- Ratified first (docs/analysis/close-flywheel-proposal-review-visibility-ratification-2026-06-16.md) before any impl edits.
- Additive proposal_review_posture in evals/close_derived_climb (from already-captured emission bodies; asserts born proposal_only/SPECULATIVE/requires_review posture, review_eligible, none_accepted_or_promoted inside the yardstick).
- Additive proposal_review_summary in evals/anti_regression DemoReport + run_demo (teaching gate review_states + ProposalLog transition counts from the temp log events exercised by S1-S3; close_derived subsection from the embedded climb).
- Updated RESULT text, contract test docstring + soft presence assert, climb __init__/contract, testing-lanes (new subsection), anti-regression docs, runtime_contracts.
- All strictly within scope: measurement/visibility only; no changes to review logic, FrameVerdict, promotion, teaching mutation, or core behavior.
- Verified: 90 contract tests green, core demo anti-regression JSON + text show the signals, climb posture present with correct values, wrong_total=0, all_gates_held + corpus_identical preserved, smoke lanes unaffected.
- Builds on #793 dedicated surface + #792/#791 embedding. Third Door / Mechanical Sympathy / Semantic Rigor alignment per ratif.
- No brief adjustments needed; workflow, scope, and success criteria followed exactly.
- Makefile: new 'test-close-flywheel' target (clearly named heavy surface; runs full Claim-B yardstick + anti embedding; explicitly not in fast/slow/full).
- docs/testing-lanes.md: new prominent 'Dedicated CLOSE Flywheel Regression Surface (Claim-B Level)' section with purpose, invocation (make primary), full Claim-B capabilities list, runtime (~60s+ heavy), hermeticity guarantees, Engineering Pillars alignment (Mechanical Sympathy / Semantic Rigor / Third Door per Whitepaper), and all cross-refs (ratifs, contract, anti demo, etc.).
- Cleanly embed / polish (additive, hermetic, building on #792): anti_regression/run_demo.py (comments + RESULT label the surface + make target), test_anti_regression_demo.py (updated docstring), docs/evals/anti_regression_demo.md (how-to + complementary section updated for surface participation).
- Supporting: contract.md (dedicated surface note + ratif links), runtime_contracts.md (tightened ref).
Ratified first (docs/analysis/close-flywheel-dedicated-regression-surface-ratification-2026-06-16.md). Strictly in scope. Preserves all invariants (wrong_total=0, determinism, proposal-only, etc.). No core, no CLI additions, no fast/CI inclusion, no teaching logic changes.
See ratification for pillars justification and 'why only correct path'.
Three shareable demo / benchmark writeups modeled on the existing
`docs/evals/phase6_comparative_demo.md` treatment, each accompanied
by an asciinema-rendered GIF for at-a-glance viewing on the repo page.
- docs/evals/anti_regression_demo.md — three-gate defense; per-gate
table; honesty paragraph about the synthetic regression in S2 (real
ReplayEvidence shape via documented run_replay= kwarg); sample run
output; falsifiable claims index.
- docs/evals/learning_loop_demo.md — headline before/after; CORE-vs-
pretraining comparison table; trust-boundary code snippet showing
the _CORPUS_PATH swap; per-scene table; full sample run; subject-
selection rationale (pack-resident ∧ no active chain ∧ deterministic
intent classification).
- docs/evals/teaching_loop_bench.md — what's byte-identical and why
it matters per artifact; 100-run reference numbers (unique=1 across
all five artifacts; mean=1.849s p50=1.838s p95=1.851s); pairing
paragraph with ADR-0045 (read vs write determinism).
GIF captures (rendered with asciinema 3.2.0 + agg 1.8.1, github-dark
theme, JetBrains Mono):
- docs/evals/assets/anti_regression.gif (120K, 944x843)
- docs/evals/assets/learning_loop.gif (332K, 944x1039)
- docs/evals/assets/teaching_loop_bench.gif (64K, 860x1000)
Raw .cast files preserved alongside the GIFs for re-rendering at
different themes / speeds / sizes without re-recording.
README.md — added writeup-link column to the Inter-Session Memory
three-demo table.
