Follow-up to PR #398 — lights up the dormant consumption path by
extending _match_rate_with_currency to publish composition_shape +
pre-composed CandidateInitial in parsed_anchors.
Scope: one matcher extension (_match_rate_with_currency) for the
currency-per-unit composition shape ("$X each"). Other composition
shapes (multi-quantity, additive, subtractive) deferred to ME-3/4/5
follow-ups.
Subject binding decision pinned: Option A (refuse when same-sentence
subject is absent). Forbids Option B (placeholder subject —
fabricates attribution). Defers Option C (cross-sentence subject)
to its own ME-2 brief.
Honest consequence: case 0019 stays refused in THIS PR (requires
Option C). Truth-test #1 replaced with a synthetic "Maria bought 3
vet appointments at $400 each" canary that has same-sentence
subject. The flywheel turns one revolution: ratify → compile →
load → consume → admit, end-to-end on the synthetic canary.
Operator profile: Opus (load-bearing wrong=0; pre-composed
CandidateInitial; case 0050 mandatory pin).
Test surface enumerated (4 test files, 12+ tests):
- test_matcher_extension_currency_per_unit (8 narrowness tests)
- test_matcher_extension_case_0050_hazard_pin (mandatory)
- test_matcher_extension_end_to_end_admission (truth test)
- test_matcher_extension_train_sample_baseline_preserved
- test_matcher_extension_public_split_preserved
6-row truth test pinned. Anti-regression invariants enumerated.
Forbidden surface includes Option B + new SAFE category entries +
solver mutation.
Recommended next dispatch sequence: ME-1 → ME-2 (case 0019) →
ME-3/4/5 (remaining composition shapes).
Closes the consumption-half of the math teaching loop for two of three
sub-types per docs/handoff/CONSUMPTION-WIRING-DISPATCH-PACK.md (PR #397).
Companion to the doctrinal brief in PR #396.
Modules
-------
- language_packs/compile_frames.py — byte-deterministic compile of
frames/*.jsonl → frames.jsonl (sorted by (frame_category, surface_form))
- language_packs/compile_compositions.py — same shape for
compositions/*.jsonl → compositions.jsonl
- generate/comprehension/frame_registry.py — load_frame_registry()
mirroring load_lexicon: cache by (path, mtime, sha256), manifest
checksum verification (optional frame_checksum field), polarity
validation, conflict detection, empty-registry no-op
- generate/comprehension/composition_registry.py — same shape PLUS:
* SAFE_COMPOSITION_CATEGORIES enforced at LOAD (defense in depth;
raises WrongCompositionCategory on any unsafe category — protects
against pack edits that bypass the handler)
* polarity "falsifies" exposed via is_falsified() (consumer must
suppress; not silently treated as affirms)
- language_packs/compiler.py — manifest verification extended for
frame_checksum + composition_checksum, mirroring the proven
glosses_checksum pattern (optional fields; backward-compatible)
- generate/recognizer_anchor_inject.py — inject_from_match consults
composition_registry when the per-category injector returns empty
AND the matcher publishes ``composition_shape`` in parsed_anchors.
Registry is a gate (admissibility) not an arithmetic primitive
(ADR-0169 §"Mutation boundary").
Tests (38 new, all green)
-------------------------
tests/test_frame_registry_load.py (11 tests)
tests/test_composition_registry_load.py (11 tests)
tests/test_composition_consult_in_injector.py ( 6 tests)
tests/test_consumption_case_0050_hazard_pin.py( 3 tests, parametrized
over allowlist)
tests/test_consumption_empty_registry_no_op.py( 4 tests)
tests/test_consumption_partition.py ( 3 tests)
Registered in core/cli.py "packs" suite.
Suite results
-------------
core test --suite teaching -q → 93 passed
core test --suite runtime -q → 20 passed
core test --suite packs -q → 51 passed
core eval gsm8k_math --split public → 150/150, wrong=0
Truth-test rows (6-row binding table in dispatch pack):
#1 Case 0019 admits ............. PARTIAL — see Scope Boundary below
#2 Case 0050 stays refused ....... PASS
#3 train_sample 3/47 → ≥4/46 ..... PARTIAL — same as #1#4 wrong == 0 preserved .......... PASS
#5 public split 150/150 .......... PASS
#6 Empty-registry no-op .......... PASS
Scope Boundary (honest finding)
-------------------------------
Rows #1 and #3 (case 0019 admission) require a matcher extension that
publishes ``composition_shape`` + a pre-composed CandidateInitial in
parsed_anchors. The existing currency_amount / multiplicative_aggregation
matchers in generate/recognizer_match.py are detection-only (return
empty parsed_anchors). This PR ships the consumption infrastructure
correctly but the runtime path remains dormant until a follow-up PR
extends the matcher. The dispatch pack's truth test #1/#3 cannot fire
without that extension.
The wiring is positioned correctly: inject_from_match → consult
composition_registry → admit on affirms-with-payload, suppress on
falsifies, refuse on absence. A synthetic recognizer match with
populated composition_shape + composed_initial DOES admit through the
new path (covered by 6 tests in test_composition_consult_in_injector.py).
A follow-up brief naming the matcher-extension work is the
recommended next step.
Anti-regression invariants verified
-----------------------------------
- wrong == 0 on core eval gsm8k_math (public 150/150)
- case 0050 stays refused (parametrized over allowlist categories)
- ADR-0166 — no new eval lanes
- ADR-0167 partition — no cognition imports in any new module
- Empty-registry runtime byte-identical to today (no-op test)
- SAFE_COMPOSITION_CATEGORIES enforced at write AND load
- polarity semantics (affirms vs falsifies) honored
- engine_state/* never committed
Production-line dispatch form of the consumption-wiring brief in
PR #396. One bundled PR recommended (CW-1 + CW-2 share pack-compile
+ manifest extension + case 0050 pin). Split only if CI cycle time
forces.
CW-1 — Frame consumption:
language_packs/compile_frames.py + generate/comprehension/frame_registry.py
+ reader wire + manifest frame_checksum extension.
CW-2 — Composition consumption:
language_packs/compile_compositions.py +
generate/comprehension/composition_registry.py + injector wire in
generate/recognizer_anchor_inject.py + manifest
composition_checksum extension. SAFE_COMPOSITION_CATEGORIES
enforced at load (defense in depth); polarity "falsifies"
suppresses injection (not silently "affirms").
Truth test pinned as binding (6-row table). PR is not done unless
case 0019 admits, case 0050 stays refused, train_sample moves from
3/47 → ≥4/46, wrong==0 holds, public split unchanged (150/150),
empty-registry runtime byte-identical to today.
Operator profile: Opus (load-bearing wrong=0 surface; case 0050
mandatory pin; same rigor as CC-2).
Names the structural gap discovered in the first end-to-end
CompositionClaim ratification (2026-05-27 post-#393):
ratification handler writes JSONL artifacts cleanly, but no runtime
code reads compositions/*.jsonl or frames/*.jsonl. Two of three
sub-types ship the ratification half of the loop without the
consumption half.
State:
lexicon/ writer ✓ reader ✓ (LexicalClaim — closed)
frames/ writer ✓ reader ✗ (FrameClaim — half-open)
compositions/ writer ✓ reader ✗ (CompositionClaim — half-open)
Proposes one bundled PR (CW-1 + CW-2) mirroring the proven
generate/comprehension/lexicon.py::load_lexicon pattern:
CW-1 — Frame consumption: pack-compile frames/*.jsonl into a
runtime-loadable artifact; new load_frame_registry()
loader; reader wire.
CW-2 — Composition consumption: pack-compile compositions/*.jsonl;
new load_composition_registry(); injector wire in
generate/recognizer_anchor_inject.py.
Hard requirements: SAFE_COMPOSITION_CATEGORIES allowlist enforced
at both write and load (defense in depth); polarity "falsifies"
honored; manifest checksum extended per CLAUDE.md "Semantic Pack
Discipline"; empty-registry runtime byte-identical to today.
Truth-test pinned: success is the EVAL DELTA, not the artifact
append. PR is "done" when case 0019 (the canary I ratified) admits
under train_sample, train_sample moves from 3 correct / 47 refused
to ≥4 correct / 46 refused, case 0050 stays refused, wrong==0 holds.
This brief is orthogonal to the workbench UI wave (W1..W4); both
can ship in parallel. Recommended operator: Opus (load-bearing
wrong=0 surface; same rigor as CC-2).
W0 of the workbench-UI wave per WORKBENCH-UI-WAVE-SCOPING.md.
Pure docs PR; no UI code.
Decision: the workbench is a local keyboard accelerator for the
existing local-CLI ratification surface (ADR-0161 Surface C), not a
fourth ratification surface and not a new trust boundary. Every
workbench-driven ratification action invokes the same Python
entrypoint as the corresponding CLI invocation, with identical
preconditions, exceptions, and append-only JSONL effects.
Amends ADR-0160 v1 read-only stance narrowly: admits driving the
three Tier 1.5 handlers (apply_lexical_claim, apply_frame_claim,
apply_composition_claim) and the existing core teaching review path
through the workbench API. Honors ADR-0161's surface set unchanged
(workbench is part of Surface C, not a new surface). Honors ADR-0162
no-go list and pins the keyboard contract referenced in §7.
Five open questions from the scoping brief resolved:
Q1 in-process via existing Python entrypoints
Q2 single-operator (multi-operator deferred)
Q3 same chat/telemetry.py JSONL sink, new event kinds
(operator_ratify / operator_reject / operator_defer /
operator_navigate); no parallel log
Q4 fonts and icons bundled locally; no CDN
Q5 dist/ gitignored; CI verifies build, does not commit artifact
Ratification record extended with ratifier_kind: "workbench" — audit
forensic discriminant only, not a permission gate. proposal_id + to
remain the only load-bearing replay fields (ADR-0161 §5 unchanged).
Compatibility audit covers ADR-0146, 0150, 0152, 0160, 0161, 0162,
0167, 0168/0168.1, 0169/0169.1, 0172. Forbidden surface enumerated:
no remote operator, no CORS relaxation, no new mutation paths, no
auto-ratify, no batch ratification, no engine_state writes outside
the existing checkpoint path, no parallel workbench-events log, no
mobile/responsive form factors (ratification stays on Surfaces A+B
for mobile per ADR-0161).
Acceptance gates pinned per W1..W4 of the scoping brief.
Names the wave shape before any implementation. Audits what doctrine
has already settled (ADR-0160 stack pins + read-only trust boundary;
ADR-0162 design system + 15-component must-ship list + no-go list),
catalogs the current state (backend complete, frontend zero), surfaces
the five operator pain points sourced from the 2026-05-27 demo and the
CompositionClaim brief pack, and proposes a five-wave sequence:
W0 (docs) — Trust-boundary ratchet ADR (ADR-0173 working title)
admitting operator ratification through the workbench,
scoped to existing Tier 1.5 handlers (Lexical / Frame /
Composition) and pinning the keyboard contract.
W1 (base) — workbench-ui/ scaffold per ADR-0162 Branch 1.
W2 (read) — ProposalQueue + ProposalCard + ProposalDetailPanel.
W3 (act) — RatificationCommandPanel + handler dispatch (the
throughput multiplier).
W4 (verify)— TraceDrawer + ReplayTheater + EvalCenter.
Guardrails enumerated: CLAUDE.md docs discipline, ADR-0162 no-go list,
determinism, trust boundary, wrong==0, case 0050 hazard pin,
keyboard-first, accessibility, local-first, no engine_state writes
outside the checkpoint path.
Open questions (in-process vs out-of-process ratification, single- vs
multi-operator, telemetry path, font/icon bundling, build artifact
location) listed for W0 resolution. No code in this brief.
* docs(tier1.5+tier2): FrameClaim handler + Tier 2 W5 schema brief pack
Two parallel briefs ready for dispatch:
- F1: FrameClaim ratification handler (Opus) — implements ADR-0168 +
ADR-0168.1; turns 2 of 8 Tier 1 proposals into real GSM8K
admissions on ratify
- T2-W5: MathReaderInferenceProposal schema (Sonnet) — Tier 2 substrate
with two-arm test-and-learn type contract
Zero file overlap between briefs; safe to dispatch concurrently. W6+
deferred until FrameClaim is live (Arm 2 known-good preservation needs
a working handler to verify against).
* docs(briefs): correct pack + workbench paths in Tier 1.5/Tier 2 brief
Operator dispatching F1 (PR #389) discovered:
- Pack path is language_packs/data/en_core_math_v1/, not packs/en_core_math_v1/
- Workbench dispatch table lives in workbench/readers.py, not workbench/api.py
Both operators landed on the correct locations regardless. Folding the
corrections into #387 directly so future operators reading the brief
get the real paths.
Bundles three post-Tier-1 follow-ups into one PR (no scope change, no
new ADR — implementation tightening on the already-shipped corridor).
(1) Standalone JSONL self-containment
teaching/math_contemplation_proposal.py
+ to_jsonl_record() — emits proposal_id + full evidence_pointers
(nested dicts including audit_row) + full reasoning_trace.steps
+ from_jsonl_record() — inverse; goes through build_proposal()
so all invariants are re-validated; raises on proposal_id mismatch
canonical_bytes() UNCHANGED (still the content-hash function;
trace_id/proposal_id stability preserved)
core/cli.py W3 lane now writes to_jsonl_record() output instead of
canonical_bytes() — same compact-JSON encoding (sort_keys=True,
ensure_ascii=False, separators=(",", ":"))
workbench/readers.py loads via self-contained record fields directly;
decompose_audit() re-run removed. read_math_proposal() now reads
reasoning_trace.steps and evidence_pointers from the JSONL record.
(2) Widened change_kind heuristic dispatch
teaching/math_contemplation.py
+ _CHANGE_KIND_BY_PAIR table on (refusal_reason, missing_operator):
(unexpected_category, pre_frame_filler_sentence) → matcher_extension
(unexpected_category, multi_subject_sentence) → frame_reclassification
(unexpected_category, fraction_percentage_literal) → matcher_extension
(unexpected_category, descriptive_frame_question) → frame_reclassification
(unresolved_pronoun, pronoun_resolution) → matcher_extension
Single-key fallback (lexicon_entry/narrowness_violation/
frame_unrecognized) retained for completeness.
hypothesis-step justification text updated to reflect new table.
Result on audit_brief_11.json:
3 matcher_extension (was 0)
2 frame_reclassification (was 0)
3 injector_sub_shape (was 8)
0 vocabulary_addition (no unknown_word group ≥2 in train sample)
(3) shape_category structural gap
MathReaderRefusalEvidence does not carry shape_category, so the
proposal cannot derive it. All proposals continue to emit
ShapeCategory.UNCATEGORIZED with a structural-gap comment. No
invented values — handler dispatch decision (per ADR-0167-FOLLOWUPS
§1) drives ratification routing today, not shape_category.
Tests
+ W1: 5 new tests (to_jsonl_record self-containment, round-trip,
byte stability, proposal_id mismatch rejection, canonical_bytes
unchanged invariant)
+ W2: 3 new pair-dispatch tests + real-audit change_kind distribution
test + shape_category-uncategorized test
+ W3: 2 new tests (records are self-contained, round-trip via
from_jsonl_record); existing byte-comparison test updated to use
proposal_id ordering instead of canonical_bytes
+ W4: existing 6 tests updated to build JSONL via to_jsonl_record;
+ 1 new decoupling test that drops teaching.math_contemplation from
sys.modules and verifies the workbench still loads + serves detail
Verification
- core eval math-contemplation produces the expected 3/2/3 distribution
- core test --suite teaching -q → 33 passed
- core test --suite runtime -q → 20 passed
- All 57 ADR-0172 W1-W4 tests pass (49 existing + 8 new)
Determinism / invariants preserved
- canonical_bytes() byte-stable (test pins this)
- to_jsonl_record() byte-stable via sort_keys=True + no floats
- wrong=0 invariant: proposals stay evidence-only; no auto-apply
- ChangeKind Literal unchanged (4 values; no new ones invented)
Wires teaching/math_proposals/proposals.jsonl into the CORE Workbench
API (ADR-0160) alongside the existing cognition proposal queue:
workbench/schemas.py
- MathReasoningStep, MathProposalSummary, MathProposalDetail,
MathRatifyResult schemas
workbench/readers.py
- MATH_PROPOSALS_JSONL + _DEFAULT_MATH_AUDIT_PATH constants
- teaching/math_proposals added to ALLOWED_ARTIFACT_ROOTS
- _HANDLER_DISPATCH table (vocabulary_addition→LexicalClaim; all
others not yet implemented)
- list_math_proposals(), read_math_proposal(), ratify_math_proposal()
- read_math_proposal() re-runs decompose_audit() to recover full
4-step reasoning trace (canonical_bytes only carries trace_id)
- ratify_math_proposal() raises NotImplementedError with clear
"handler not yet implemented: {change_kind}" for unhandled kinds
workbench/api.py
- GET /math-proposals, GET /math-proposals/{id}
- POST /math-proposals/{id}/ratify → _math_ratify()
(vocabulary_addition→200/routed; unhandled→501 with loud message)
tests/test_adr_0172_w4_workbench_e2e.py — 6 tests:
1. loads from JSONL
2. renders domain:math badge (distinct from cognition /proposals)
3. ratify-vocabulary_addition routes to LexicalClaim (200)
4. ratify-matcher_extension fails loudly (501 "handler not yet
implemented")
5. all 4 trace steps visible in detail response
6. no cross-contamination between math and cognition queues
teaching + runtime suites green (28 + 20 passed).
Brief-gap note: canonical_bytes() excludes proposal_id and serialises
evidence pointers as hashes only. D1 loader derives proposal_id via
sha256(line_bytes) and re-runs decompose_audit() to recover full trace
for read_math_proposal(). This works but means the JSONL cannot be
loaded without the original audit file. If a future wave needs
standalone JSONL loading, C1 should emit a richer format.
Add decompose_audit(audit_path) to teaching/math_contemplation.py.
Groups audit_brief_11.json refusal rows by
(refusal_reason, missing_operator), emits one
MathReaderRefusalShapeProposal per group of >=2 rows, each carrying a
4-step ReasoningTrace (observation -> grouping -> hypothesis ->
conclusion).
Determinism:
- Group iteration sorted by (refusal_reason, missing_operator).
- Evidence per group sorted by case_id.
- Output tuple sorted by proposal_id.
- 10x rerun -> byte-identical proposals + trace_ids.
Pure read-only: audit file is not mutated, no proposals written to
disk, no chat/field/generate/algebra imports.
Tests (tests/test_adr_0172_w2_decomposer.py): real-audit emission,
determinism (10x), evidence floor, change-kind dispatch over all four
heuristic branches, four-step trace, case_id sort, proposal_id sort,
empty input -> empty tuple, unmapped operator skip, missing file ->
FileNotFoundError, no-mutation contract.
Added to core test --suite teaching.
New module `teaching/math_contemplation_proposal.py` defines the
`MathReaderRefusalShapeProposal` dataclass — the math-domain analog of
`TeachingChainProposal` for the Tier-1 contemplation corridor.
- `build_proposal` enforces all seven invariants: math domain, ShapeCategory
enum membership, ≥2 evidence pointers, valid ChangeKind Literal, JSON-
serializable payload, ≥40-char wrong_zero_assertion, and non-None
reasoning_trace with a non-empty trace_id.
- `canonical_bytes` / `compute_proposal_id` produce stable sha256-based IDs;
evidence reduced to evidence_hash, trace to trace_id for stability.
- `ReasoningTrace` imported under TYPE_CHECKING only (W0/A1 not yet merged);
duck-typed at runtime via trace_id attribute.
- 16 tests cover all eight brief obligations plus freeze and sensitivity checks.
- `core test --suite teaching -q` green (17 passed).
Schema-only module defining ReasoningStep / ReasoningTrace with
byte-identical canonical serialization and sha256 trace_id derivation.
Replay-equivalence is enforced by:
- sorted-key JSON, no whitespace, ensure_ascii=False, allow_nan=False
- recursive rejection of float values in payloads (replay hazard)
- step_index monotonicity from 0
- empty trace rejected
- Literal-checked step_kind across all eight Tier 1+2 kinds
No runtime hook. No import from chat/field/generate/algebra.
Downstream (W1 ShapeProposal, W2 decomposer) consume this schema.
Tests: 12 new, full teaching suite green (17 passed).
The brief pack referenced `teaching/audit_evidence.py` in 3 spots
(A2 schema field, A2 read-required list, B2 algorithm step 3a). The
actual module on main is `teaching/math_evidence.py` (carries
`MathReaderRefusalEvidence` per ADR-0167).
Sonnet (A2 / PR #380) discovered the discrepancy and correctly used
the real module. This patch corrects the brief so Wave B operators
(B1 / B2) do not hit the same gap on dispatch.
No runtime change. Pure docs.
Coordination artifact for ADR-0172 Tier 1 dispatch. Six PRs in the
ADR (W0, W0.1, W1, W2, W3, W4) collapsed into a 4-wave DAG with two
concurrent briefs per wave A and B.
Operators are dispatched in their own UIs by pointing at the
section heading — "read §Brief A1" etc. Bundling options A/B/C
inside the doc let the operator choose CI economy vs wall-clock.
No runtime change. Pure docs.
Second implementation PR of the ADR-0170 wave. Extends the DCS injector
to emit ``CandidateOperation(kind='add')`` for acquisition verbs
alongside the existing ``CandidateInitial`` emission for possession
verbs. Proves the W1 type-widening with real emission of both union
members.
## What changes
### `generate/recognizer_match.py`
- New `_ACQUISITION_VERBS` frozenset (12 verbs: collect/get/receive/buy
inflections). Each member is a subset of `ADD_VERBS` so the downstream
CandidateOperation post-init whitelist accepts the matched_verb token.
- Extractor now accepts either possession OR acquisition verbs and
records `anchor_kind` (`"possession"` | `"acquisition"`) plus
`verb_token` in the parsed anchor schema.
### `generate/recognizer_anchor_inject.py`
- `inject_discrete_count_statement` dispatches on `anchor_kind`:
- `"possession"` → `CandidateInitial` (existing behavior unchanged)
- `"acquisition"` → `CandidateOperation(add)` (new)
- New helper `_build_operation_from_discrete_count_acquisition`
constructs the operation. Operand uses `_resolve_count_value`;
matched_verb uses `_locate_token` for round-trip ground check.
- Return type uses `InjectorEmission` from W1.
### Tests
- `tests/test_adr_0170_w2_dcs_acquisition_verbs.py` (new) — 22 tests:
- Verb-set membership pins
- Acquisition ⊂ ADD_VERBS sanity check
- Possession + Acquisition disjoint
- Extractor records anchor_kind correctly
- Injector emits CandidateOperation for acquisition verbs
- Possession path still emits CandidateInitial unchanged
- Deliberate exclusions (gained / donated / saved) still refuse
- Case 0050 hazard pinned (does/contemplates not in either set)
- Determinism + roundtrip_admissible passes
- Updated `tests/test_adr_0163_d2_discrete_count_injection.py` to
reflect new anchor schema fields (anchor_kind, verb_token).
- Updated `tests/test_adr_0170_w1_injector_type_widening.py` —
the DCS injector now legitimately returns
`tuple[InjectorEmission, ...]` (not narrower).
## Deliberate exclusions
These verbs are NOT in `_ACQUISITION_VERBS` and the extractor refuses
them — preserving wrong=0:
- `gained / gains / gain` — delta-of-attribute (weight, age), not
acquisition. Admitting as add-operation would risk wrong>0 on
questions that ask total state.
- `donated / donates / donate` — SUBTRACT semantics (actor gives away).
- `saved / saves / save` — ambiguous (time vs money vs effort).
Widening this set is operator-reviewable per `feedback-wrong-zero-
hazard-case-0050` discipline.
## ADR-0131.G.1 branch-disagreement discipline preserved
The regex parser already emits `CandidateOperation(add)` for
acquisition verbs via `ADD_VERBS` for single-word units. The new DCS
injector path emits the same kind of operation for multi-word units
(where the regex parser fails). Collapsed-tie when both paths emit
identical operations on overlapping shapes; no disagreement.
## Test plan
- tests/test_adr_0170_w2_dcs_acquisition_verbs.py: 22 passed (new)
- tests/test_adr_0163_d2_discrete_count_injection.py: ~30 passed
(existing tests updated for new schema fields)
- tests/test_adr_0170_w1_injector_type_widening.py: 6 passed
- tests/test_recognizer_skip_wrong_zero.py + brief_11b + brief_11 +
candidate_graph_wiring + candidate_domain_partition: passed
- evals/gsm8k_math/train_sample/v1: counts=correct=3 refused=47 wrong=0
unchanged (case 0023 still has S2/S3 downstream blockers; W2's value
is infrastructure, not direct lift)
## Hard invariants
- `wrong == 0` preserved (case 0050 hazard pin + deliberate verb
exclusions + roundtrip_admissible gate)
- ADR-0166: no new eval lanes
- No teaching-store / pack mutation
- ADR-0131.G.1 branch-disagreement discipline preserved (acquisition →
operation, not initial)
- Five-layer wrong=0 safety net (ADR-0163.D.2) intact and extended
## W3 NOT in this PR — honest skip
Initial plan was to bundle W2 + W3 (A1 currency_amount injector).
Inspection of the 4 actual `currency_amount` GSM8K refusals showed
none match A1's narrow form (`<ProperNoun> earns|charges $<amount>`):
| Case | Statement | Reason narrow form doesn't fit |
|---|---|---|
| 0019 | "this requires 3 vet appointments, which cost $400 each" | anaphoric subject + multi-quantity |
| 0026 | "Aaron and his brother Carson each saved up $40" | multi-subject + "each" |
| 0028 | "It cost $100,000 to open initially" | pronoun subject |
| 0043 | "Her mother gave her an additional $4, and her father twice as much" | multi-clause + comparative + transfer |
Shipping W3 as-designed would have re-introduced the dead-code pattern
#373 just cleaned up. Skipped honestly; ADR-0172 Tier 1's decomposer
(the next wave) will surface category-shape mismatches like this
programmatically.
* docs(ADR-0172): math-domain corpus-decomposition mechanism (Learning Arc analog)
Scoping ADR for the math-domain analog of cognition's
`teaching/contemplation.py` corpus-decomposition loop (Learning Arc
milestone 2026-05-25).
## What this ADR scopes
A mechanism that reads the math audit corpus and emits
`MathReaderRefusalShapeProposal` records — structural commonalities
across N refusal cases, paired with the candidate mechanism change
that would resolve them (matcher extension, injector sub-shape,
vocabulary addition, frame reclassification).
Today the operator does this decomposition by hand (reads
audit_brief_11.md, identifies the commonality across 21 DCS
refusals, scopes the matcher/injector extension, files a focused PR).
ADR-0172 shifts the decomposition to the engine, with HITL
ratification preserved.
## Sequencing — explicit
ADR-0172 ships AFTER ADR-0170 (injector contract widening),
ADR-0168 (FrameClaim handler), and ADR-0169 (CompositionClaim
handler — reserved). Without those substrates, the decomposer can
identify patterns but cannot route them to a ratification handler
that knows how to materialize them. Cognition's learning arc
followed this same sequencing: substrate first, then decomposer.
## Why this matters
ADR-0167 LexicalClaim shipped the math-domain wire from refusal →
evidence → operator-ratification. ADR-0172 closes the gap to the
engine-decomposes loop — the moment cognition's learning arc
qualitatively shifted from "engine refuses + operator authors" to
"engine teaches itself through reviewed correction."
The Learning Arc memory entry (2026-05-25) names that moment as
when measurable progress accelerated. ADR-0172 makes the math-domain
trajectory toward the same loop explicit in the queue.
## Hard invariants preserved
- wrong=0 by construction (proposals are evidence-only)
- ADR-0166: no new eval lanes
- No teaching-store / pack mutation
- No non-deterministic mechanism (rule-based grouping, not learned
classification)
- Cross-domain partition (ADR-0167 W2-C) preserves cognition
contemplation behavior
No code, no test, no eval, no pack change in this PR.
## Cross-references
- ADR-0056/0057 — cognition contemplation/proposal substrate (template)
- ADR-0167 + FOLLOWUPS §1 — parent evidence wire
- ADR-0168 + ADR-0168.1 — FrameClaim (ratification target)
- ADR-0169 (reserved) — CompositionClaim (ratification target)
- ADR-0170 — injector contract widening (substrate prerequisite)
- Memory: Learning Arc Milestone 2026-05-25 — the moment to recreate
- Thesis: decoding, not generating — the principle preserved
* amend(ADR-0172): add Tier 2 — intensional contemplation with test-and-learn loop
Per operator feedback during ADR-0172 review: the corpus-decomposition
mechanism should not only emit explicit rules (extensional) but also
develop inference (intensional) — recognizing structural equivalence
classes across surface variations without enumerating them.
## Tier 2 — intensional contemplation
Engine recognizes that 'Sam has 5 apples' and 'Sam collected 5 apples'
carry the same canonical proposition structure, without an explicit
verb-list extension. Emits MathReaderInferenceProposal records that
name structural equivalence classes rather than enumerable rules.
This is the thesis word the original draft missed: rationalization.
Tier 1 ratifies rules; Tier 2 ratifies inference.
## Test-and-learn loop
Tier 2 proposals carry held-out test evidence:
1. Decomposer surfaces hypothesis
2. Held-out subset of corpus reserved
3. Bridge applied to held-out cases; admissibility gates run
4. Outcome scored (positive / negative / neutral)
5. Negative-evidence proposals auto-rejected before HITL
6. Operator reviews proposal + test result, not bare claim
This makes Tier 2 thesis-coherent: engine decodes a structural
pattern, tests it against unseen corpus cases, surfaces the test
result. Wrong=0 cannot leak through — held-out test failures reject
internally.
## Updated implementation outline
Tier 1 wave: W1-W4 (schema, decomposer, CLI, workbench integration)
Tier 2 wave: W5-W9 (schema, equivalence-class recognizer, test-and-learn
loop, HITL integration, bridge application path)
## Hard invariants preserved at both tiers
- wrong=0 by construction (Tier 1: evidence-only proposals; Tier 2:
held-out test rejects wrong-admitting bridges internally)
- ADR-0166: no new eval lanes
- No non-deterministic mechanism (rule-based grouping + deterministic
test-and-learn, not learned classification)
- Cross-domain partition preserves cognition contemplation behavior
* amend(ADR-0172): split Tier 2 test-and-learn into two-arm confirmation
Per operator feedback during ADR-0172 review: 'confirm against known
facts/prior solutions' is the missing arm. The Tier 2 test-and-learn
loop now has BOTH:
- Arm 1 (negative / wrong=0 on held-out refusals) — already drafted
- Arm 2 (positive / known-good preservation) — NEW
Arm 2 inherits ADR-0057's replay-equivalence contract: any
inferential bridge that would change a currently-correct outcome is
REJECTED INTERNALLY before reaching HITL, even if the new outcome is
defensible. Existing truth survives; new truth is gated.
Both arms must PASS or be neutral. Either arm rejecting → proposal
does not reach the operator. This makes the engine's reasoning
provably conservative: it confirms against truth it already knows AND
truth it hasn't yet decided.
The 5-step proposal lifecycle is updated to reflect both arms +
test-set partition + per-case verdict tables in the emitted proposal.
No code change. No runtime effect.
* amend(ADR-0172): add foundational reasoning-articulation substrate
Per operator feedback: for the engine to infer/test/learn from
feedback, it must first be able to ARTICULATE its own reasoning in a
structured, persistent, replayable form.
Articulation is the project thesis's 5th anchor ("listen → comprehend
→ recall → think → articulate → learn from reviewed correction →
replay"). Today CORE articulates SURFACE (templated realizer output)
but does not articulate REASONING — the inference chain that took the
engine from refusal corpus to hypothesis to proposal.
Without reasoning-articulation, none of the three loops can work:
- Loop 1 (self-test) has nothing to record about what it tested or why
- Loop 2 (HITL review) sees a black-box conclusion, not inference chain
- Loop 3 (feedback) has no specific step the operator can target with
a rejection rationale
## Substrate: ReasoningTrace schema
Every proposal carries a typed, content-addressable
ReasoningTrace recording each inference step:
ReasoningStep:
step_kind: observation | grouping | abstraction | hypothesis |
test_design | test_application | test_result | conclusion
input_pointers: prior steps + evidence rows
claim: human-readable assertion at this step
justification: why the engine made the claim
output_payload: type-discriminated by step_kind
The trace is byte-identical across replays of the same corpus +
verdict history. Inherits CORE's existing determinism discipline.
## Sequencing
Articulation ships FIRST (new W0 wave) — it is the prerequisite for
Tier 1 and Tier 2 and Loop 3. Each downstream wave emits or consumes
ReasoningTraces.
## Hard invariants preserved
- Deterministic-replay (trace byte-identical under same inputs)
- ADR-0057 replay-equivalence (trace IDs stable across reruns)
- No non-determinism added (rule-based step emission, not learning)
- ADR-0166: no new eval lanes
No code, no test, no eval, no pack change in this PR.
The G.2 test \`_comparative_clause_refusal_count\` reads \`report.json\`
and counts refusals whose reason quotes a statement clause containing
comparative anchors ("more/less than", "twice as many", etc.). After
#359's wrong=0 fix, the candidate-graph emits two refusal-reason
families that both quote a statement:
1. "no admissible candidate for statement: '...'" — parser-path
refusal (the comparative-parse-failure family this metric tracks).
2. "recognizer matched but produced no injection for statement:
'...'" — recognizer-path refusal; the quoted statement may
incidentally contain comparative anchors but the refusal cause is
the missing injector, NOT the comparative parse.
The pre-#359 counter only saw family (1) reasons; post-#359 it
over-counts whenever a recognizer-path refusal quotes a statement
containing comparative anchors. This was the test failure A2's PR
(#369) and the cleanup PR (#373) both surfaced.
## Fix
Filter the counter to exclude family (2) explicitly. Recognizer-path
refusals are tracked separately by the recognizer-wiring test suite;
they don't belong in the G.2 metric.
Result on current main:
- total statements with comparative anchors in refusal reasons: 2
- parser-path: 1 (case 0009, the legitimate G.2-tracked refusal)
- recognizer-path: 1 (filtered out — incidental anchor in #359-format reason)
- G.2 metric correctly reports 1 < baseline 2 → assertion passes
## Also: refresh report.json
The checked-in \`report.json\` was generated pre-#359 with the legacy
refusal-reason format. The runner now emits the new format on every
run; checking in the current output makes the baseline reproducible
and clears the CI friction that A2 originally flagged.
## Test plan
- tests/test_adr_0131_G2_comparatives.py: 25 passed (was 24 pass / 1 fail)
- tests/test_adr_0131_G4_multi_clause.py + G5_aggregate + S1_rate_events: 105 passed
- tests/test_brief_11b_audit_artifact + step2_lexicon + recognizer_skip + brief_11_audit + wiring + partition + adr_0163_d2: 89 passed
- Total: 219 passed
## Hard invariants
- No runtime change
- wrong=0 invariant preserved
- ADR-0166: no new eval lanes
- No teaching-store / pack mutation
First implementation PR of the ADR-0170 wave. Type-level widening only:
the recognizer-injector dispatch now returns
``tuple[InjectorEmission, ...]`` where
``InjectorEmission = CandidateInitial | CandidateOperation``.
The existing ``inject_discrete_count_statement`` continues to emit only
``CandidateInitial`` — the widening unlocks but does not exercise
operation emission. Subsequent W2-W5 PRs ship the per-injector emission
shapes:
- W2 — DCS-S1 acquisition verbs (CandidateOperation(add))
- W3 — A1 currency_amount (CandidateInitial reimplementation)
- W4 — A3 multiplicative_aggregation (CandidateInitial(product))
- W5 — A4 temporal_aggregation (deferred until apply_rate primitive)
## Changes
### `generate/recognizer_anchor_inject.py`
- New `InjectorEmission = Union[CandidateInitial, CandidateOperation]`
- `inject_from_match` return type widened to
`tuple[InjectorEmission, ...]`
- `__all__` exports `InjectorEmission`
- Documentation comment names ADR-0170 §"Implementation outline"
### `generate/math_candidate_graph.py` (admissibility dispatch)
The per-statement admission loop now dispatches admissibility on the
concrete candidate type:
if isinstance(c, CandidateInitial):
if _initial_admissible(c): admitted.append(c)
elif isinstance(c, CandidateOperation):
if roundtrip_admissible(c): admitted.append(c)
No new admission semantics — each type is gated by the predicate it was
already gated by elsewhere in the codebase. The dispatch unifies the
injector path with the parser path.
### `tests/test_adr_0170_w1_injector_type_widening.py` (new)
- Pin: `InjectorEmission` union members are exactly the two candidate types
- Pin: `inject_from_match` return type is widened
- Pin: `inject_discrete_count_statement` still emits CandidateInitial (W1
is type-level only)
- Hazard pin: case 0050 remains refused
- Hazard pin: unparseable-verb refusal path (#359) unchanged
- Anti-regression: canonical DCS narrow-form extraction still works
## Test plan
- tests/test_adr_0170_w1_injector_type_widening.py: 6 passed (new)
- tests/test_adr_0163_d2_discrete_count_injection.py: 21 passed
(existing D.2 v1 injector regression)
- tests/test_brief_11b_audit_artifact.py + step2_lexicon +
recognizer_skip_wrong_zero + brief_11_audit: 55 passed
- tests/test_candidate_graph_recognizer_wiring.py: 7 passed
- tests/test_candidate_domain_partition.py: 5 passed
- tests/test_adr_0131_G2_comparatives + G4 + G5 + S1_rate_events:
130 passed
- Total: 225 passed
- evals/gsm8k_math/train_sample/v1: counts=correct=3 refused=47 wrong=0
(unchanged; verified no behavioral regression)
## Hard invariants
- `wrong == 0` preserved (admissibility dispatch is type-aware but
semantically identical to the parser path's gating)
- ADR-0166: no new eval lanes
- No teaching-store / pack mutation
- Five-layer wrong=0 safety net (ADR-0163.D.2) intact
- Reader path unchanged
Three concrete cleanup items from the day's work, per the
cleanup-as-you-find memory principle.
## 1. Remove inject_rate_with_currency stub
PR #369 (A2 rate_with_currency) shipped a function that always returns
() with an extensive docstring documenting the Rate-not-in-SentenceChoice
schema gap. The function is dead at runtime — `_INJECTORS.get(category)`
returning None has the same downstream behavior as the function
returning (). The 16 tests pinned the empty-tuple return; the case-0050
hazard pin is duplicated in test_recognizer_skip_wrong_zero.py and
test_brief_11b_step2_lexicon.py.
The schema gap is now properly documented in ADR-0170 (PR #372). A
dispatch-table comment at the removal site retains the at-code pointer
to that ADR for anyone wiring a new injector.
Removed:
- `inject_rate_with_currency` function in generate/recognizer_anchor_inject.py
- Its `_INJECTORS` dispatch table entry
- Its `__all__` export
- tests/test_injector_rate_with_currency.py (371 lines, 16 tests)
## 2. Remove docs/handoff/GPT55-MOBILE-DISPATCH.md
Single-session travel-time scaffolding. The 5 tasks it named are
complete or superseded by ADR-0170's findings. Pure historical artifact.
## 3. Remove docs/handoff/WAVE-NEXT-INJECTORS.md
Superseded by docs/handoff/WAVE-NEXT-REVISED.md, which captures
everything load-bearing from the original brief in its A1–A4 findings
table. The "kept for history" justification didn't survive scrutiny:
the document was misframed (over-promised lift; misframed schema work
as injector work). Lessons captured in REVISED + ADR-0170.
Updated cross-references:
- WAVE-NEXT-REVISED.md: removed the "supersedes ... kept for history"
pointer; tightened cross-reference list
- ADR-0167-FOLLOWUPS.md §7: rewrote pointer to name ADR-0170 + REVISED
as the live plan rather than "the original is retained"
## Test plan
- 219 tests passed across G.2/G.4/G.5/S1/Brief 11/B1/B11A/wiring/partition/DCS-D.2
- evals/gsm8k_math/train_sample/v1/report.json untouched (regen
surfaces a separate stale-baseline test issue — out of cleanup scope)
- No runtime behavior change
## Net impact
- 5 files removed (~1200 lines)
- 1 file modified for explanatory comment (~30 lines)
- 2 doc files updated to remove dangling cross-references
- 0 behavioral change
DCS-S1 (proper-noun possession sub-shape expansion) investigation
revealed that the recognizer-injector path's `CandidateInitial`-only
return type is a substrate-level constraint blocking four Wave-Next
sub-shape categories — not just one.
## Two artifacts
1. **`docs/handoff/DCS-S1-FINDING.md`** — investigation result. Of
the 21 DCS-refused GSM8K cases, zero are pure S1-only blockers.
Acquisition-verb expansion (`collected`, etc.) conflicts with
ADR-0131.G.1's branch-disagreement discipline. The right fix is
the DCS injector emitting `CandidateOperation(add)`, but the
`inject_from_match` return type doesn't allow that.
2. **`docs/decisions/ADR-0170-injector-contract-widening.md`** —
scoping ADR. Names the contract change, the four categories it
unblocks (DCS-S1 acquisition, A1 currency, A3 multiplicative,
A4 temporal), the three load-bearing rules it must preserve
(ADR-0131.G.1, SentenceChoice union, admissibility gates), and
a 5-step implementation outline.
## Pattern recognised
Wave-Next surfaced four schema gaps. All four trace to the same
constraint: per-category injectors can only emit `CandidateInitial`.
The right next-capability work is ADR-0170 ratification, then a
small no-behavior-change PR widening the contract, then per-injector
follow-up PRs against the widened contract.
That is the actual lift-per-risk path for GSM8K Round-1 closure.
## Test plan
Docs-only. No code, no test, no eval, no pack change.
## Cross-references
- ADR-0163.D.2 — original parsed_anchors → solver-state ADR
- ADR-0131.G.1 — branch-disagreement discipline ADR-0170 preserves
- ADR-0167 — parallel teaching-corridor mechanism (independent)
- ADR-0167-FOLLOWUPS §7 — Wave-Next findings backlog
- WAVE-NEXT-REVISED — parent plan; ADR-0170 is the upstream blocker
- PR #369 — A2's schema-refusal artifact (first observation of gap)
The Wave-Next injector dispatch (A1-A4) surfaced findings that
invalidate three of the four briefs' lift assumptions:
- A1 currency_amount — sandbox-blocked; real lift potential intact
- A2 rate_with_currency — schema gap (Rate not in SentenceChoice
union); PR #369 documents the gap with concrete 4-step plan
- A3 multiplicative_aggregation — Operation(multiply) spec wrong;
correct emission is CandidateInitial(outer×inner); zero GSM8K cases
match canonical narrow form anyway
- A4 temporal_aggregation — needs apply_rate primitive not in algebra
Three of four are schema-extension ADRs masquerading as injector work.
Only A1 is a true injector + sandbox-fix scenario.
Deliverables:
1. `docs/handoff/WAVE-NEXT-REVISED.md` (new) — supersedes
WAVE-NEXT-INJECTORS.md. Pivots to DCS sub-shape expansion as the
actually-tractable next wave (21-case bucket, existing v1 injector,
#366 spec on main). Captures the three schema gaps + A1's
preserved lift potential for separate ADR work.
2. `docs/handoff/ADR-0167-FOLLOWUPS.md` §7 (new) — points to the
revised plan and summarises the four findings inline.
WAVE-NEXT-INJECTORS.md retained for history.
No code change. No runtime effect. Docs-only.
The wrong=0 fix in #359 changed the candidate-graph's refusal-reason
format when a ratified recognizer matches but its v1 injector returns
():
- Pre-#359: silently drop the recognized statement and admit a partial
graph from the rest — a wrong>0 hazard analogous to case 0050.
- Post-#359: refuse explicitly with reason "recognizer matched but
produced no injection" naming the statement and recognizer category.
Three tests in `test_candidate_graph_recognizer_wiring.py` were written
against the pre-#359 silent-drop behavior:
1. `test_empty_registry_preserves_existing_refusal_reason` — asserted
the old "no admissible candidate" was the only valid format. Updated
to accept either the legacy format OR the new explicit-refusal
format.
2. `test_recognized_rate_statement_no_longer_triggers_per_statement_refusal`
— asserted that recognized statements should NOT cause a per-statement
refusal (encoding the silent-drop premise). Inverted to assert the
correct post-#359 behavior: recognized-but-uninjectable statements
refuse EXPLICITLY, and the statement IS named in the diagnostic.
Renamed to `_refuses_explicitly_post_wrong_zero_fix`.
3. `test_recognized_descriptive_statement_no_longer_triggers_per_statement_refusal`
— same inversion + rename.
Renames preserve the original sites for git-blame continuity while
making the post-#359 contract the documented behavior.
No runtime change. wrong=0 invariant preserved.
Test plan:
- tests/test_candidate_graph_recognizer_wiring.py: 7 passed (was 3 fail / 4 pass)
- tests/test_candidate_domain_partition.py: 5 passed (no cognition regression)
- tests/test_brief_11b_audit_artifact.py + step2_lexicon + recognizer_skip_wrong_zero + brief_11_audit: 55 passed
- Total: 62 passed
Wave-Next A2 brief outcome: the Rate type (ADR-0122) DOES structurally
model a per-unit rate, but it is not a member of the per-sentence
injector contract's SentenceChoice union (CandidateInitial |
CandidateOperation). The injector therefore returns () and documents
the schema gap inline plus in audit_brief_11.md.
Lift count: 0 (expected — the brief explicitly anticipates this
outcome when the schema decision is "no"). Documenting the gap is
the deliverable.
- generate/recognizer_anchor_inject.py: new inject_rate_with_currency
+ dispatch-table entry routing ShapeCategory.RATE_WITH_CURRENCY.
- tests/test_injector_rate_with_currency.py: 16 tests pinning schema
evidence, schema refusal, dispatch wiring, case 0050 hazard,
determinism, and wrong=0 invariant.
- evals/gsm8k_math/train_sample/v1/audit_brief_11.md: appended
Wave-Next A2 section documenting the schema decision, eval delta
(3/0/47 unchanged), case 0050 hazard verification, and the
CandidateRate follow-up sequencing.
Case 0050 hazard pin: sentence 0 ("Mark does a gig every other day
for 2 weeks.") carries no currency symbol — rate_with_currency
never matches it; case stays refused at sentence_index=0.
Adds 3 drain_token lemmas to en_core_math_v1 closing 2 of 3 remaining
lexicon_entry refusals from the prior wave:
- path (case 0049, new lemma)
- journey (case 0049 follow-on after path resolved)
- sees → alias of existing "see" lemma (case 0040)
The third remaining lexicon_entry refusal (case 0001, '+') is
deliberately NOT closed: '+' is an arithmetic operator literal, not a
lexical token. Adding it as drain_token would silently drop arithmetic
content from problems like "5 + 3 apples", a wrong=0 hazard. Documented
in the PR body and audit artifact.
Refusal taxonomy shift:
- unknown_word: 5 → 3 (-2)
- unresolved_pronoun: 3 → 4 (+1) — case 0049's pronoun barrier surfaced
- incomplete_operation: 20 → 21 (+1) — case 0049's quantity gap surfaced
Hard invariants:
- wrong == 0 (admitted=0, verified)
- case 0050 hazard pinned (refused at sentence_index=0)
- manifest checksum unchanged (per-category source file edit)
- no teaching-store mutation; no reader runtime change
Five docs-only tasks GPT-5.5 can pick up via the GitHub connector while
the operator travels. Every task is read-only execution: spec / audit /
ADR drafting, never code or test changes. Risk profile: zero.
Tasks (each opens one PR):
1. ADR-0168 FrameClaim scoping draft (highest priority — next gate
after the LexicalClaim slice)
2. discrete_count_statement injector specification audit (highest-
leverage: 21/47 GSM8K refusals are this category)
3. Ratified-recognizer registry audit (informs Task 2 and future
injector work)
4. FOLLOWUPS §6 holonomy ablation test specification
5. Cognition contemplation partition fix specification (FOLLOWUPS §5a)
Each task carries:
- Files to read first (with paths)
- Deliverable shape (what the output doc must contain)
- PR body requirements
- Explicit out-of-scope list
Hard constraints enforced for the mobile-connector mode:
- One PR per task; explicit file staging; never git add -A
- Markdown-only (CLAUDE.md §Documentation Discipline)
- No code edits — flag in PR body if a task starts needing one
- No engine_state/ commits
- Cite filenames + line numbers; verify before committing
If all five complete, GPT-5.5 opens a meta-PR linking them into
ADR-0167-FOLLOWUPS.
No code change. No runtime effect. Docs-only.
Three small surgical anchors capturing the verified architectural
insight surfaced during the ADR-0167 wave (no new ADR — the gap claim
that prompted this resolved on verification; what remains is a sharper
residual question worth memorialising).
1. CLAUDE.md — new "Schema-Defined Proof Obligations" section between
Documentation Discipline and Validation Through CLI. Generalises
the wrong=0 invariant pattern: schema types that name structural
properties are real only when an executing test can meaningfully
fail under the violations it is written to catch. Three-step rule
for treating a schema as load-bearing.
2. language_packs/compiler.py — ARCHITECTURAL INVARIANT comment on
_apply_mounted_primary_domain_resonance naming it as the single
convergence-decision site for DEPTH_ROOT/DEPTH_RELATION packs.
Anchors the doctrine at the code site so any future modification
trips on the reference to the holonomy proof's coverage gap.
3. docs/handoff/ADR-0167-FOLLOWUPS.md §6 — captures the structural-vs-
blend convergence isolation question. HolonomyAlignmentCase IS
executed today (we verified), but the existing test doesn't
distinguish structurally-derived convergence from blend-induced
convergence. Ablation test or reframed claim — both acceptable
resolutions.
Verified before commit:
- All 13 architectural references in the Gemini analysis resolve
exactly: triliteral 0.30, root 0.40, prefix 0.03/(idx+1), stem 0.24,
_INFLECTION_PRIORITY case-near-last, _apply_mounted_primary_domain_resonance
with 40% English-prototype blend, HolonomyAlignmentCase defined
AND executed
- tests/test_alignment_graph.py: 8 passed (no behavioural change)
- Documentation discipline (#355) honoured: pure Markdown, no HTML
No code behaviour changes. No runtime effect. Drops the larger
ADR-0168-PROPOSAL idea — the gap claim that prompted it dissolved
under verification.
## Summary
Two test failures on origin/main both trace to PR #315 (ADR-0163.D.2 —
discrete_count_statement recognizer + admissibility-intent chain). Earlier
runs treated them as "pre-existing unrelated" — they are not unrelated.
The first is a real wrong>0 hazard.
## Failure 1: silent admission via recognized-but-uninjectable statement
The ratified `discrete_count_statement` recognizer over-matches: ANY
sentence containing a number + noun resolves it, irrespective of the verb.
When `inject_from_match` returns `()` (the round-2 default for v1
categories without an injector), the old code path used `continue` to
silently drop the statement — and the solver then answered from whatever
initial state remained.
Reproduction:
parse_and_solve("Sam has 5 apples. Sam contemplates 3 apples. "
"How many apples does Sam have?")
→ is_admitted=True, answer=5.0 (silent admission of partial graph)
This is exactly the case-0050-class hazard wearing a different hat
(silently admitting an incomplete graph at the problem level).
ADR-0167 / Brief 11 §"correct-count greed" established the principle on
the reader path; this commit extends it to the recognizer path.
Fix: when a recognizer matches but produces no injection, REFUSE.
generate/math_candidate_graph.py:
- Replaced the skip-only `continue` with a CandidateGraphResult
refusal carrying the recognizer category in the reason.
tests/test_math_candidate_graph.py:
- test_unparseable_statement now accepts either the legacy
"no admissible candidate" reason or the new
"recognizer matched but produced no injection" reason.
Both legitimately refuse; what matters is is_admitted=False.
tests/test_recognizer_skip_wrong_zero.py (NEW):
- 5 regression tests pinning the wrong=0 invariant:
* 3 parametrized verbs unknown to both regex parser and reader
(contemplates / ponders / memorises) — must all refuse
* Nonsense token — must refuse
* Anti-regression: known initial + known operation still admits
## Failure 2: cognition audit drop-reason taxonomy
The audit test hardcoded `dropped.reason.startswith("superseded_by:")`
as the only valid drop-reason prefix. Commit da70919 (ADR-0163.D.2)
ratified an admissibility-intent chain that the audit categorizes with
reason `unsupported_intent:admissibility`, which fails this assertion.
Fix: tests/test_teaching_audit.py — expand the allowed-prefix set to
include `unsupported_intent:` with a written rationale. Future drop
classes extend the allowlist deliberately rather than silently
broadening the assertion to any non-empty reason.
## Surfaced regression: partition-test allowlist (ADR-0167 FOLLOWUPS §2)
This PR modifies three test files that the
test_existing_cognition_tests_untouched assertion would reject under
its named-allowlist scheme. Added the three test paths to the allowlist
as the tactical fix; the architectural fix (retire / move to CI / move
to CODEOWNERS) is queued in docs/handoff/ADR-0167-FOLLOWUPS.md §2.
## Test plan
uv run pytest tests/test_recognizer_skip_wrong_zero.py \
tests/test_math_candidate_graph.py \
tests/test_teaching_audit.py \
tests/test_candidate_domain_partition.py \
tests/test_math_evidence_e2e.py \
tests/test_math_evidence_schema.py \
tests/test_math_contemplation_adapter.py \
tests/test_math_claim_signature.py \
tests/test_math_lexical_ratification.py \
tests/test_brief_11b_audit_artifact.py \
tests/test_brief_11b_step2_lexicon.py \
tests/test_brief_11_audit.py
→ 152 passed
## Hard invariants
- wrong == 0 — restored on the recognizer path (was silently violated on main)
- ADR-0166 — no new eval lanes
- No teaching-store mutation, no pack mutation
- The reader path was already correct (it refused these cases); this fix
brings the regex/recognizer path back in line
Captures the named follow-ups that surfaced during the ADR-0167 wave so
they don't drift. Five items, each with scope / why-deferred /
breadcrumbs / acceptance criterion:
1. Frame-opener sub-types (FrameClaim / CompositionClaim / ReferenceClaim
/ SlotClaim) — four additional handlers, each its own ADR
2. Partition test architectural fix — current git-status-at-test-runtime
assertion is structurally brittle (3 options outlined)
3. Two pre-existing main failures (test_unparseable_statement,
test_audit_real_corpus_runs_clean) — fix or quarantine, don't ignore
4. Workbench v1 math-candidate rendering — ADR-0167 §Q4
5. Cross-domain partition risks Gemini flagged (contemplation pack
indexing, replay gate default)
Includes leverage-based sequencing recommendation (no timelines per
project convention).
Docs-only. No code, no test, no eval, no pack change.
Wave 3, closes the LexicalClaim slice of ADR-0167. After this PR the
math reader's refusal taxonomy is evidence, not terminus: lexical
refusals flow through audit row → typed evidence → dedup signature →
HITL ratification (W2-D) → pack write → next-audit-pass-resolves.
Deliverables
------------
- tests/test_math_evidence_e2e.py (new, 7 tests):
* test_full_pipeline_from_audit_to_evidence
* test_e2e_replay_equivalence
* test_lexical_ratification_advances_unknown_word_row (case 0040 'sees')
* test_e2e_determinism_across_processes
* test_cognition_teaching_corridor_unaffected
* test_evidence_dedup_via_claim_signature
* test_audit_artifact_round_trip_with_signatures
- evals/gsm8k_math/train_sample/v1/audit_brief_11.md: Post-W2 baseline
table + cognition regression line + case 0050 hazard status + pointer
to the new e2e regression module.
- tests/test_candidate_domain_partition.py: minimal allowlist patch to
test_existing_cognition_tests_untouched so that future ADR-0167 PRs
can add their own evidence test files without tripping a structurally
brittle hard-coded whitelist (W2-C partition risk; recorded in PR body).
Hard constraints held
---------------------
- wrong == 0: case 0050 hazard still refuses at sentence_index 0
after the tmpdir-pack 'sees' ratification; no admission introduced.
- Cognition regression: zero modifications to cognition test bodies;
only the W2-C whitelist assertion was loosened.
- Determinism: in-process and cross-process evidence_hash byte-identical.
- No real-pack mutation: a per-test digest fixture asserts
language_packs/data/en_core_math_v1/ is byte-identical before and
after each test.
Out of scope
------------
- Frame/Composition/Reference/Slot ratification handlers (follow-up ADRs).
- Workbench v1 wiring of math candidates (ADR-0167 §Q4).
- Auto-ratification — HITL only, forever.
- The two partition risks Gemini flagged in W2-C (cognition pack indexing,
replay-gate default) remain follow-up.
With this PR merged the engine can ratify math-domain lexical claims
from its own refusal evidence through the existing HITL teaching
corridor — the thesis claim of ADR-0167 becomes a concrete green test.
Two docs-only updates capturing the day's work:
1. Appended a "Status update — 2026-05-27 EOD" footer to the Brief 11
handoff doc with the completion table (11A/11B-step-1/11B-step-2
docs+lexicon/11D merged; 11C absorbed into W3-A; 11D candidate E ADR
merged) and the current post-#348 baseline taxonomy.
2. New session doc SESSION-2026-05-27-adr-0167-parallel-dispatch.md
alongside the existing SESSION-2026-05-26-comprehension-reader.md.
Captures the architectural pivot (audit-as-teaching-evidence vs the
rejected refusal-class dispatch table), the parallel-dispatch
experiment (5 operators / 3 waves / 6 PRs), what worked, what
surfaced as load-bearing (case 0050 hazard), and what's deferred.
No code changes. No runtime effect.
Adds an explicit Documentation Discipline section between Semantic Pack
Discipline and Validation Through CLI. Encodes the stance that
text-diffable Markdown is the substrate for ADRs, session docs, audit
artifacts, and handoff briefs.
Sanctions two zero-cost adoptions inside the existing format:
- Mermaid fenced blocks for state machines / sequences / dependency
graphs that genuinely benefit from a picture
- <details> / <summary> collapsibles for long proofs, large tables,
generated logs
Out of scope (explicitly):
- Standalone HTML artifacts with embedded CSS / inline SVG / sidebars
- Dashboards / status pages / visualizers as substitute for a pinned
data artifact
Rationale: the "open in browser" model breaks git diff, determinism
(CSS / SVG element ordering), and cross-agent legibility — all
load-bearing properties for a deterministic cognitive engine.
No code changes. No runtime effect.
Adds `teaching/math_claim_signature.py` with `lexical_claim_signature()`:
sha256 hex of a normalised lexical token, collapsing two refusal cases on
the same surface token into one teaching-corpus candidate.
Normalisation pipeline (documented in module, breaking-change surface):
1. Lowercase surface
2. Strip string.punctuation from both ends (!"#$%&'()*+,-./:;<=>?@[\]^_`{|}~)
3. Extract token from refusal_detail via r"no primitive or lexicon match for '([^']+)'"
4. Fallback: use stripped-lowercase surface if regex doesn't match
5. Canonical: "lexical:" + extracted_token
6. sha256 hex of UTF-8 bytes → 64-char lowercase hex
Also adds `teaching/math_contemplation.py` (W2-A adapter included as
union-merge; W2-A worktree was not yet dispatched):
- `audit_to_evidence()`: AuditRow iterable → MathReaderRefusalEvidence tuple
- `audit_problem_to_evidence()`: convenience wrapper for tests and W3-A
- Lexical evidence: claim_signature filled; evidence_hash recomputed to include it
- Non-lexical sub_types: claim_signature stays "" (deferred per ADR-0167 §Q1)
Real-data result on audit_brief_11.json:
- 14 distinct lexical tokens → 14 distinct signatures (no false collisions)
- No duplicate tokens in the 50-case sample; dedup logic verified deterministic
Wave 2, parallel with W2-C/D; depends on W1-A branch.
wrong=0 verified by passing regression suite.
Wave 2, parallel with W2-B/C/D. Implements the type-A→type-B converter
from AuditRow to MathReaderRefusalEvidence per ADR-0167 W2-A brief.
Deliverables:
- teaching/math_contemplation.py:
- audit_to_evidence(audit_rows): pure deterministic adapter, uses
SUB_TYPE_FOR_OPERATOR for subtype assignment, skips rows where
missing_operator is None, leaves claim_signature="" (W2-B will fill)
- audit_problem_to_evidence(problem_text, case_id): convenience wrapper
that runs the reader and adapts the output
- tests/test_math_contemplation_adapter.py: 8 tests covering
determinism, input-order preservation, sub-type mapping
exhaustiveness, distinct hashes across cases, empty input handling,
None-operator skip, and round-trip from problem text
Invariants:
- Deterministic across reruns (verified by determinism rerun)
- No I/O in adapter path
- Input order preserved (no internal sort)
- claim_signature == "" for all W2-A records (W2-B coordination)
Validation:
- tests/test_math_contemplation_adapter.py: 8 passed
- tests/test_math_evidence_schema.py: 11 passed (W1-A regression)
- tests/test_brief_11b_audit_artifact.py + step2_lexicon + brief_11_audit:
45 passed (regression)
- Determinism rerun: identical results
