Five new wiring-debt entries from L4 (recognition) and L5
(cognition pipeline) audits:
- W-010 — L4 recognition bypasses L3 vocabulary (operator decision:
intentional token-level or wire VocabManifold consumption).
- W-011 — Typed recognition refusals dropped at pipeline boundary
(mechanical fix, small; closes recognition audit-trail gap).
- W-012 — InnerLoopExhaustion not caught in ChatRuntime.chat()
(mechanical fix, small; sibling of W-011; closes ADR-0142 debt #3).
- W-013 — core/cognition/explain.py dormant (operator decision:
wire, relocate, or delete).
- W-014 — core/cognition/provenance.py partially live, evals-only
(operator decision: lighter version of W-013).
Reordered suggested next-ADR sequence to lead with mechanical quick
wins (W-011, W-012, W-004) before operator-decision items (W-006,
W-013/14, W-010), before second-order changes (W-005), before the
big L10 unit (W-008). Reasoning documented inline: early measurable
progress, no architectural risk, demonstrates audit-to-fix loop
closes.
Updated dependency graph to show the three independent groups
(mechanical, operator-decision, L10-gated chain).
L0-L5 audited; L6-L9 pending. Ratchet stays append-only; v2 marker
in title and "L0-L5 + L10 scope" in subtitle.
The test asserts ledger status is in {reasoning-capable, audit-passed},
but ADR-0120 (PR #195, dec98ea) promoted mathematics_logic to expert
without updating this test. Test was failing on main as part of the
full suite (surfaced during PR #239 verification: Codex's versor-
threshold fix ran full suite, found this unrelated failure).
Test's docstring explicitly states the invariant is reasoning_capable
holding while "the status string moves with later promotions" — so
the fix is to extend the expected tuple, not to revert the promotion.
Cleanup per feedback-cleanup-as-you-find: the orphan was a follow-on
of ADR-0120 that should have shipped with the promotion PR.
Verified: 14/14 passing locally.
Verdict: PARTIAL.
Updates the substrate liveness registry with the L1 field substrate audit, including ADR enumeration, module/caller mapping, suite lane evidence, cross-layer contract findings, and downstream notes.
Cleanup: none; no unambiguously dead L1 code was found. Test-only helpers and pulse-only field operators are documented for review instead of deleted.
Verification: python3 -m core.cli test --suite smoke -q; python3 -m core.cli test --suite algebra -q; python3 -m core.cli test --suite pulse -q; python3 scripts/verify_lane_shas.py.
Names the missing prerequisite that recognizer-storage v2 and
substrate-liveness-audit v2 both flagged: the process shape in which
the engine accumulates capability over its lifetime, survives reboot
as recovery, and presents a narrow async HITL ratification entrypoint.
Cross-reference discipline applied up-front (per
feedback-adr-cross-reference-discipline memory entry — fourth
iteration; this time grep BEFORE draft). Existing ADRs identified
as load-bearing: ADR-0040 (telemetry sink, persistent audit trail),
ADR-0041/0042 (operator surface + audit-tour), ADR-0055 (four-tier
memory: T1 session vault → T4 ratified packs; explicitly names
"what survives across all sessions and reboots"), ADR-0056/0080
(contemplation loop), ADR-0057 (proposal review machinery this
scope must build on), ADR-0014 (vault promotion gate, currently
dormant — L2 audit will verify), ADR-0027/0029/0033 (identity/
safety/ethics packs, currently startup-loaded).
Current state honestly mapped: every entry is a one-shot CLI
command via argparse in core/cli.py; ChatRuntime is per-invocation;
no long-lived process exists.
Four sub-questions framed:
1. Process shape — long-lived daemon vs. hybrid (state externalized
+ restored) vs. one-shot CLI with audit-trail-as-lifetime.
2. State partitioning — session-state (ephemeral) / engine-state
(live, persistent across reboot) / substrate-state (cold,
persistent).
3. Reboot recovery — what verifies, what reloads vs. rederives, what
records.
4. HITL async entrypoint — queue shape, backpressure, operator
interaction model.
Cross-references shelved project-engine-identity-candidate (DNA-
analog EngineIdentity) as potential primitive if sub-question 3
demands cross-reboot identity verification. Does NOT un-shelve it;
flags trigger.
Explicit rejections: database persistence (per ADR-0055 north-star);
network primary entrypoint (per user-circumstances memory entry,
always-on-internet unsafe to assume); multi-tenant; re-architecting
ChatRuntime.
Constraints inherited from CLAUDE.md: deterministic replay, no
hidden state, HITL is narrow entrypoint, reboot is recovery not
control flow, append-only artifacts stay append-only, no drift
repair / hot-path normalization.
This is a scope, not a decision. Spike/ADR decides; audit findings
(L4-L9) inform.
First per-layer audit of the substrate-liveness program. Establishes the
registry shape and standard of evidence for subsequent layers.
L0 (algebra primitives) is foundation; verdict CLOSED:
- 4 ADRs in scope (ADR-0001 versor invariant, ADR-0003 coordinate
dissolution, ADR-0004 rotor as operator, ADR-0009 compositional
physics).
- 6 modules (versor, rotor, cga, cl41, holonomy, backend); every
module has at least 2 live-import sites outside the package and
outside tests (38 distinct caller files overall).
- core test --suite algebra exercises every L0 module: 82 passed, 50
skipped (Rust-parity tests, Python-only env — not a closure gap).
- Cross-layer contract pass 1 (mechanical): every exposed symbol has
at least one downstream consumer.
- Cross-layer contract pass 2 (semantic): versor_condition < 1e-6
invariant is measured per turn (core/cognition/trace.py:34), folded
into deterministic trace payload, surfaced to operator via CLI, and
gated at the eval boundary (evals/cognition/runner.py:60). Matches
CLAUDE.md discipline of "measure and surface, don't weaken."
No cleanup performed — no dead code, no redundant modules, no
orphaned tests found at L0. Foundation is honest.
One scope-hypothesis correction: layering table cited "algebra/backend/"
(directory); reality is "algebra/backend.py" (file). Hypothesis drift,
recorded for amendment if it matters elsewhere.
Three forward-pointing notes left for downstream auditors:
- L1 should verify field propagation correctness is tested
independently of L5's downstream versor_condition measurement.
- L2 should verify vault honors exact-CGA-recall end-to-end, not just
at the algebra layer.
- ADR-0020 (Rust parity) is cross-cutting; audit when Rust integration
is live rather than at any single layer.
Format established for subsequent per-layer commits. Audit progress
table in registry root tracks pending layers; resume-after-interruption
is "look at the progress table, start with the first pending layer."
* docs(audit): scope substrate liveness audit (system-of-systems closure)
The recognizer-storage v1→v2 revision surfaced a pattern: CORE
contains ~140 ADRs, many marked Implemented, but several have
spec-in-code that nothing live calls (e.g., VaultPromotionPolicy in
core/physics/learning.py — imported by no module outside its package).
The engine today executes a subset of its own design.
Per the operator's system-of-systems framing (human body / universe /
ecosystem: subsystems achieve closure together; a half-built layer
degrades the whole organism silently): this scope defines a layered
audit that walks from the foundation outward to identify, per ADR
and per module, which subsystems are closed (designed + wired +
exercised + cross-layer consistent), which are partial, and which
are open.
The audit method is mechanical: grep + caller-trace + end-to-end test
verification + cross-layer contract check. Two reviewers running the
audit should produce identical verdicts. No refactoring, no new ADRs,
no subjective judgment — just evidence.
The output is two artifacts: a closure registry (per-layer, per-ADR
verdicts with evidence) and a ratchet plan (wiring sequence in
dependency order). Both append-only / revisable; both committed to
the repo as audit artifacts.
First-pass layering (L0 algebra primitives → L11 forever-running
engine, with L10 runtime model named as the missing prerequisite)
is a hypothesis the audit will refine. Layers L0–L3 are expected to
be closed (foundation); L4–L9 are expected to be partial; L10–L11
are explicitly open and depend on the audit + the runtime-model
scope.
Applies feedback-adr-cross-reference-discipline (the memory entry
this revision flagged): explicit cross-references to ADR-0006/0014/
0055/0056/0057/0142/0143/0144 and the existing scope docs.
This is a scope, not an audit. Audit deliverables (registry, ratchet)
are separate work.
* docs(audit): revise substrate-liveness-audit scope to v2 (self-review fixes)
Self-review surfaced two HIGH, three MEDIUM gaps in v1. Notably,
v1 of the scope that creates cross-reference discipline still
committed the documented mistake — third consecutive iteration of
the same failure mode in one session (recognizer-storage v1
substrate overclaim → recognizer-storage v2 drop-off invention →
audit-scope v1 ADR range mis-grouping). New "Self-review
acknowledgment" section records the pattern's durability and
states the structural mitigation: the audit's mechanical
deliverables make the discipline impossible to skip silently,
which is more rigorous than the memory entry alone.
HIGH-1 — ADR range mis-grouping. v1 layering table listed
"ADR-0055..0064" as L7 (teaching loop); verification showed
ADR-0058-0064 are predominantly L6 (surface composition,
correction telemetry, cross-pack resolution). Fixed L7 to cite
only ADR-0057; added explicit note that ADR-range citations
are starting points and the audit's first act per layer is
re-enumeration.
HIGH-2 — Audit tractability buried in risks. ~140 ADRs requires
structural handling, not just a risk warning. Promoted "per-layer
commits + per-layer handoff to subagents + progress tracking in
registry + optional per-layer file splitting" to a first-class
Step 0 in the audit method. The audit is explicitly framed as the
archetypal parallel-agent handoff candidate.
MEDIUM-1 — Expected-status column anchored the auditor. v1's
table had my predictions ("Closed (foundation)", "Live but
session-bounded"). Removed; replaced with a "Where to look first"
column. Explicit note: "No expected-status column intentionally
— predictions are the failure mode this scope was meant to
prevent."
MEDIUM-2 — "End-to-end test" criterion maps awkwardly onto CORE's
suite-lane organization. Reframed Step 4 to "Identify the
exercising suite lane" with concrete `core test --suite {…}` /
`core eval …` invocations. A module whose only test coverage is
in `tests/` files not reached by any suite lane is a closure gap.
MEDIUM-3 — Cross-layer contract check was hand-wavy. Made
Step 5 explicitly two-pass: mechanical (grep for at least one
consumer per exposed field/method) carries full verdict authority;
judgment-required semantic mismatches are flagged for operator
review rather than verdicted mechanically.
LOW fixes: softened "two reviewers identical" claim; L10/L11
explicitly marked not-audit-targets; per-layer file splitting
flagged as auditor's choice; closure-criteria item 4 wording
aligned with new Step 4.
Frontmatter status bumped to "Draft v2"; date line records
revision provenance.
* docs(recognition): scope recognizer storage against existing thermodynamic substrate
Two changes:
1. New scope: docs/decisions/recognizer-storage-scope.md (draft v1).
Reframes the recognizer-storage question against ADR-0006 (field
energy operator) and ADR-0014 (vault promotion policy) — the
thawed ↔ crystallized lattice already implemented under
core/physics/{energy,learning}.py. The three-candidate framing
(pack / vault / substrate) was drafted without acknowledging this
substrate; once it's in view, the storage question collapses to:
how does a derived recognizer participate in the existing
excitation / cooling / coherence-settling / promotion / re-thaw
dynamics, and what extension is needed for HITL-gated drop-off.
Names three measurements that need definition (recognizer
excitation, coherence residual, promotion criteria), one sibling
ADR (drop-off / deprecation), and the forever-running runtime
principle. Explicitly rejects pack-as-recognizer-container,
vault-without-substrate-reframe, per-session re-derivation, and
approximate match.
2. Amendment to docs/decisions/teaching-derived-recognition-scope.md.
Appends a "Connection to existing thermodynamic substrate" section
acknowledging the three-candidate omission, citing ADR-0006/0014,
and pointing forward to the recognizer-storage scope. The original
framing is preserved for history.
Neither doc proposes a decision. Both define the question.
Process note: the omission this corrects motivated saving a project
memory (feedback-adr-cross-reference-discipline) to prevent
independent reinvention in future ADR work.
* docs(recognition): revise recognizer-storage scope to v2 (self-review fixes)
Self-review surfaced two HIGH and two MEDIUM gaps in v1.
HIGH-1 — Substrate liveness overclaim. v1 described the entire
field-energy + vault-promotion lattice as live. Verified: only the
energy half is wired (FieldEnergyOperator called by ingest/gate.py,
field/propagate.py, language_packs/compiler.py); core/physics/learning.py
(VaultPromotionPolicy) is imported by no module outside core/physics/.
Added "Substrate liveness audit" subsection that honestly accounts for
which pieces are live vs. dormant, and explicitly states that the
recognizer-storage ADR must deliver both wiring the dormant promotion
path AND extending it for recognizers as content type.
HIGH-2 — Meta-irony: v1's drop-off section invented a HITL ratification
path without cross-referencing ADR-0057's existing teaching-chain
review/replay/append-only-log machinery — exactly the failure mode the
new feedback-adr-cross-reference-discipline memory was meant to prevent.
Added explicit cross-reference: drop-off reuses ADR-0057's review-and-log
plumbing; load-bearing originality is the recency-driven trigger and
the (non-replay-equivalence) gate. Plus HITL latency named as a
load-bearing architectural constraint, not just queue plumbing.
MEDIUM-1 — "Forever-running runtime" was framed as an assumption. Honest
status: current runtime is session-bounded (core chat is a CLI; each
invocation builds a fresh ChatRuntime; no long-lived process). Reframed
as a prerequisite (own scope, gates this one), not an assumption.
MEDIUM-2 — "Substrate-resident destination" was named but never sketched,
making the IOU concrete-free. Added a one-paragraph sketch (recognizer
as versor; recognizer as null-cone region) to keep the destination
honest. Explicitly illustrative, not committed.
LOW corrections inline: recognizer-excitation temporal-direction note;
0.05 residual threshold marked as default; cold-path latency reframed
as a general vault concern recognizers inherit rather than introduce.
Frontmatter status bumped to "Draft v2"; date line records revision
provenance.
When a pinned lane drifts, the script prints actual/expected SHAs but
gives no guidance. Authors then have to look up that --update exists
and that CLAIMS.md needs regenerating alongside.
Adds a remediation block printed only on mismatch, listing the most
common drift sources (core/cognition/result.py, chat/runtime.py,
generate/realizer.py, capability registries) and the two commands
needed to re-pin: --update + generate_claims.py.
Why this is the right scope: branch protection now blocks merge on
red lane-shas CI (enabled 2026-05-24), so the remaining gap is
discoverability — telling authors what to do, not enforcing that
they do it. A one-line message change carries that signal without
adding hooks, templates, or infrastructure.
No behavior change on success.
566-line scope document defining the next recognition phase after
ADR-0144's epistemic carrier. Not a decision — defines the question
the follow-up ADR must answer.
v2 reframes from v1:
- feature-bundle outputs whose type emerges from lifted features (not
pre-decided proposition categories)
- evidence-bound lifts with span pointers + contradiction detection
for adversarial robustness
- multi-resolution decoding (chunked-first / word-by-word fallback)
Companion to docs/decisions/proposition-graph-scope.md (shipped with
ADR-0144). Anchored to the decoding-not-generating thesis.
Three lane SHA pins drifted because intentional surface/serialization
changes shipped without re-running scripts/verify_lane_shas.py --update.
Bisect attributing the drift:
- demo_composition + public_demo broke at 5cad0a4 (#118 ADR-0110
mathematics_logic → expert_demo) — the demos enumerate the expert set.
- demo_composition drifted a second time at ab4c7cb (#220 Phase 3
state tagging spine) — additional epistemic fields shifted the surface.
- domain_contract_validation broke at a45eab1 (#219 Phase 2 epistemic
bug repairs) — normative/epistemic field shape changed.
The in-tree canonical report for fabrication_control_summary was also
stale vs. its (correct) pin; refreshed here for byte-alignment.
After this commit: 7/7 lanes match pinned SHAs; verify_lane_shas.py
runs green locally and in CI.
Followup (separate PR): hook/template guard so future PRs that touch
core/cognition/result.py, chat/runtime.py, or capability registries
re-run --update before merge.
Implements the PropositionGraph epistemic carrier (ADR-0144):
recognition/carrier.py — EpistemicTransition, EpistemicNode, EpistemicGraph.
Frozen, JSON-serializable, byte-deterministic. EpistemicNode wraps a
RecognitionOutcome with an append-only provenance chain; epistemic_state
property tracks last transition's to_state or outcome.state when empty.
recognition/connector.py — epistemic_node_to_graph_node(). Maps an admitted
EpistemicNode's FeatureBundle (agent/relation/count/unit) to a GraphNode
for the generation-side articulation planner.
CognitiveTurnPipeline gains a recognizer: DerivedRecognizer | None param
(default None — all existing callers unaffected). When attached, run()
calls recognize() at the top of every turn and wraps admitted outcomes in
an EpistemicGraph. CognitiveTurnResult.epistemic_graph carries it.
RuntimeConfig.recognition_grounded_graph: bool = False — opt-in flag that
replaces the intent-derived PropositionGraph with one derived from the
admitted EpistemicNode via the connector.
RatificationOutcome gains three specific PASSTHROUGH sub-values
(PASSTHROUGH_NO_FIELD / NO_VOCAB / NO_VERSOR) for _ratify_intent
observability (ADR-0142 debt 1). All normalise to "passthrough" before
trace_hash so pre-ADR-0144 hashes are byte-identical.
24/24 acceptance tests pass; 67/67 smoke tests pass; no regressions.
* feat(epistemic): populate normative_detail on TurnEvent and ChatResponse
Adds normative_detail_from_verdicts() to core.epistemic_state and wires
it into both the stub and main ChatResponse/TurnEvent construction sites.
The field carries a sorted comma-separated list of violated boundary or
commitment IDs when normative clearance is VIOLATED or SUPPRESSED; empty
string otherwise.
* docs(ADR-0142): ratify epistemic state taxonomy — 14-state vocabulary + normative clearance axis
Formalises the six-subsystem Framing 1 audit findings into a first-class
decision. Accepts the 14-state taxonomy and companion 4-value normative
clearance axis. Documents Phase 3 deliverables already landed and defers
structured provenance + cross-subsystem transition machinery to ADR-0144.
* feat(recognition): output contract + ADR-0143
Adds recognition/outcome.py: RecognitionOutcome, FeatureBundle,
BoundFeature, EvidenceSpan, NegativeEvidence, the three typed refusal
classes (ShapeRefusal, FeatureEvidenceRefusal, FeatureConsistencyRefusal),
and RecognitionProvenance. Frozen dataclasses, JSON-serializable,
byte-deterministic invariants enforced in __post_init__.
ADR-0143 commits to Mechanism D (multi-resolution anti-unification over
token sequences) and defines the two-phase acceptance test.
* feat(recognition): derive phase1 anti-unifier
Adds recognition/outcome.py: RecognitionOutcome, FeatureBundle,
BoundFeature, EvidenceSpan, NegativeEvidence, the three typed refusal
classes (ShapeRefusal, FeatureEvidenceRefusal, FeatureConsistencyRefusal),
and RecognitionProvenance. Frozen dataclasses, JSON-serializable,
byte-deterministic invariants enforced in __post_init__.
ADR-0143 commits to Mechanism D (multi-resolution anti-unification over
token sequences) and defines the two-phase acceptance test.
* feat(epistemic): populate normative_detail on TurnEvent and ChatResponse
Adds normative_detail_from_verdicts() to core.epistemic_state and wires
it into both the stub and main ChatResponse/TurnEvent construction sites.
The field carries a sorted comma-separated list of violated boundary or
commitment IDs when normative clearance is VIOLATED or SUPPRESSED; empty
string otherwise.
* docs(ADR-0142): ratify epistemic state taxonomy — 14-state vocabulary + normative clearance axis
Formalises the six-subsystem Framing 1 audit findings into a first-class
decision. Accepts the 14-state taxonomy and companion 4-value normative
clearance axis. Documents Phase 3 deliverables already landed and defers
structured provenance + cross-subsystem transition machinery to ADR-0144.
* feat(epistemic): add first-class state enums
* feat(epistemic): tag TurnEvent with state axes
* feat(epistemic): serialize turn state axes
* feat(packs): tag curated and inferred unit entries
* feat(epistemic): expose word-level state on manifold
* feat(epistemic): expose vault status mapping
* feat(epistemic): preserve pack entry states through compiler
* test(epistemic): cover phase 3 state tagging spine
* feat(runtime): wire epistemic_state + normative_clearance into ChatResponse
Add first-class epistemic_state and normative_clearance fields to
ChatResponse (defaulting to "undetermined"/"unassessable" for backward
compat). Import epistemic_state_for_grounding_source and
clearance_from_verdicts into chat/runtime.py and populate both fields on
the stub path (TurnEvent + ChatResponse) and the main path (TurnEvent +
ChatResponse). Fix the test fixture to use "euro per hour" (a genuinely
composed unit) instead of "dollars per hour" which is a curated lexicon
entry and returns DECODED, not INFERRED.
* test(cognition): update term_capture_rate baseline from 0.9167 to 1.0
unknown_logos_019 now correctly surfaces "light" as a pack-resident
token near the logos versor — producing term_capture_rate 1.0 on both
main and Phase 3. The 0.9167 pin was stale relative to a surface change
already on main; Phase 3 did not introduce this shift.
* docs(epistemic-scope): mark Framing 1 audit complete across all six subsystems
Teaching pipeline (47 pts, 0 new states), cognition pipeline (42 pts,
0 new states, 1 EPISTEMIC_STATE_NEEDED placeholder), and chat runtime
(47 pts, 0 new states, 6 provenance gaps) audits complete. Taxonomy
confirmed stable; remaining work is implementation debt and provenance,
not taxonomy extension.
* feat(epistemic): add first-class state enums
* feat(epistemic): tag TurnEvent with state axes
* feat(epistemic): serialize turn state axes
* feat(packs): tag curated and inferred unit entries
* feat(epistemic): expose word-level state on manifold
* feat(epistemic): expose vault status mapping
* feat(epistemic): preserve pack entry states through compiler
* test(epistemic): cover phase 3 state tagging spine
* feat(runtime): wire epistemic_state + normative_clearance into ChatResponse
Add first-class epistemic_state and normative_clearance fields to
ChatResponse (defaulting to "undetermined"/"unassessable" for backward
compat). Import epistemic_state_for_grounding_source and
clearance_from_verdicts into chat/runtime.py and populate both fields on
the stub path (TurnEvent + ChatResponse) and the main path (TurnEvent +
ChatResponse). Fix the test fixture to use "euro per hour" (a genuinely
composed unit) instead of "dollars per hour" which is a curated lexicon
entry and returns DECODED, not INFERRED.
* test(cognition): update term_capture_rate baseline from 0.9167 to 1.0
unknown_logos_019 now correctly surfaces "light" as a pack-resident
token near the logos versor — producing term_capture_rate 1.0 on both
main and Phase 3. The 0.9167 pin was stale relative to a surface change
already on main; Phase 3 did not introduce this shift.
* fix(epistemic): make empty resonance evidence undetermined
* fix(evals): classify verified realizer failures separately
* fix(packs): treat absent domain manifests as valid noop
* test(packs): cover missing manifests and scope boundary domains
* test(epistemic): cover phase 2 known bug fixes
* fix(vault): make FALSIFIED exclusion explicit in _status_admits
FALSIFIED entries previously fell through to the ADMISSIBLE_AS_EVIDENCE
set-check, which excluded them correctly but left the distinction between
CONTRADICTED (FALSIFIED) and UNVERIFIED-POSSIBLE (SPECULATIVE) implicit.
Add an early guard so FALSIFIED is explicitly rejected before the tier
filter, matching the CONTRADICTED semantics from the epistemic taxonomy.
Vault, language-packs, and runtime-packs audits complete. Findings:
- Ratifies INFERRED (14th epistemic state): derived from DECODED
primitives by ratified deterministic rule; composite never curated.
Grounded by language_packs composition rules (per/square/cubic unit
synthesis). Sits between DECODED and UNVERIFIED-POSSIBLE in the
epistemic progression.
- Ratifies normative clearance axis as orthogonal companion to the
epistemic axis. Safety/ethics verdicts are not epistemic states;
they answer a different question (normative compliance vs. truth-
value). Four clearance states: CLEARED, VIOLATED, UNASSESSABLE,
SUPPRESSED. Every proposition in ChatResponse/TurnEvent carries
both an epistemic_state and a normative_clearance tag.
- Closes open question 5 (identity/safety/ethics interaction):
identity grounds the epistemic axis; safety/ethics live on the
normative axis; they coexist without collapsing.
- Updates RecognitionOutcome shape with both axes.
- Marks all four subsystem audits complete in Framing 1 block;
documents vault implementation debt (_status_admits conflation)
and deferred candidate (COMPOSED_RECOGNITION).
- Records four Phase 2 implementation bugs in summary:
evidence.py empty-pairs silent-FALSIFIED, runner DECODED-
UNARTICULATED misclassification, domain_contract present=False
inconsistency, _status_admits FALSIFIED/SPECULATIVE conflation.
Taxonomy is now stable. Phase 2 (bug fixes) and Phase 3 (first-class
state tagging in ChatResponse/TurnEvent) are the remaining work.
Math-subsystem audit (40 decision points, 9 files) confirmed the 9-state
starter taxonomy was too coarse. Ratifies four new states surfaced as
EPISTEMIC_STATE_NEEDED gaps:
- EVIDENCED-INCOMPLETE: lift completed for a sub-span; proposition
structurally partial but not contradicted (grounded by orphan-rate
refusal in math parser)
- DECODED-UNARTICULATED: trace is replay-equal; surface realization
path broke — exposes a runner misclassification where RealizerError
on a verified trace is currently outcome="wrong"
- SCOPE_BOUNDARY: engine recognized the proposition type; refuses
because the type is outside the current capability envelope, not
because the lift failed
- COMPUTATIONALLY_BOUNDED: search budget exhausted before answers were
enumerated; distinct from AMBIGUOUS (no answers compared) and
UNDETERMINED (text likely has structure)
Also: updates primitives mapping table, marks Framing 1 audit complete
for math subsystem, closes the "too coarse" risk item (9 → 13 states),
and records the runner misclassification as a load-bearing correctness
issue for the next runner revision.
* feat(ADR-0141): multiply as CGA dilator versor (positive non-zero)
Adds `multiply(scale)` to `generate/math_versor_arithmetic.py` as the
standard CGA dilator for multiplicative scaling along e1, restricted to
`scale > 0`. All ten ADR-0141 assertion families pass.
Preliminary measurement confirmed:
N = n_o ∧ n_inf: component -1 at index 15 (blade (3,4) = e4∧e5)
N² = +1.0 (pure scalar) → closed-form D_s = cosh(α/2) + sinh(α/2)·N
n_o · n_inf = -1; n_o² = n_inf² = 0
Because N² = +1, the cosh/sinh expansion is exact in float64 and
D_s · ~D_s = cosh² − sinh² = 1 holds to machine epsilon.
The sandwich D_s·X·~D_s produces a null point with n_inf normalization
1/s. `decode_quantity` is updated to divide by that factor, recovering
value · s. For translator outputs (normalization = 1) the result is
identical to the previous direct e1 read; all 152 prior add/subtract
tests pass unchanged.
`embed_quantity` is updated to embed directly in float64, eliminating
float32 quantization error for values like 0.01 (float32(0.01) ≠ 0.01);
all prior test-case values were exactly representable in float32.
* docs(ADR-0141): add decision document for multiply-as-dilator spike
The ADR doc was drafted in a separate branch and not present when the
implementation worktree was created from origin/main. Adding it now so
the decision record lands on main with the implementation it specifies.
Content unchanged from the draft — same spec the implementation already
satisfies (10 assertion families, fixed test cases, falsification
discipline, deferred scope for negative / zero / divide / Rate).
No code or test changes in this commit.
Extends generate/math_versor_arithmetic.py with one new function:
def subtract(addend: float) -> np.ndarray:
return translator(-float(addend))
Single-line delegate to translator(); no new algebra.
Adds tests/test_arithmetic_subtract_and_group.py covering all nine
ADR-0140 acceptance families:
Families 1-6 (ADR-0139 families applied to subtract):
1. Embedding well-formedness — null cone preserved for subtract cases
2. Translator-of-negative well-formedness — versor_condition < 1e-6
3. Closure — sandwich result stays on null cone
4. Arithmetic correctness — decoded value == a − b within 1e-9
5. Replay determinism — byte-identical across runs
6. Composability — subtract(c) ∘ subtract(b) decodes to a − b − c
New group-property families (structural verification of ADR-0139 claim):
7. Inverse composition — T_{-b} * T_b = identity (max residual: 0.000e+00)
8. Round-trip closure — versor_apply(T_{-b}, versor_apply(T_b, X)) → (a, u)
9a. Sum composition — T_a * T_b = T_{a+b} (max residual: 0.000e+00)
9b. Commutativity — T_a * T_b byte-equals T_b * T_a (all 10 cases)
All 96 tests pass. Group residuals are exactly 0.0 in float64.
The additive subgroup of Cl(4,1) translators along e1 is abelian and
closed; ADR-0139's algebraic claim holds at the group level.
First step of the Engine A lift program (CLAUDE.md commits the project to a
single deterministic cognitive engine; Engine B / math pipeline was always
intentional scaffolding per math_solver.py:24). Proves the load-bearing
unknown: one arithmetic operation can be represented as a closed versor at
the required tolerance, with no new normalization and no weakened invariant.
Scope (frozen by ADR-0139):
- One operation: add
- Single-axis embedding: quantities on e1 axis
- No graph wiring, no pipeline integration, no GSM8K case routed
- Unit carried as caller metadata
Construction:
- embed_quantity(v, u) = embed_point([v, 0, 0]) (existing CGA primitive)
- translator(b) = 1 - 0.5 * (b*e1 * n_inf) (textbook CGA translator)
- decode_quantity(F, u) = (F[1], u) (e1 coordinate)
Measured values (all 11 fixed cases + composability):
a b vcond(T) |<R,R>| decode_err
0.0 0.0 0.000e+00 0.000e+00 0.000e+00
0.0 1.0 0.000e+00 0.000e+00 0.000e+00
1.0 0.0 0.000e+00 0.000e+00 0.000e+00
3.0 4.0 0.000e+00 0.000e+00 0.000e+00
7.0 -3.0 0.000e+00 0.000e+00 0.000e+00
0.25 0.75 0.000e+00 0.000e+00 0.000e+00
1.5 2.5 0.000e+00 0.000e+00 0.000e+00
-5.0 5.0 0.000e+00 0.000e+00 0.000e+00
-2.0 -3.0 0.000e+00 0.000e+00 0.000e+00
100.0 1.0 0.000e+00 0.000e+00 0.000e+00
1.0 100.0 0.000e+00 0.000e+00 0.000e+00
compose (2, 3, 5) → 10: |<R2,R2>| = 0.000e+00, decode_err = 0.000e+00
Every residual is exactly 0.0 in float64. The construction is algebraically
closed: T_t * reverse(T_t) = 1 - 0.25*B^2 where B = t*n_inf, and B^2 = 0
because (e14)^2 + (e15)^2 = -1 + 1 and cross-terms cancel. No machine-epsilon
drift accumulates because the relevant cancellation happens at the algebraic
level before float arithmetic.
ADR-0139 acceptance items 1-6 (one parametrized test family each):
1. Embedding well-formedness — test_family1_embedding_is_null (11 cases)
2. Translator well-formedness — test_family2_translator_unit_versor (11 cases)
3. Closure — test_family3_sandwich_preserves_null (11 cases)
4. Arithmetic correctness — test_family4_decode_matches_sum (11 cases)
5. Replay determinism — test_family5_replay_byte_identical (11 cases)
6. Composability — test_family6_two_translators_compose (1 case)
Total: 56 tests, all passing.
Lift program decision: proceeds. Follow-on ADRs (subtract, multiply, Rate,
compare, MathProblemGraph → PropositionGraph, pipeline integration, first
GSM8K case end-to-end through Engine A) are now justified by a concrete
algebraic foundation rather than design speculation.
Out of scope per ADR-0139:
- No modifications to algebra/, core/cognition/, chat/, math_solver.py,
math_verifier.py, math_realizer.py, math_candidate_parser.py
- No GSM8K runner changes
- No pack changes
- Engine B continues serving GSM8K unchanged; the 3/50 admission set is
preserved
CLI lanes intentionally not run — main has known test-rot orthogonal to
this PR. The 56 new tests are self-contained and the diff touches only
three new files.
Adds a 3-line TODO comment above `_score_one_candidate_graph` in
evals/gsm8k_math/runner.py. No behavior change.
Flags that `report.json` metrics may not credit candidate-graph
admissions routed through this branch (Stage 1 candidate-graph
parse + internal solve path) the same way `_score_one` admissions are
credited. Aggregation in calling code needs an audit before the
canonical run.honest_runner.json artifact can be trusted for
cross-phase comparison.
This is Piece A of a three-piece hygiene split. The MEMORY.md
compaction and worktree audit pieces are deferred — they need
human judgment (re-shaping vs. truncating) and an OS-correct date
predicate (BSD vs. GNU), neither of which fits a one-shot script
pass.
No tests run — this change is comment-only and has zero runtime
effect.
* content(packs): update relations checksum
* revert transient relations manifest checksum
* content(packs): extend relations lexicon additively
* content(teaching): extend relations chains additively
* content(packs): ratify relations manifest checksum
* test(packs): accept additive relations lemma extension
* test(packs): add relations v1 extension regressions
* fix(tests): align relations extension lemma set
* content(packs): add relations mastery report
* content(packs): drop unused .mastery_report.json sidecar
Language packs do not consume mastery reports — the pattern is from
identity packs (packs/identity/) and has no consumer in language_packs/
loader.py or compiler.py. The added sidecar's self-seal hash also did
not validate against sha256(json.dumps(body, sort_keys=True,
separators=(',', ':'))).
Drop the file. The actual ratification surface for this pack is the
manifest.json lexicon_checksum, which still matches lexicon.jsonl
bytes (verified).
A small typed linguistic layer (FractionOperand, ComparativeOperand,
QuantityReference, ReferenceTarget) replacing the closed-and-deferred
ADR-0137 with a shape-driven design. Justified by the rescan-v3 ledger
showing 7 cases under fraction_operand + compound_comparative that
share a common deep structure (value relative to literal or
prior-sentence anchor) with multiple surface shapes.
Key commitments:
- Three typed phrase structures handle the closed surface set
(frac/percent of X, N times as much/greater than X, frac more/less
than X), where X is either a sentence-internal literal or a
QuantityReference to a prior grounded quantity.
- Binding pass is minimal: sentence-order lookup of QuantityReference
against prior grounded candidates with unique-match gating. No
generic DeferredCandidate apparatus.
- Pinned English convention: "N times greater" = N+1 multiplier
(documented + tested). Other reading requires explicit revisit.
- Supersedes ADR-0137 in scope; the deferral note's reopen criterion
is met by this lighter, more specific design.
- S.1/S.2 short-circuits stay as joins of grounded candidates;
this ADR does not subsume them.
Forcing case for cross-sentence binding: gsm8k-0029 ("three times
greater than the cost of the mouse" + "the mouse cost $16"). Clean,
unambiguous, two-sentence binding.
Self-correction caught before push: gsm8k-0010 was initially framed
as the forcing case, but its expected dataset answer requires a
non-standard English parse of "1/4 more than X" (the natural reading
gives 17; the dataset says 9, requiring X/4 + 7). Per non-negotiable
#2 the binding pass MUST refuse on this; 0010 is reclassified from
"expected admission" to "negative probe." 0029 takes the forcing-case
slot.
Honest expected admission delta: +1 to +2 (0005, 0029 high
confidence; 0041, 0043 partial credit only).
In scope: in the same PR family, fix the issue gsm8k-0029 surfaces by
implementing the binding pass. Out of scope: inverse arithmetic
(0004), multi-term aggregate references (0036), pronoun anchoring,
self-referential cycles.
S.4 extends initial-state parsing with two closed subject-slot widenings:
- Indefinite-article: `A <noun> has N <unit>` (gsm8k-0046 sentence 1)
- Prepositional-prefix existential: `In a <place>, there are N <unit>...`
(gsm8k-0038 sentence 1)
Design choice: sibling regexes (_INITIAL_HAS_INDEF_RE,
_INITIAL_THERE_ARE_PREFIX_RE) rather than widening the global _ENTITY
pattern — preserves existing behavior across all other initial-state
extractors (cascade-safety).
Per the S.x corridor discipline: no new short-circuit; new candidates
flow through extract_initial_candidates and the existing graph machinery.
No solver/graph/verifier changes.
Honest delta:
- Direct admissions: 0 (admission set unchanged at {0014, 0018, 0042})
- Barrier shifts: +2 (gsm8k-0038: novel_initial_form → compound_comparative;
gsm8k-0046: novel_initial_form → fraction_operand)
- wrong == 0 on every lane
Bundled with this PR for ledger currency:
1. tests/test_rescan_v3_invariants.py refactored to read frozen on-disk
v3 artifacts only (no more re-running build_rescan against live
parser). The previous design tied a historical snapshot to live code
and broke the moment any new phase landed.
2. rescan_v4.py + refusal_rescan_v4.json + refusal_taxonomy_v4.json +
tests/test_rescan_v4_invariants.py — the current live snapshot.
Shifts: exactly 2 (0038, 0046). Same pattern as v3.
Sonnet wrote: S.4 parser/axis-lane/tests/ADR.
Opus wrote: rescan_v4.py + v3 test refactor + bundling.
Files:
- generate/math_candidate_parser.py (+142 lines)
- evals/math_capability_axes/S4_novel_initial_form/v1/ (20-case lane)
- tests/test_adr_0136_S4_novel_initial_form.py (40 tests)
- docs/decisions/ADR-0136.S.4-novel-initial-form.md
- evals/gsm8k_math/train_sample/v1/{rescan_v4.py, *_v4.json}
- tests/test_rescan_v4_invariants.py (8 tests)
- tests/test_rescan_v3_invariants.py (refactored to artifact-only)
Re-runs parse_and_solve on the 50-case GSM8K train sample on current
main (post-S.3) and compares to v2. Result: admitted=3/50 (unchanged),
wrong=0, exactly 1 barrier shifted v2→v3.
Shift: gsm8k-0010 (compound_statement → fraction_operand). S.3's
_INIT_MUTATION_RE resolves "Yun had 20 paperclips initially, but then
lost 12" to InitialPossession(Yun, 8, paperclips). First refusal moved
to sentence 2: "Marion has 1/4 more than what Yun currently has, plus
7" — needs fraction-operand + coreference-quantity + comparative-additive
arithmetic.
Top blockers (v3):
compound_statement 5 (was 6)
novel_initial_form 5 (unchanged)
fraction_operand 4 (was 3 — gsm8k-0010 moved here)
novel_initial_verb 4 (unchanged)
Artifacts:
- evals/gsm8k_math/train_sample/v1/rescan_v3.py
- evals/gsm8k_math/train_sample/v1/refusal_rescan_v3.json
- evals/gsm8k_math/train_sample/v1/refusal_taxonomy_v3.json
- docs/decisions/ADR-0136.S3-post-rescan.md
- tests/test_rescan_v3_invariants.py (7 tests; determinism + admission
set unchanged + exactly-one-shift + 0010-specific shift assertions)
PR #204 (ADR-0137 retrospective binding, rescoped to subsumption-only)
was drafted then closed without merging. The deferral reason is
structural: the DeferredCandidate/BindingProof apparatus is the right
shape for true retrospective binding (first-pass candidate has open
slots awaiting later evidence), but re-examination showed neither S.1
nor S.2 short-circuit fits that definition — both join two fully
grounded candidates. With no kind that has open slots in the v2
ledger, the machinery would degenerate to a join everywhere, which is
speculative infrastructure ahead of a forcing function (CLAUDE.md
warns against this pattern).
Update appended to the post-rescan notes so the deferral lives in the
repo, not just in a closed PR thread. Includes a reopen criterion:
ADR-0137 (or successor) may return when a case appears whose first-pass
candidate has genuinely open slots only later-sentence evidence can
close. Until then the unlock vehicle is S.x.
The S.1/S.2 short-circuits remain as tactical bridges; the canonical
runner staleness is better fixed in the runner than in a binding
layer.
Measurement-only branch. Re-runs parse_and_solve on all 50 GSM8K train-sample
cases against the current parser (post-S.1/S.2) and produces a barrier-shift
ledger comparing v1 taxonomy to current behavior.
Results: admitted=3/50 (0014, 0018, 0042), wrong=0, barrier_shifted=27/50.
Context-filler dominance collapsed from 23→3 cases; compound_statement (6)
and novel_initial_form (5) are now the largest buckets.
Subsumption directive pinned: ADR-0137 SHALL re-derive all short-circuit
admissions as (DeferredCandidate, evidence, BindingProof) triples.
- Add classify_sentence() + has_numeric_token() to math_candidate_parser.py.
Rule: sentence with no digit and no word-number cannot introduce parseable
numeric state — classify as "context" and skip safely (wrong==0 preserved).
- Add pre-pass in parse_and_solve() (math_candidate_graph.py): strips context
sentences before extraction; falls through to refusal if none remain numeric.
- Extend capacity patterns for gsm8k-0018:
- _CAPACITY_INVERTED_RE: "During M <time-unit> <Actor> can <verb> N <unit>"
- _CAPACITY_Q2_RE: "How many <unit> [on average] is <Actor> able to <verb>,
when the <event> lasted for T <time-unit>?"
- GSM8K: 1/50 -> 2/50 (gsm8k-0018 admits with answer 16.0); admitted_wrong==0.
- Tests: 47/47 pass (12 new for classifier, inverted patterns, 0018 end-to-end).
All five G.x capability axes shipped (G.1–G.5); admission remained 0/50
throughout — expected, because the 50 sample cases fail at the statement
layer (rate verbs, implicit entities, multi-step ops), orthogonal to the
question-layer and initial-state-verb work the G.x axes targeted.
Decisions:
- Probe retired as a per-iteration gate (signal-to-noise ≈ 0 at 0/50)
- `admitted_wrong == 0` invariant preserved as a standing architectural
invariant, CI-pinned by existing test + per-axis regression guards
- Re-activation criterion named: statement-layer expansion that
plausibly admits ≥1 new case (Δadmission_rate ≥ 0.02)
- Probe runner + report stay in-repo for future statement-layer push
Docs-only. No test, parser, solver, or eval changes.
