core/generate
Shay cd97d59f13 fix(math): restore WAVE-A multiplicative aggregate completeness provenance
The ADR-0191 completeness guard (added after WAVE-A) requires aggregating
initials to expose every consumed source token via
`consumed_value_tokens`, so it can confirm no source quantity was
silently dropped.  The WAVE-A "each weighing" injector predates the guard
and left that field empty, so for every "<Subject> <verb> M <outer>, each
... N <unit>" reading the guard computed required={M, N} vs
consumed={M*N} and refused as "incomplete reading: source quantities
[M, N] not consumed".  This silently regressed the entire WAVE-A
capability — the canary `test_lilibeth_canary_solves_end_to_end` has been
red on main (it failed byte-identically on f79b647; the smoke gate does
not collect this dedicated test file, so it merged green originally).

Fix: populate `consumed_value_tokens=(count_a_token, count_b_token)` on
the composed initial — exactly the contract the day-enumeration and
embedded-quantifier aggregators already satisfy.

wrong==0 preserved: the two tokens genuinely ARE the multiplicands of the
emitted value; the guard remains refusal-only.  Serving frozen: this
shape does not occur in train_sample, so the fix is serving-neutral.

Evidence:
- tests/test_wave_a_multiplicative_aggregation_injector.py: 11 passed
  (was 1 failed) incl. test_wrong_zero_preserved (full train_sample eval,
  wrong==0).
- core test --suite packs: 141 passed (was 1 failed, 140 passed).
- core test --suite smoke: 67 passed.
- scripts/verify_lane_shas.py: lanes 8/8 match pinned SHAs — the
  train_sample_v1 serving SHA is byte-identical, proving zero serving
  count change.

PR checklist:
- Capability: restores WAVE-A multiplicative-aggregate reading regressed
  by ADR-0191.
- Invariant: wrong==0 (completeness guard stays refusal-only; tokens are
  true multiplicands).
- Lane: core test --suite packs / smoke + lane-SHA gate (8/8).
- No hidden normalization, stochastic fallback, approximate recall, or
  unreviewed mutation.
- Trust boundary: none widened — internal candidate provenance only.
2026-05-31 16:36:44 -07:00
..
binding_graph
comprehension feat(adr-0174-phase5a): retire inert GSM8K scoring-path reader 2026-05-28 13:38:44 -07:00
cue_precision feat(adr-0177-cp2a): cue-precision ledger training + measurement (+ unit hygiene) (#461) 2026-05-29 10:21:58 -07:00
derivation feat(adr-0195): GSM8K product promotion bridge — serving 4/46/0 → 6/44/0, wrong=0 (#500) 2026-05-30 17:33:56 -07:00
__init__.py
admissibility.py
articulation.py
articulation_legality.py
attention.py
bridge_trace.py
dialogue.py
discourse_planner.py
exhaustion.py
graph_constraint.py
graph_planner.py
grounding_accessors.py
intent.py
intent_bridge.py
intent_ratifier.py
math_candidate_graph.py feat(adr-0195): GSM8K product promotion bridge — serving 4/46/0 → 6/44/0, wrong=0 (#500) 2026-05-30 17:33:56 -07:00
math_candidate_parser.py feat(adr-0194): labeled-container subject entity shape — 'Jar A has N' parses, wrong=0-proven (substrate) (#499) 2026-05-30 16:56:09 -07:00
math_completeness.py fix(adr-0191): candidate-graph completeness guard — real-corpus wrong 5→0 (#496) 2026-05-30 15:45:07 -07:00
math_parser.py chore(audit): substrate cleanup — dead spike, gitignore, deprecation, reader diagnosis 2026-05-28 07:00:33 -07:00
math_problem_graph.py fix(math-graph): refuse contradictory initial possessions (wrong=0 hazard) 2026-05-28 09:51:14 -07:00
math_realizer.py
math_roundtrip.py feat(adr-0179-ex2): bare-decimal grounding in the shared round-trip primitive 2026-05-28 17:43:12 -07:00
math_solver.py
math_symbolic_equivalence.py
math_symbolic_normalizer.py
math_verifier.py
morphology.py
ood_surface_generator.py
operators.py
perturbation_suite.py
proposition.py
realizer.py
realizer_guard.py
recognizer_anchor_inject.py feat(adr-0195): GSM8K product promotion bridge — serving 4/46/0 → 6/44/0, wrong=0 (#500) 2026-05-30 17:33:56 -07:00
recognizer_match.py fix(math): restore WAVE-A multiplicative aggregate completeness provenance 2026-05-31 16:36:44 -07:00
recognizer_registry.py
result.py
rotor_admissibility.py
salience.py
semantic_templates.py
stream.py
surface.py
templates.py