFF so existing behavior is unchanged:
- dream_rollouts (>1): multi-rollout contrastive reflection per task
- recall_k (>0): associative recall of the K most-similar past tasks (from a
capped task_archive persisted in state.json) into tonight's dream
- dream_factor (>0): synthetic task variants
New shared engine module skillopt_sleep/dream.py (recall_similar, dream_augment,
dream_consolidate) is called by both the plugin cycle and the experiment harness,
so reported numbers exercise the exact shipped code. Built on the existing
rollouts_k/sample_id support already in consolidate.py/rollout.py.
Validated (5 nights x 10 real tasks/night, full held-out test, GPT-5.5, gated):
the gain scales with recall depth on a clean signal —
SearchQA recall_k=10 +3.1, recall_k=20 +4.5, full-history reference +5.6;
SpreadsheetBench (nano, gate-free) +3.6. Flat within noise on saturated/noisy
cells. See docs/sleep/EXPERIENCE_REPLAY.md (+ raw runs under blog_runs/v2_port/).
Co-Authored-By: Claude Opus 4 <noreply@anthropic.com>
Open-source-tool / research-code separation:
- git mv skillopt/sleep/ -> skillopt_sleep/ (top-level, sibling to the research
skillopt/ package). History preserved as renames.
- All imports skillopt.sleep.* -> skillopt_sleep.*.
- Vendor the validation gate into skillopt_sleep/gate.py (a self-contained copy
of skillopt.evaluation.gate). The engine now has ZERO dependency on the
research package — verified: grep finds no `from skillopt.` in skillopt_sleep/,
and consolidate's gate resolves to skillopt_sleep.gate.
- Plugin scripts/commands/skill call `-m skillopt_sleep`.
29 tests pass; `python -m skillopt_sleep` runs standalone.
Co-Authored-By: Claude Opus 4 <noreply@anthropic.com>
