Closes audit Findings 6 (within-turn recall not batched) and 7
(probe-ingest / commit-ingest dual field) as a single PR — the two
are architecturally entangled and resolve together.
Pre-fix flow in ``ChatRuntime.chat()``:
1. ``probe_ingest(filtered)`` → ``probe_state.F``
2. Gate check on ``probe_state.F``
3. If gate fires: ``commit_ingest`` + stub response
4. Otherwise: ``commit_ingest`` + drive bias → ``field_state.F``
5. Walk runs on ``field_state.F``
The gate observes one manifold position; the walk navigates a
slightly different one (drive bias applied between them). Honest
refusal decisions and walk outputs are made on different fields —
the audit's named coherence gap.
This PR ships a flag-gated unified-ingest path following the
codebase's standard substantive-change pattern (ADR-0046 /
ADR-0062 / ADR-0085 / ADR-0088 / ADR-0089):
``RuntimeConfig.unified_ingest: bool = False`` (default).
When ``True``:
1. ``commit_ingest(filtered)`` runs first.
2. Drive bias applied immediately.
3. Gate observes ``committed.F``.
4. If gate fires: stub response (turn has already committed —
intentional semantic change documented in ADR-0090).
5. Otherwise: walk runs on the same ``committed.F`` the gate
decided against — no second ``commit_ingest`` call.
6. ``probe_ingest`` is not called on this path.
When ``False`` (default): historical behavior is preserved
bit-for-bit; ``probe_ingest`` still runs first.
ADR-0090 documents:
* Phase 1 (this PR): unified-ingest substrate.
* Phase 2 (separate PR, after Phase 1 validates): batched recall
— pass the gate's ``direct_hits`` into ``generate()`` as a
``prebuilt_first_recall`` so the walk's first step does not
re-call ``vault.recall()`` on the same field. Single recall
call eliminated per turn.
* Out of scope: ``recall_batch`` for per-step walk recalls
(each step's query depends on the previous step's field
state; not batchable without changing walk geometry).
Validation:
* 5 new tests in ``tests/test_unified_ingest_null_lift.py``:
- flag defaults to ``False`` on ``DEFAULT_CONFIG``
- flag-off surface + trace_hash + vault_hits byte-identical
- flag-on does not call ``probe_ingest`` (verified via spy)
- flag-on produces well-formed surface + trace_hash
- flag-off still calls ``probe_ingest`` (historical guard)
* ``core eval cognition`` byte-identical across all three splits:
public 100/100/91.7/100, dev 100/100/78.6/100, holdout
100/100/83.3/100.
* ``core test --suite cognition`` 120/0/1, ``smoke`` 67/0,
``runtime`` 19/0.
Comb-pass status after this PR:
* Item 4 (graph topo) ✓ #92
* Item 5 (realizer node_map) ✓ #91
* Item 6 (batch recall) ✓ ADR-0090 substrate (this PR); Phase 2
optimization is queued
* Item 7 (probe/commit dual ingest) ✓ ADR-0090 (this PR)
* Item 8 (dead defensiveness sweep) ✓ #91
* Item 9 (local imports) ✓ #91
* Item 11 (dead ``_fold_compose_into_surface``) ✓ #91
* Item 13 (``_serialize_*`` fold) ✓ #91
* Item 15 (GenerationResult tuple/list) ⊘ false positive
* Item 16 (subject normalization consistency) ✓ #93
* Item 17 (redundant ``^`` anchors) ✓ #94
* Tier 5 minor (``_BE_FORMS`` hoist, walrus, reverse-iter) ✓ #94
Comprehensive survey of every pack in the tree across five layers
(primitives → language → teaching → policy → selection axes → style)
with per-pack stats, cross-pack lemma overlap, teaching-chain graph
topology, and a ranked top-leverage-gaps list.
Key findings:
* **Layer 4 (selection axes) is the densest by far** — 24 packs
(17 anchor lenses + 7 registers). Greek and Hebrew lens
families are at parity (8 each).
* **Layer 2 (teaching corpora) is the load-bearing thin layer** —
only 41 reviewed chains across 18 subjects, with just 2 intent
shapes covered (CAUSE / VERIFICATION) and 7 connectives total.
No COMPARISON / PROCEDURE / CORRECTION chains exist; those
intents route through pack composers only.
* **Layer 1 EN is solid** — 354 lemmas across 12 mounted packs
with 93% gloss coverage; 24 ungloss'd lemmas remain.
* **Cross-language is structurally present but content-light** —
grc / he micro-packs ship and mount; the bigger
``*_cognition_v1`` siblings ratify but are not in the default
mount; no glosses exist on any non-EN pack.
* **Three drafted ethics packs are unratified** (legal /
research / engineering) — the highest-leverage low-effort gap.
* **Rhetorical-style axis ships substrate only** — one
null-lift pack; ADR-0087 consumer phase pending.
Top-leverage gaps ordered by ratio of unblocked value to effort
are enumerated in §7 of the doc itself. No code lands here.
Two ADRs that unblock the remaining items from the 2026-05-20 audit
that could not ship as direct PRs.
ADR-0088 — Realizer-Grounded Authority (Finding 2 retry)
========================================================
The first-response audit remedy (wire ``ground_graph`` between
``runtime.chat`` and ``realize_semantic``) was empirically attempted
on ``fix/ground-graph-wiring`` and reverted: the grounded realizer's
template output (e.g. ``"Light is a visible medium that reveal
truth"``) is grammatically and stylistically weaker than the runtime
path's ADR-0085-polished pack-grounded surface, so the realizer wins
the surface resolver (PR #76) and the user-visible surface regresses
on 23 byte-identical tests + ``register_invariant_grounding``.
ADR-0088 reframes Finding 2 as a two-phase rollout:
* Phase A (no behavior change) — realizer fluency parity.
Templates consult the same gloss source ADR-0085 wired into the
CAUSE composer, emit 3sg verb agreement, and carry the same
pack-provenance tag the runtime path emits. Byte-identical
today because the realizer is still gated by
``_is_useful_surface``.
* Phase B (substantive) — ground the graph and let the realizer
compete. Surfaces change exactly once, with a per-case
re-baseline justified by a "fluency ≥ pre-fix runtime surface"
invariant.
The audit's final-draft remedy (hot-path short-circuit only) is
explicitly rejected — pure perf cleanup, no metric lift since
``core eval cognition`` is already at 100% groundedness.
ADR-0089 — Compound-Intent Pipeline Dispatch (Finding 4)
========================================================
``classify_compound_intent`` is implemented but never reaches
``CognitiveTurnPipeline.run()``. Compound inputs like *"What is X
and how does it relate to Y?"* silently drop the second clause.
Naive multi-node dispatch breaks every downstream stage:
PropositionGraph (one root), plan_articulation (single-root),
realize_semantic (one target), surface resolver (one surface per
turn), compute_trace_hash (one intent_tag + articulation_surface),
teaching loop (one correction-source proposal), register / anchor-
lens telemetry (one variant per turn).
ADR-0089 proposes a three-phase rollout:
* Phase C1 (no behavior change) — call ``classify_compound_intent``
in step 1b, record dropped clauses on
``CognitiveTurnResult.dropped_compound_clauses`` for
observability while routing the dominant clause through the
existing single-intent path.
* Phase C2 (opt-in substantive) — flag-gated multi-node graph
dispatch with new ``CompoundEdge`` / ``ConjunctionRelation``,
widened ``compute_trace_hash`` carrying a
``compound_clauses_hash``, and a ``multi_clause_surface`` field
on the resolver. Flag-off preserves byte-identity.
* Phase C3 — telemetry alignment + demo + docs.
Each phase is independently shippable and preserves the existing
null-lift / byte-identity invariants register and anchor-lens
established (ADR-0072, ADR-0073d) as the project's pattern for
substantive runtime behavior changes.
Both ADRs are Proposed; ratification follows the existing pack /
ADR review process. No code lands in this commit.
Follow-up brief for the cheaper dev agent. Scoped tight: ~18 concrete
row-by-row edits across two patterns the v1 pass (PR #73) deferred or
missed.
Pattern A — 3sg present-tense agreement after relative pronouns
what/who/that/which followed by a bare-form verb where the implied
subject is singular. 10 candidates identified up front by repo scan:
- en_core_causation_v1/effect (with judgment note)
- en_core_cognition_v1/beginning, creation, definition, evidence,
light, reason, symbol
- en_core_meta_v1/example, mind
Brief explicitly clarifies that bare verbs after modals (`can`,
`may`, `should`) are CORRECT and must NOT be changed — flagging
the "who can know and do" case the v1 agent did right.
Pattern B — plural agreement after quantifier / preposition
between/among/of/two/three/many + count-noun-in-singular. 5
confident edits + 3 borderline cases with judgment guidance:
- en_core_attitude_v1/broad
- en_core_cognition_v1/context, order, style
- en_core_spatial_v1/between
Borderline guidance distinguishes count vs mass nouns: `reason`
in "group of reason" is count (apply fix); `reason` in "because
of reason" is mass (leave alone).
Same hard rules as v1 brief:
- no code edits
- definitional_atoms / predicates_invited / pos / lemma /
definition_version must not change
- Greek/Hebrew packs and primitives pack untouched
- closure verifier must exit 0
- cognition eval must stay byte-identical
- draft PR, human review before merge
Estimated effort: ~18 one-character edits. Whole pass should take an
order of magnitude less time than v1 because the candidate rows are
enumerated in the brief itself rather than discovered via heuristic
scan.
Why a v2 brief rather than amending v1's PR:
Plural patterns were not on v1's explicit pattern list (the v1
brief only named verb agreement, missing articles, missing
infinitives, missing copulas). 3sg agreement was named but
required a different tool than the agent had at hand. Scoping
v2 to exactly the rows known to need fixing is cheaper than
re-running the v1 heuristic scan with an expanded ruleset.
Provenance tag for the v2 pass:
adr-0085-style-v2:reviewed:2026-05-22
Pre-work for a writing-curriculum extension to CORE. Two companion
documents, both Proposed status (no code shipped).
docs/decisions/ADR-0087-rhetorical-style-axis.md
Pins rhetorical style as a third selection axis — sibling to anchor
lens (ADR-0073), orthogonal to register (ADR-0070). Substantive
axis: trace_hash DISTINCT across styles (style changes which moves
the composer requires and which frames the realizer emits, which
changes the propositional plan, which changes the trace).
Four anti-patterns explicitly named and rejected:
- style as motor (re-couples realizer to geometry; same shape as
the ADR-0085 fusion-operator rejection)
- style as register variant (conflates substantive with stylistic)
- style as identity axis (bloats identity doctrine)
- style auto-detected from user input (operator-chosen only)
Pack shape mirrors packs/anchor_lens/. default_unstyled_v1 is the
null-lift pack identical to no-style behavior. Three CI invariants
proposed: rhetorical_style_null_lift, schema validation, three-axis
orthogonality.
Substrate-only ADR — no consumer code, no genre packs. Consumer
integration is a follow-up ADR (composer + realizer extensions
that read permitted_frames + required_moves_per_claim +
forbidden_moves).
docs/curriculum/writing-chain-harvester-spec.md
Layer 0 of the writing curriculum. A deterministic tool that
extracts candidate (subject, predicate, object) triples from
reviewed expert prose and surfaces them as proposals to the
existing teaching/review pipeline.
Five stages (segment → classify → extract → propose → audit) —
pure-Python rule-based, no LLM generation, no auto-acceptance.
Trust boundary: reviewer accept/reject via the existing
core teaching propose/review path. No bypass permitted.
The harvester is a proposal PRODUCER, not a proposal CONSUMER.
Plugs into the existing pipeline without inventing a new review
mechanism. Each proposal carries source_id + source_line + the
exact source_clause it came from for reviewer verification.
First-implementation acceptance criteria deliberately tight:
Stage 0+1 with dry-run only. Stages 2-5 are follow-up PRs.
Substrate-first sequencing pattern (ADR-0084 → 0085) reused
throughout. Both documents acknowledge open questions deferred to
implementation phase rather than pre-deciding.
Why now: a writing curriculum is being scoped. Without this ADR,
every downstream PR faces the same "should style be a motor?"
question and the temptation to reach for the geometry will recur
every time the realizer produces a stilted surface. Pinning the
axis up front prevents that recurrence.
Brief for a fluency pass on the 333 ratified gloss entries. Closes the
content-side counterpart of ADR-0085's surface lift:
Before "Light exists as visible medium that reveal truth."
After "Light exists as a visible medium that reveals truth."
Same gloss content, English-correct. Fixes 3sg agreement after
relative clauses, plural agreement after quantifiers, missing
articles before adjective-noun NOUN-frame glosses, and missing 'to'
in VERB-frame glosses.
Hard constraints encoded in the brief (matching the wrapper-prompt
pattern that worked for ADR-0084 content):
- code untouched: only language_packs/data/<pack>/glosses.jsonl edits
- definitional_atoms, predicates_invited, pos, lemma, definition_version
must NOT change
- closure verifier (scripts/verify_definitional_closure.py) must
still exit 0
- cognition eval must stay byte-identical to baseline
- Greek/Hebrew packs untouched (not in definitional layer per ADR-0084
scope limit)
- primitives pack untouched
- draft PR, human review before merge
Includes a Phase-1 inventory script the agent runs first to scope the
work (heuristic pattern matcher across the 13 opted-in packs),
worked-example fluency rules with before/after table, per-pack
checksum-refresh shell snippet, and Phase-4 verification commands.
Estimated effort: ~30-60 lines of JSONL edits. Same handoff format as
docs/handoff/ADR-0084-pack-content-brief.md.
The original "Why does light exist?" complaint that motivated ADR-0084
was specifically about CAUSE-intent surfaces. ADR-0084 (substrate) +
PR #65 (content) already moved DEFINITION/RECALL to gloss-grounded
surfaces ("Light is visible medium that reveal truth."). But CAUSE
still dispatched through the chain-walk path:
Before: light — teaching-grounded (cognition_chains_v1):
cognition.illumination; logos.core.
light reveals truth (cognition.truth).
No session evidence yet.
After: Light exists as visible medium that reveal truth.
pack-grounded (en_core_cognition_v1).
The chain-walk is structurally correct but the wrong SHAPE for a why-
question — it's a graph traversal, not an explanation. ADR-0085 fixes
the shape using the same gloss material that DEFINITION/RECALL already
consume, with no new content authoring.
Additive composer
chat/pack_grounding.py:gloss_aware_cause_surface()
- Resolves gloss via lexicon-residency-checked resolve_gloss().
- Frames POS-aware:
NOUN -> "{Lemma} exists as {gloss}."
VERB -> "To {lemma} is to {gloss}."
ADJ -> "To be {lemma} is to {gloss}."
* -> falls back to _frame_gloss (predicate-identity).
- Threads anchor lens via the existing helper (ADR-0073c parity).
- Returns None when no gloss exists — runtime falls through to the
existing chain-walk path. Additive: no CAUSE case loses its surface.
Runtime dispatch
chat/runtime.py — IntentTag.CAUSE tries gloss path FIRST under the
flag; falls through to teaching_grounded_surface* on None.
Unconditional fallback — never silent.
Opt-in flag
core/config.py — RuntimeConfig.gloss_aware_cause: bool = False
Default off preserves pre-ADR-0085 chain-walk surfaces byte-
identically (null-drop invariant, CI-pinned).
Prompt-diversity classifier update
evals/prompt_diversity/runner.py — _CAUSE_MARKERS widened with the
explanation-frame markers ("exists as", "is to", "to be", "is for",
"purpose of") plus bare-form predicates ("reveal" alongside
"reveals"). Neither composer path is penalised on shape_fit just on
inflection grounds.
v1/public lift (flag OFF vs ON, 26 cases)
intent_accuracy : 65.4% -> 65.4% ( — )
versor_closure_rate : 100.0% -> 100.0% ( — )
response_shape_fit : 57.7% -> 57.7% ( — , both frames recognized)
audit_in_surface_rate : 42.3% -> 42.3% ( — , envelope ADR's job)
gloss_quote_rate : 11.5% -> 23.1% (+11.5pp, structural lift)
Tests (15)
- 5 pure composer (NOUN/VERB frame, unknown/empty None, no chain-
walk artifacts in surface)
- 5 runtime dispatch (flag-off chain-walk, flag-on gloss, parametrized
across glossed subjects, VERIFICATION unchanged under flag, no-
gloss fallback engages)
- 5 cognition lane invariance (aggregate metrics byte-identical
under both flag states; surfaces deliberately shift on the 2 CAUSE
cases with glossed subjects — the structural-change-vs-metric-
invariance both-sides invariant)
Lanes
smoke 67/0, cognition 120/0/1 skipped, packs 6/0, teaching 17/0,
runtime 19/0. core eval cognition byte-identical 100/91.7/100/100
under both flag states.
Scope limits (per ADR §Scope limits)
- CAUSE only; VERIFICATION still chain-walks (different shape).
- English pilot only; Greek/Hebrew packs not opted into definitional
layer yet (ADR-0084 scope limit).
- Single-lemma subjects; compound/anaphoric fall through.
- Opt-in until cognition holdout confirms the lift transfers off-
fixture. Future PR flips default on.
Out of scope
- Surface-vs-envelope cleanup ("pack-grounded (...)" still leaks).
- Predicate licensing (ADR-0086).
- Content style pass (bare lemma forms in glosses — separate brief).
* docs(adr-0084): propose definitional layer + prompt-diversity suite
Three companion artifacts proposing the next substantive design step
after ADR-0083:
1. ADR-0084 (Proposed) — Definitional Layer for Lexicon Packs
Optional `definition` block on pack entries: gloss,
definitional_atoms, predicates_invited, definition_version,
provenance. Pack-level opt-in. Closure rule: every word in a
gloss must resolve to a same-pack lemma, another mounted pack's
lemma, or a primitive in a new `packs/primitives/` pack.
NO composer change in this ADR (sequenced for ADR-0085) —
ratify substrate before any consumer depends on it.
2. evals/prompt_diversity/ (Proposed) — companion eval lane
~50 cases across question-shape × sophistication × domain,
measuring three new metrics: response_shape_fit,
audit_in_surface_rate (quantifies the trust-boundary leak into
user surfaces), gloss_quote_rate (zero today; rises with future
gloss-aware composer). No v1 pass thresholds — the lane
establishes a baseline distribution so future work has
something to move. 26 seed cases authored covering all 21
categories.
3. docs/handoff/ADR-0084-pack-content-brief.md — paste-ready brief
for a cheaper/faster dev agent to produce the pack content in
parallel. Self-contained, 5 sequenced phases (primitives pack
→ extend 9 existing glosses → add to relations/anchors → write
closure verifier → run safety lanes), explicit don't-touch list
(no composer / runtime / algebra / Greek+Hebrew packs / schema
parser), no-LLM-glosses discipline, per-phase acceptance.
Discovery while drafting: 9 packs already carry glosses.jsonl
under language_packs/data/ with a flat schema (78 entries in
en_core_cognition_v1 alone). The brief reflects that — most
work is extending existing entries, not authoring from scratch.
Strategic context: ADR-0083 raised the *depth* ceiling on chain
composition; ADR-0084 raises the *fidelity* ceiling. The φ
separation probe (memory: phi-separation-falsified) established
that semantic capability lives in chain composition, not in φ
geometry, so deepening the composer's substrate is the natural
next step. ADR-0084 → 0085 (gloss-aware composer) → 0086
(predicate licensing at ratification) is the planned sequence.
* feat(adr-0084): substrate — schema parser, primitives loader, closure verifier
Substrate-only code-side for ADR-0084 (Definitional Layer for Lexicon Packs).
No composer touches the new fields yet; consumer integration is ADR-0085.
Schema (additive, default preserves byte-identity)
- LanguagePackManifest.definitional_layer: bool = False
- compiler loader propagates the flag from manifest.json
language_packs/definitions.py (new)
- GlossEntry dataclass: lemma, gloss, pos, definitional_atoms,
predicates_invited, definition_version, provenance_ids
- parse_gloss_entry(payload, *, strict) — strict mode enforces ADR-0084
§Schema validation row-by-row: required keys, typed lists, no
unknown keys, positive definition_version; lax mode preserves the
legacy two-field shape for back-compat
- load_pack_glosses(pack_id, *, strict) with cache + clear hook
- verify_definitional_closure(pack_id, *, mounted_pack_lemmas,
primitive_lemmas, strict) returning tuple[ClosureViolation, ...];
case-insensitive resolution; cycles permitted per ADR
packs/primitives/loader.py (new)
- Sister loader to packs/safety/ and packs/identity/
- PrimitivesPack frozen dataclass with .lemmas frozenset
- Gates: checksum match, kind=='primitives', definitional_layer:true,
never_auto_mutable:true, pack_id matches dir, primitive_count
cross-check, duplicate-lemma rejection, path-traversal rejection,
strict per-entry schema with allow-list
- DEFAULT_PRIMITIVES_PACK = 'en_semantic_primitives_v1'
tests/test_adr_0084_definitional_substrate.py
- 38 tests covering strict parser (each required key rejection, unknown
key rejection, empty predicates_invited allowed, empty
definitional_atoms rejected, invalid definition_version), lax
parser back-compat, load_pack_glosses (missing/strict raise/lax
skip/malformed JSON), closure verifier (same-pack/primitive/mounted/
unresolved/case-insensitive), primitives loader (every gate), and
a back-compat check that every shipped pack still ratifies with
definitional_layer=False
Lanes: smoke 67/0, cognition 120/0/1, teaching 17/0, runtime 19/0,
packs 6/0. Cognition eval byte-identical 100/91.7/100/100.
When the content PR lands (primitives.jsonl + extended glosses.jsonl
under ADR-0084-pack-content-brief.md), the gate catches any closure-rule
violation without further code change.
* feat(evals): prompt_diversity lane runner — measurement instrument for ADR-0084+
Implements the runner against the existing contract.md + 26-case v1
public split. Lane auto-discovered by evals.framework via the standard
contract + runner convention.
Runner (evals/prompt_diversity/runner.py)
- run_lane(cases, *, config, workers) -> LaneReport
- 5 metrics: intent_accuracy, versor_closure_rate (carried over from
cognition), plus the three new lane-specific metrics —
response_shape_fit, audit_in_surface_rate, gloss_quote_rate
- breakdown dict groups by (question_shape, sophistication, domain)
per contract §How to read the output
- mirrors evals.cognition.runner's parallel worker pattern
Per-shape classifier (deliberately substring/regex-simple at v1)
- predicate_identity, explanation, sequence, two_subject_contrast,
narrative, honest_disclosure
- Unknown shape => neutral pass (don't penalise new categories)
Audit-leak detector
- trust-boundary preamble markers (teaching-grounded (, pack-grounded
(, No session evidence yet.)
- dotted semantic-domain tag regex (cognition.illumination, etc.)
Gloss-quote detector
- resolves expected_terms via chat.pack_resolver.resolve_gloss
- 4-token contiguous-window match against surface (high-confidence
"gloss actually quoted", not "shared one common word")
Tests (tests/test_prompt_diversity_runner.py — 23)
- shape classifier parametrized over the six expected_shape values
- audit-leak detector parametrized over preamble + tag + clean cases
- end-to-end on v1 public:
* versor_closure_rate == 1.0 (only v1 pass threshold per contract)
* every metric in [0, 1]
* breakdown groups present with the four per-cell metrics
* diversity gate: >=5 question shapes, >=3 domains
(defends against future regressions that collapse the suite
back to a cognition-shaped fixture)
v1/public baseline (26 cases)
intent_accuracy : 65.4% (contract predicted 70-85%)
versor_closure_rate : 100.0% (only v1 pass threshold) PASS
response_shape_fit : 53.8% (contract predicted low)
audit_in_surface_rate: 42.3% (contract predicted ~100%)
gloss_quote_rate : 7.7% (contract predicted 0%)
Three baseline surprises worth noting in the report (NOT failures —
the v1 lane is explicitly there to establish the distribution):
- audit_in_surface_rate at 42% (not 100%) means the chain-walk leak
fires on ~11/26; the other 15 are honest-disclosure cases that
emit no audit envelope. Sharpens the future surface-vs-envelope
ADR's actual target: grounded surfaces specifically.
- response_shape_fit at 54% (not "low") — classifier likely has
false positives on the ", which " cause-marker. Worth tightening
once we have an ADR-0085 baseline to compare against.
- intent_accuracy at 65% (below predicted 70-85%) — classifier dips
harder on adversarial/cross-pack than expected. Real gap.
All five smoke/cognition/teaching/runtime/packs lanes still green;
core eval cognition byte-identical 100/91.7/100/100.
* feat(packs): ADR-0084 pack content (primitives + extend glosses + closure verifier) (#65)
* feat(packs): ADR-0084 pack content
* feat(packs): repair ADR-0084 definitional content
* test(adr-0084): adjust substrate manifest tests for post-#65 content reality
PR #65 flipped definitional_layer:true on 13 English packs (9 core +
4 relations + collapse-anchors). The substrate's previous test
test_existing_packs_unchanged asserted that en_core_cognition_v1 +
en_core_relations_v1 still had definitional_layer:False — which was
the right pre-content invariant but is wrong post-content.
Replace it with two complementary tests that hold against real content:
- test_non_opted_packs_default_false:
pins that packs that DIDN'T flip the flag (en_minimal_v1,
he_core_cognition_v1, grc_logos_cognition_v1) still surface
definitional_layer=False through the loader. Defends against
a future change accidentally flipping the flag on a non-opted
pack.
- test_opted_packs_carry_flag:
pins that packs that DID flip the flag (en_core_cognition_v1,
en_core_relations_v1) surface definitional_layer=True through
the loader. Proves the substrate's manifest-field propagation
works against real ratified content, not just fixture packs.
Net: +1 test, same intent (substrate ratifies the manifest field
correctly), now with real-content coverage on both sides of the gate.
All 62 ADR-0084 substrate + prompt-diversity tests pass.
Strict superset of ADR-0062's depth-1 composer. `max_depth` is the
number of follow-up hops appended beyond the initial chain:
max_depth=0 → byte-identical to single-chain surface
max_depth=1 → byte-identical to ADR-0062 composed
max_depth=2 → byte-identical to ADR-0062 when no second hop
survives, strict superset when one does
The composer surfaces content the realizer was silently dropping
from chains already ratified in `cognition_chains_v1`. Example
live lift on `"Why does light exist?"`:
composed: "light reveals truth, which grounds knowledge."
transitive(2): "...which grounds knowledge, which requires evidence."
Cycle-safe at every depth via a single visited-set; single-corpus
traversal in v1 (cross-corpus transitive deferred to a follow-up
ADR alongside ADR-0064's cross-pack model).
Both flags default False — every existing surface is preserved
byte-identically. When both `composed_surface` and
`transitive_surface` are True, transitive wins.
Implementation:
- `core/config.py`: `transitive_surface: bool = False`,
`transitive_max_depth: int = 2`.
- `chat/teaching_grounding.py`: `_resolve_followup` shared helper
refactored out of the depth-1 composer (no behavioural change),
plus new `teaching_grounded_surface_transitive(subject,
intent_tag, *, max_depth)`.
- `chat/runtime.py`: dispatch order — transitive > composed > single.
Verification:
- tests/test_transitive_surface.py: 16 new tests covering pure-fn
contract, visited-set cycle guard at every depth, runtime
integration, and the cognition-lane null-drop invariant at
`max_depth=2` (public + holdout splits).
- tests/test_composed_surface.py: 11/11 pass after the helper
refactor (ADR-0062 behaviour preserved).
- `core test --suite smoke`: 67 pass.
- `core test --suite cognition`: 120 pass, 1 skipped.
- `core test --suite teaching`: 17 pass.
- `core eval cognition`: 100 / 91.7 / 100 / 100 (byte-identical).
* chore(evals, cli): contract standardization + bench --json stdout cleanliness
End-of-session shippability pass. Three concrete fixes:
1. core/cli.py — bench --json no longer pollutes stdout
Several bench paths call scripts.run_pulse.run_pulse which prints
verbose [pulse] traces unconditionally to stdout, breaking jq /
programmatic consumers of --json output.
New _bench_stdout_guard() redirects stdout → stderr for the
duration of the bench run when --json is set. Operator still sees
the pulse trace (on stderr), but --json consumers get a clean JSON
document on stdout. Applied to all four bench paths: cost,
articulation, default suite, and --suite all.
Verified: core bench --suite determinism --json now produces
parseable JSON; human path still shows 1140 [pulse] lines.
2. evals/{frontier_compare,realizer_guard}/contract.md (new)
core/contemplation/contract.md (new)
Each new contract follows the established pattern (37 contracts
already exist under evals/<lane>/contract.md):
- What it measures
- Why it matters (structural win)
- How to run
- How to read the output
- Pass criteria table
- When it has failed and why
- Runner / module layout
Coverage:
- frontier_compare: both Lane A (CORE-only suites) and Lane B
(cross-provider prompt_battery) with explicit guardrails
against mixing — operator asks for the wrong lane combination,
runner exits 2 with helpful error.
- realizer_guard: C1/C2 articulation safety boundary — synthetic
illegal candidates rejected directly by check_surface AND
former-bug runtime prompts now produce legal articulations.
- contemplation (ADR-0080): not under evals/ since it's runtime
infrastructure that consumes eval reports — contract lives at
core/contemplation/contract.md. Documents the read-only +
SPECULATIVE-only + deterministic-replay invariants and the
shared DiscoveryCandidateSink plumbing convergence (ADR-0080).
3. evals/CLAIMS.md — Tier 2 rows added
- frontier_compare Lane A: determinism.primary_score, max_versor_condition
- frontier_compare Lane B: prompt_battery.primary_score (CORE adapter),
cross-provider artifact persistence
- realizer_guard: all_claims_supported
- contemplation: SPECULATIVE-only invariant, deterministic replay,
additive sink path, no pack mutation (all CI-pinned by tests)
Verification
------------
$ core test --suite smoke -q
67 passed in 27.22s (no regression)
$ uv run pytest -q tests/test_contemplation_loop.py \
tests/test_contemplation_pipeline_convergence.py \
tests/test_frontier_compare_cross_provider.py
27 passed in 4.87s
$ core bench --suite determinism --json 2>/dev/null | jq .results[0].passed
true (was: JSONDecodeError on prior [pulse] pollution)
* feat(evals/ui): report viewer renders Lane B cross-provider + pass-rate chart
Stop-hook caught that #62 only covered contracts — the 929-line
report_viewer.html was never audited against the new cross-provider
report shape from #61. Two real gaps:
1. Lane-aware observation drawer
The drawer hardcoded Lane A (CORE-native) fields: surface,
grounding_source, anchor_lens_mode_label, versor_condition.
Lane B (cross-provider) observations carry different fields:
provider, model, elapsed_ms, error_type, error_message.
Loading a cross-provider report rendered only the surface row
with empty `grounding` — the provider + model + timing data
was unreachable without expanding "Show raw JSON".
Fix: detect Lane B (presence of `obs.provider`) and render the
appropriate field set. Lane A still renders identically (now
also surfaces trace_hash + register_id when present, which were
silently buried in the raw JSON before).
2. Pass-rate chart per suite
The summary strip showed one aggregate Primary % across all
suites, with no way to see WHICH suite is dragging the score.
Multi-suite runs (e.g. --suite all) had to expand each panel
individually to find the failing one.
Fix: new .passrate-chart element below the summary strip,
one horizontal bar per suite showing passed/total. All-pass =
solid green, all-fail = solid red, partial = green/red split
at the pass fraction. CSS only — no new dependencies.
3. SUITE_PREAMBLES gains the prompt_battery entry so the sidebar
shows the "side-by-side surface evidence across providers"
description when loading a Lane B report.
Verified
--------
- Brace/paren/div balance unchanged (308/308 / 380/380 / 54/54)
- One <script> tag pair preserved
- Generated a real Lane B report via
`python -m evals.frontier_compare --provider core --suite prompt_battery`
for visual confirmation
Out of scope (noted for future PR)
----------------------------------
Sampled 3 `core demo` targets:
- register-tour: clean schema (all_claims_supported, claims, grid)
- audit-tour: both scene_1_* keys AND an empty scenes:[] array — inconsistent
- anti-regression: no all_claims_supported key, uses all_gates_held instead
Demo schema standardization deserves its own PR — operator tooling
would benefit from a uniform top-level success field across demos.
* docs(evals) + chore(demos): systematic audit + uniform success field
Stop-hook caught two real gaps after the contract+UI PR:
- demos had divergent success-field names (all_gates_held vs
learning_loop_closed vs claim_supported vs nested claims_supported)
- no systematic look at the 48 eval directories had been done
Both addressed concretely; remaining work captured in audit doc
rather than vaguely deferred.
1. Demo schema standardization — uniform all_claims_supported field
----------------------------------------------------------------------
All 9 ``core demo`` targets now emit a top-level
``all_claims_supported: bool`` field. Existing per-demo fields
(``all_gates_held``, ``learning_loop_closed``, ``claim_supported``,
nested ``claims_supported``) are preserved for backwards compat —
the new field is an alias derived from the demo's existing success
signal, not a replacement.
Operator tooling and the CI gate can now target
``all_claims_supported`` without knowing each demo's idiomatic
field name.
Files touched:
- evals/anti_regression/run_demo.py — adds AND of all_gates_held +
active_corpus_byte_identical
- evals/learning_loop/run_demo.py — adds AND of learning_loop_closed +
active_corpus_byte_identical
- scripts/publish_pack_measurements.py — adds AND of the three
entries in the nested claims_supported dict
- evals/long_context_cost/comparison_runner.py — adds alias for
claim_supported (singular)
The 5 demos already using ``all_claims_supported`` (audit-tour,
register-tour, anchor-lens-tour, orthogonality-tour, articulation)
are unchanged.
Verified across all 9 demos:
audit-tour : True
register-tour : True
anchor-lens-tour : True
orthogonality-tour : True
pack-measurements : True ← new alias
anti-regression : True ← new alias
learning-loop : True ← new alias
articulation : True
long-context-comparison : True ← new alias
2. docs/EVAL_AUDIT_2026-05-20.md — systematic 48-lane audit
------------------------------------------------------------
Replaces the "future PR" deferral with a concrete document.
Contains:
- Method (what was inspected for each lane).
- Summary (40/48 have contract.md; 18/48 have saved results;
empty results/ ≠ broken — most lanes regenerate on demand).
- Cross-provider relevance triage:
* 9 lanes are cross-provider-relevant and could benefit
from the prompt_battery-style adapter pattern (cognition,
english_fluency_ood, hebrew_fluency, koine_greek_fluency,
grammatical_coverage, inference_closure, multi_step_reasoning,
discourse_paragraph, foundational_*_ood, etc.).
* 29 lanes are CORE-only by design (versor closure, anchor
lens, identity divergence, provenance, etc.) — wiring
providers would be category-erroneous.
- Demo schema standardization status (this PR closes that).
- UI/UX coverage matrix.
- 5 concrete follow-up items, each focused enough for a single
PR, none requiring architectural change.
Regenerated reports
-------------------
evals/long_context_cost/results/comparison_v1.json and
evals/results/phase2_pack_measurements.json now contain the new
all_claims_supported field (auto-regenerated when validating the
schema change).
evals/frontier_compare/results/sample_core_promptbattery.json
added as a reference Lane B report so the new viewer always has
something to load on first open.
Resolves a same-day numbering collision: the prior session produced
ADR-0080 + ADR-0081 (geometric stress field, falsified) in
docs/decisions/ while the frontier-provider-adapters work was
authored as ADR-0081 in a newly-created docs/adr/ directory,
unaware of the concurrent track.
This commit takes the minimum-blast-radius fix:
- docs/adr/ADR-0081-...md → docs/adr/ADR-0082-...md
- Update title header to ADR-0082, add "Renumbered from" breadcrumb
- Update the two source-file docstrings that cite the ADR number
(providers.py, model_registry.py)
The "two ADR directories" question (docs/adr/ vs docs/decisions/)
is NOT resolved here — docs/adr/ now has exactly one entry, while
docs/decisions/ is the canonical location per CLAUDE.md. A future
PR should either consolidate or document the split; this commit
just unblocks the immediate naming collision.
Out of scope:
- Consolidating directories
- Renumbering anything in docs/decisions/
- Re-numbering on the dev's local main (already pulled into this branch)
Wires observational telemetry on the composer-vs-graph atom-set
relationship. Phase 1 is strictly observational: no enforcement,
no surface mutation, no grounding-source change, no trace-hash impact.
New telemetry fields on TurnEvent + ChatResponse:
composer_graph_atom_status ∈ {equivalent, divergent,
graph_unconstrained,
composer_no_atoms,
not_applicable, ""}
composer_atom_set_hash SHA-256 over sorted unique atoms
graph_atom_set_hash SHA-256 over sorted unique atoms
composer_graph_atom_overlap_count int
Composer atoms come from existing pack candidate metadata
(pack_semantic_domains channel through _maybe_pack_grounded_surface).
Graph atoms come from build_graph_from_input + resolve_lemma on
node.subject/predicate/obj — no prose parsing. When a grounded
composer path lacks explicit atom provenance, status is
'composer_no_atoms'.
New pure helper:
chat/atom_equivalence.py — normalize_atoms, hash_atoms,
atoms_for_graph_nodes, compare_atom_sets
Tests (tests/test_composer_graph_atom_equivalence.py):
- Pack DEFINITION path produces observable equivalence
- Divergent atom sets produce distinct hashes
- Register invariance: atom hashes + status identical across
{neutral, terse, convivial}; trace_hash also constant (R5 axis)
- Anchor lens engaged case still ASCII-only on surface
- No prose-parsing helper symbols introduced in runtime.py
(extract_candidate_surface_lemmas, surface_lemma,
parse_surface_atoms) — enforces Phase 1 boundary
Performance note: build_graph_from_input now runs on every warm
English turn (previously only when forward_graph_constraint=True).
Phase 1 accepts this cost to make the telemetry universally
available; Phase 2+ can introduce a feature flag if needed.
Validation:
- Cognition eval byte-identical: 100/100/91.7/100
- Full lane: 2864 passed, 3 skipped, 0 failed (+5 over baseline)
- Targeted lane: 72 passed in tests/test_{graph_constraint,
pack_grounding,register_tour_demo,anchor_lens_tour_demo,
orthogonality_tour_demo,realizer_guard_holdout,
composer_graph_atom_equivalence}.py
R5 (ADR-0072) shipped the register *machinery*; ADR-0074's orthogonality
tour proved the axis was decoratively orthogonal to anchor-lens but
inspection of the cognition-eval surfaces revealed two structural gaps:
* On pack-grounded DEFINITION/RECALL/COMPARISON composers, the only
realizer override any register consumed was `disclosure_domain_count`
— which only fires on the no-gloss disclosure path. Under terse_v1,
every gloss-DEFINITION cell was byte-identical to default_neutral_v1.
* The register-tour's `surfaces_vary_at_least_once` gate could be
satisfied by convivial's decorative wrapper alone, masking that
regression in CI.
R6 closes both:
Layering separation (the load-bearing fix):
* New TurnEvent/ChatResponse field `register_canonical_surface` carries
the composer output BEFORE any register transformation. The pipeline
hashes this field for `trace_hash`, preserving R5's invariant that
per-prompt trace_hash is CONSTANT across registers even while
substantive transforms produce visibly different surfaces.
Substantive transforms (`chat/register_substantive.py`):
* terse_v1 gains 3 bool knobs: `drop_provenance_tag`, `compress_gloss`,
`drop_articles` — all pure regex transforms on the canonical surface.
* convivial_v1 gains `append_semantic_domain_clause` — appends a single
bounded "Related: <atom>." clause using the lemma's pack atoms.
* default_neutral_v1 leaves overrides empty; substantive transform is
byte-identical no-op (preserves `byte_identity_null_lift`).
* C1 (ADR-0075) safety preserved: drop_articles refuses to drop
articles following `not` (avoids R3 violations); no knob combination
trips R2/R3.
Strengthened tour gate (`evals/register_tour/run_tour.py`):
* Replaces `surfaces_vary_at_least_once` with two falsifiable claims:
- `terse_substantively_differs_from_neutral_on_pack_grounded_definition`
- `convivial_substantively_differs_from_neutral_on_pack_grounded_definition`
Both restrict to DEFINITION+pack-grounded cells and require
difference beyond whitespace/punctuation.
* New claim `register_canonical_surfaces_identical` directly proves
the layering separation.
* Preserves R5's `all_grounding_sources_identical` +
`all_trace_hashes_identical`.
Pack ratification:
* Loader widened to accept `bool` for closed-set R6 keys
(drop_provenance_tag / compress_gloss / drop_articles /
append_semantic_domain_clause).
* `_KNOWN_OVERRIDE_KEYS` ratify gate extended with same.
* terse_v1 + convivial_v1 reratified with new knobs; companion
mastery reports re-sealed. default_neutral_v1 unchanged.
Invariants pinned:
* `invariant_register_canonical_surface_constant_across_registers` (new)
* `invariant_terse_substantively_distinct_from_neutral` (new)
* `invariant_convivial_substantively_distinct_from_neutral` (new)
* `invariant_realizer_no_illegal_articulation` (C1, preserved)
* `invariant_realizer_guard_byte_identity_on_currently_passing_cases`
(C1, preserved)
Verification:
* `core eval cognition`: 100.0% / 91.7% / 100.0% / 100.0% — byte-
identical under default_neutral_v1.
* `core demo register-tour`: all 5 claims green, exit 0.
* `core demo anchor-lens-tour`: green (no anchor-lens code touched).
* `core demo orthogonality-tour`: green (5/5 claims).
* Full lane: 2858 passed, 1 pre-existing failure
(test_all_preamble_explains_combined_run, carried forward
unchanged from main). 56 new R6 tests across three files.
C1 coherence floor: a deterministic verifier that runs on every
candidate surface produced by the truth path, before assignment to
ChatResponse.surface. Rejects illegal articulations and routes them
to a bounded disclosure string — admission control with a
deterministic fallback, not normalization.
Active rules (R1 deferred during ratification — see ADR):
R2_aux_neg_requires_verb — "<aux> not <wrong-POS>" rejected
R3_be_neg_requires_predicate — "<be> not <verb>" rejected
Fail-open on unknown POS, fail-closed on explicit wrong POS.
Cognition eval byte-identical (100/91.7/100/100).
Original bug class — "Light reveals truth, right?" → "Right does not
thought." — now routes to "I do not have a reviewed articulation for
that yet." with grounding_source=none, walk_surface preserving the
rejected candidate, and telemetry carrying R2_aux_neg_requires_verb.
Files:
generate/realizer_guard.py NEW — pure verifier
chat/runtime.py hook on stub + main paths
chat/telemetry.py serialize guard fields
core/physics/identity.py TurnEvent +2 fields
evals/realizer_guard/run_holdout.py NEW — 6-prompt cluster
tests/test_realizer_guard_*.py NEW — 46 tests (unit/seam/holdout)
docs/decisions/ADR-0075-*.md NEW — ratified
Invariants pinned:
invariant_realizer_no_illegal_articulation
invariant_realizer_guard_byte_identity_on_currently_passing_cases
Lanes (excluding 1 pre-existing TestDemoPreambles failure unrelated
to C1, already present at 4426f38):
smoke 67/67 cognition 120/120(+1s) teaching 17/17
packs 6/6 runtime 19/19 algebra 132/132 full 2792/2793
A single demo that walks the full 3 × 3 × 2 matrix (register × lens
× prompts, 18 cells) and pins five claims simultaneously, packaging
both single-axis invariants into one composition gate.
The single-axis tours assert opposite invariants:
register-tour : per (lens, prompt), trace_hash CONSTANT across
registers (R5 / ADR-0072).
anchor-lens-tour : per (register, prompt), engaged lens diverges
in trace_hash from the unanchored baseline
(L1.4 / ADR-0073d).
Orthogonality-tour packages both claims simultaneously across the
full matrix, plus three surface-level claims that pin the markers
operators actually see.
Composed claims (all five must hold)
A) inner_register_invariant_within_lens
For each (lens, prompt) cell, the three register runs share an
identical trace_hash. (R5 register-tour, applied 6 times:
3 lenses × 2 prompts.)
B) outer_lens_distinctness_within_register
For each (register, prompt) cell where any non-unanchored lens
engages, that engaged lens's trace_hash differs from the
unanchored baseline at the same (register, prompt).
(L1.4 anchor-lens-tour, applied 6 times: 3 registers × 2 prompts.)
C) surface_carries_register_marker_under_convivial
Every convivial cell with a non-empty surface has a non-empty
register_variant_id.
D) surface_carries_lens_annotation_when_engaged
Every engaged cell carries [lens(<id>):<mode>] in surface AND
a non-empty anchor_lens_mode_label.
E) no_substrate_glyph_leak_across_grid
No cell's surface contains Greek/Hebrew/Syriac/Arabic glyphs.
(ADR-0073c gate re-asserted across the full matrix.)
CLI wiring
core demo orthogonality-tour human-readable grid + claims
core demo orthogonality-tour --json structured report
Exit code 0 iff all five claims hold.
Files
evals/orthogonality_tour/__init__.py NEW
evals/orthogonality_tour/run_tour.py NEW
core/cli.py EDIT
- cmd_demo handler wires orthogonality-tour
- demo choices + EPILOG examples updated
tests/test_orthogonality_tour_demo.py NEW (9 tests)
docs/decisions/ADR-0074-orthogonality-tour.md NEW
Sanity check baked into tests
test_engaged_cells_appear_for_both_non_trivial_lenses pins that
grc_logos_v1 engages on knowledge in all 3 registers (3 cells)
and he_logos_v1 engages on truth in all 3 registers (3 cells).
Prevents the lift claims being vacuously satisfied by a future
engagement regression.
Lane evidence
- 9 new orthogonality-tour tests pass.
- core demo register-tour → all_claims_supported: True
- core demo anchor-lens-tour → all_claims_supported: True
- core demo orthogonality-tour → all_claims_supported: True
- python -m core.cli eval cognition → byte-identical 100/100/91.7/100.
- Full lane: 2745 passed / 4 skipped / 1 pre-existing failure
(+9 over L1.4's 2736; the one failure remains
test_all_preamble_explains_combined_run, unrelated).
No runtime / composer / loader / pack / schema changes. Pure demo
consumer of existing telemetry contracts.
L1.3 of the anchor-lens inside-out rollout — first substantive
surface lift on the substantive axis. Two ratified non-trivial
lenses engage on cognition-pack lemmas via the alignment graph,
appending [lens(<id>):<mode>] annotations to the existing
pack-grounded surface.
Two ratified lenses
grc_logos_v1 (Greek substrate)
primary_substrate : "grc"
semantic_domain_preferences: ["logos.episteme.systematic_knowledge"]
cognitive_mode_label : "systematic"
Engages on en "knowledge" via grc-core-cog-021 (ἐπιστήμη) →
en-core-cog-007 alignment edge.
he_logos_v1 (Hebrew substrate)
primary_substrate : "he"
semantic_domain_preferences: ["logos.aletheia.verity"]
cognitive_mode_label : "covenant-verity"
Engages on en "truth" via he-core-cog-002 (אמת) →
en-core-cog-002 alignment edge.
Both ratified under method anchor_lens_lifts_proposition.
Engagement rule (single)
1. Resolve en_lemma → entry_id (cognition pack).
2. For each substrate pack matching lens.primary_substrate, load
alignment.jsonl; find edges where target_id == entry_id.
3. For each such substrate lemma, if any atom in its
semantic_domains ∈ lens.semantic_domain_preferences → engage.
4. No match → None (no annotation; byte-identical surface).
The pivot is shared semantic_domain atoms surfaced via the
alignment graph — exactly the language-neutral commitment from
ADR-0073. Engagement never touches non-English surface text;
entry_ids and atom strings only.
Surface lift
no-lens : "Knowledge is X. pack-grounded (en_core_cognition_v1)."
lens-on : "Knowledge is X. pack-grounded (en_core_cognition_v1) [lens(grc_logos_v1):systematic]."
Annotation between existing provenance and trailing period.
Both metadata fields are ASCII-bounded ≤64 chars at the loader
level, so the annotation can never carry non-ASCII.
Scope deliberately narrow
L1.3 wiring restricted to pack_grounded_surface /
build_pack_surface_candidate (DEFINITION/RECALL only). Other
composers (COMPARISON / CORRECTION / PROCEDURE / NARRATIVE /
EXAMPLE / CAUSE / VERIFICATION) accept the anchor_lens kwarg via
forward-compat default UNANCHORED but do not yet consume it.
L1.3b or later broadens to those intent shapes.
Ratify gate widening
Non-null lenses must:
- have primary_substrate ∈ {grc, he, en}
- have a non-empty cognitive_mode_label
- every preferred atom must exist in at least one lemma of the
named substrate (trust boundary: operators cannot ship a lens
pointing at atoms not on disk).
Method: anchor_lens_lifts_proposition. Null lenses still ratify
under byte_identity_null_lift (L1.2 method).
Seam allow-list widening
Truth-path modules (cognition / trace / pipeline / intent /
propagation / vault / algebra) still refused. Composer-side
imports from chat/pack_grounding.py now permitted — the same way
ADR-0069's R2 widened the register seam.
New invariants pinned (3)
tests/test_anchor_lens_engagement_unit.py (14 tests) — resolver
returns mode label only on intended substrate × en lemma pair;
case-insensitive; engagement None under null lens; synthetic
lens with unmatched atom returns None; annotation is pure ASCII.
tests/test_anchor_lens_lifts_proposition.py (17 tests) — grc
engages on knowledge only, he engages on truth only,
cross-lens isolation, three-way distinctness, replay determinism
per (lens × prompt), register-tour seam holds within each lens
scope (orthogonality CI-pinned, parametrized over 4 lens
choices).
tests/test_anchor_lens_no_glyph_leak.py (5 tests) — hard
block-scoped gate: Greek (U+0370..03FF, U+1F00..1FFF), Hebrew
(U+0590..05FF), Syriac, Arabic. Stylistic punctuation
(em-dash etc.) explicitly allowed; em-dash predates L1.3 by a
wide margin and is not a substrate-leak risk. Tested per-lens
across every cognition case + direct lens-metadata ASCII check.
Lane evidence
74 anchor-lens tests pass (37 from L1.2 + 37 new).
python -m core.cli eval cognition → public 100/100/91.7/100
byte-identical (lens=None / default_unanchored_v1).
core demo register-tour --json → all_claims_supported: True
(R5 seam still holds; L1.3 doesn't perturb presentation axis).
Full lane: 2706 passed / 4 skipped / 1 pre-existing failure
(+37 over L1.2's 2669; the one failure remains
test_all_preamble_explains_combined_run, unrelated).
Files
packs/anchor_lens/grc_logos_v1.json NEW
packs/anchor_lens/grc_logos_v1.mastery_report.json NEW
packs/anchor_lens/he_logos_v1.json NEW
packs/anchor_lens/he_logos_v1.mastery_report.json NEW
scripts/ratify_anchor_lens_packs.py EDIT
LENS_IDS adds grc_logos_v1 / he_logos_v1; gate widened.
chat/pack_grounding.py EDIT
_resolve_anchor_lens_mode, _maybe_append_anchor_lens_annotation,
_substrate_lexicon_by_entry_id, _en_lemma_to_entry_id.
build_pack_surface_candidate + pack_grounded_surface gain
anchor_lens kwarg (default UNANCHORED).
chat/runtime.py EDIT
Thread self.anchor_lens into pack_grounded_surface() call.
tests/test_anchor_lens_pack_seam.py EDIT
Doc-comment updated for L1.3 allow-list.
tests/test_anchor_lens_* NEW (3 files)
docs/decisions/ADR-0073c-anchor-lens-composer-wiring.md NEW
Umbrella ADR-0073 ratified (Accepted); L1.1 content phase
(ADR-0073a) landed. Pure pack enrichment — no runtime code, no
composer change, no test of behaviour. Substrate prerequisite for
the L1.2–L1.4 phases.
Greek additions (grc_logos_cognition_v1, 20 → 29 entries)
Knowledge family (English collapses to `knowledge`):
- ἐπιστήμη logos.episteme.systematic_knowledge
- σύνεσις logos.synesis.insight
(γνῶσις at grc-core-cog-007 unchanged — treated as the
experiential variant by the L1.3 lens config)
Love family (English collapses to `love`):
- ἀγάπη logos.agape.covenant_love
- φιλία logos.philia.companion_love
- ἔρως logos.eros.passionate_love
- στοργή logos.storge.familial_love
Time family (English collapses to `time`):
- αἰών logos.aion.age_era
- χρόνος logos.chronos.clock_time
- καιρός logos.kairos.opportune_moment
Hebrew additions (he_core_cognition_v1, 20 → 23 entries)
- חסד logos.chesed.covenant_loyalty
- שלום logos.shalom.wholeness_peace
- צδק logos.tzedek.right_order
Alignment.jsonl on both cognition-tier packs (previously only the
micro packs carried alignment)
- grc_logos_cognition_v1/alignment.jsonl — 20 edges: three-way core
dyads (word / truth / light / life / beginning / wisdom),
knowledge-family → en collapse, ἀγάπη↔חסד covenant-love pairing
(weight 0.86, Septuagintal), `cross_lang.no_english_collapse`
annotations for love + time families pointing at
`en-collapse-<family>` sentinel ids (weight 0.0).
- he_core_cognition_v1/alignment.jsonl — 7 edges: core dyads to en,
חסד↔ἀγάπη covenant pairing, no-english-collapse annotations for
חסד / שלום / צδק.
Manifest checksums refreshed per CLAUDE.md doctrine
- grc_logos_cognition_v1: b45bcf581cee… → 0f9436675707…
- he_core_cognition_v1: dee1e8c6ad9a… → 22145d008185…
Design decisions
- Existing 20 + 20 lemma atoms untouched — downstream tests /
composers / teaching chains keep referencing the same atoms.
Only new lemmas carry the distinguishing atoms.
- `cross_lang.no_english_collapse` edges are metadata not data
(sentinel target ids, weight 0.0). Their purpose is letting the
alignment graph answer "does English split this family?" without
forcing an artificial English lemma.
- Every new entry carries `adr-0073a:hand_authored:2026-05-19` in
its `provenance_ids` so future audits can find the L1.1 cohort
deterministically.
Verification
- python -m language_packs verify grc_logos_cognition_v1 → OK
- python -m language_packs verify he_core_cognition_v1 → OK
- python -m language_packs compile <both> → 29 / 23
manifold points; spot-check confirms καιρός / צδק resolve.
- python -m core.cli eval cognition → public
100 / 100 / 91.7 / 100 byte-identical (new lemmas sit on disk but
no composer references them yet).
- python -m core.cli test --suite cognition → 120/1 pass
- python -m core.cli test --suite smoke → 67/0 pass
- python -m core.cli test --suite full → 2632 passed
/ 4 skipped / 1 pre-existing failure (test_all_preamble_explains_
combined_run rename drift, unrelated).
- core demo register-tour → exit 0
(R5 seam still holds; L1.1 doesn't touch register pathway).
What L1.1 deliberately does NOT do
- No AnchorLens class (that's L1.2 / ADR-0073b).
- No composer wiring (L1.3 / ADR-0073c).
- No --anchor-lens CLI flag or demo (L1.4 / ADR-0073d).
- No teaching corpus in non-English (post-L1).
Umbrella ADR for the substantive-variation axis that composes
orthogonally against register (ADR-0068..0072). Drafted only;
status Proposed. No code, no pack, no test landed.
Architecture summary
- Anchor lens is the substantive axis: register varies surface text
while keeping grounding_source / trace_hash byte-identical;
anchor lens deliberately moves both because the proposition
itself changes when the substrate changes.
- Pivot is shared `semantic_domains` atoms (already on disk across
grc / he / en cognition packs), not transliteration tables — the
seam stays language-neutral so future substrates compose without
touching anchor-lens code.
- English compound phrasing only at the surface ("knowing-as-
experience", "knowing-as-system"); Greek / Hebrew glyphs live in
audit / provenance fields only. L1.3 invariant
`anchor_lens_no_glyph_leak` is a hard gate.
Four-phase rollout (mirrors R1–R5 cadence)
L1.1 content phase — distinction-bearing lemma additions
(ἐπιστήμη / σύνεσις / ἀγάπη-φιλία-ἔρως-στοργή / αἰών-χρόνος-
καιρός; חסד / שלום / צδק) + alignment.jsonl on the cognition-
tier packs. No code. Prerequisite for every later phase.
L1.2 AnchorLens pack class + loader + `default_unanchored_v1`
sentinel. Null-lift CI invariant pinned.
L1.3 First non-trivial lenses (`grc_logos_v1`, `he_logos_v1`)
wired into chat/pack_grounding.py composers. Proposition-
lift invariant + glyph-leak gate pinned.
L1.4 Telemetry (TurnEvent + ChatResponse gain anchor_lens_id),
`core chat --anchor-lens` flag, `core demo anchor-lens-tour`
asserting trace_hashes_distinct_across_lenses (opposite of
register-tour's claim — both must hold).
Three honest gaps blocking L1.2+
- Distinction-bearing lemmas absent from cognition packs.
- No reviewed teaching corpus for non-English (cognition_chains,
relations_chains, cross_pack_chains all en-only).
- No realizer infrastructure for cross-lingual surface composition.
L1.1 (pure content) closes all three for the cognition tier.
Orthogonality claim — load-bearing
register-tour : per prompt, fix lens, vary register → trace_hash CONSTANT
anchor-lens-tour : per prompt, fix register, vary lens → trace_hash DISTINCT
Both must continue to hold; failure of either breaks the seam.
Records the deterministic, grounded, multi-clause articulation
benchmark that the discourse-planner work has stabilised. Mirrors
the format of teaching_loop_bench.md so the four sub-benches in
benchmarks/articulation.py have a load-bearing reference document.
Headline:
* 20 independent ChatRuntime instances × 4 prompts (EXPLAIN /
PARAGRAPH / COMPOUND / WALKTHROUGH) produce 4 unique surfaces —
byte-identical determinism on the articulation path with
RuntimeConfig(discourse_planner=True).
* Every visible token traces to a pack lemma, pack gloss, reviewed
teaching-chain entry, or fixed-template connective from the
closed five-entry _MOVE_CONNECTIVE table. No synthesis.
* discourse_planner sub-bench:
cases: 4
articulate_sentence_rate: 1.0
disclosure_sentence_rate: 0.0
multi_sentence_rate: 1.0
* Compound prompt ("What is truth, and why does it matter?") emits
6 distinct grounded sentences with cross-part fact dedup, no
anchor repetition.
* Walkthrough mode walks the teaching-chain edge graph up to 3 hops,
cycle-safe, final hop as CLOSURE; no chain ⇒ degrades to ANCHOR +
SUPPORT rather than fabricating steps.
Doc explains the partitioned predicate contract
(articulate + disclosure + unarticulate = 1.0, total and disjoint)
so future readers know why ``multi_sentence_rate`` alone is not the
headline.
Companion docs cross-linked: discourse_runtime_baseline_2026-05-19.md
(lane-level delta table), the two new isolation lanes
(compound_intent_decomposition, walkthrough_chain), and the
partitioned multi_sentence_response contract.
Extends ``generate/intent.py:_RULES`` with three new expository
patterns so the upstream subject-extraction gap that the dedup
revealed is closed:
* ``^explain\s+`` → DEFINITION
* ``^(write|compose|draft) (a )?(short|brief)?
paragraph (about|on)\s+`` → DEFINITION
* ``^paragraph (about|on)\s+`` → DEFINITION
Rules placed AFTER the NARRATIVE family so ``Tell me about X`` and
``Describe X`` continue to route to NARRATIVE. Subject extraction
re-uses ``_normalize_subject`` so articles and trailing punctuation
are stripped: ``Explain the parent.`` → subject ``parent``.
``ResponseMode`` is untouched and remains orthogonal: the same prompts
still classify as ``EXPLAIN`` / ``PARAGRAPH`` independently.
20 new tests pin: each rule's expected subject, response-mode
preservation, NARRATIVE/EXAMPLE/existing-DEFINITION rules unchanged.
Lane re-measurement (multi_sentence_response, 21 cases):
flag off: multi=0.1429, primed_multi=0.0000, conn=0.5385, grounded=0.8571
flag on : multi=0.9048, primed_multi=1.0000, conn=0.8462, grounded=0.8571
Combined lift over the original (pre-wiring) baseline:
* multi_sentence_rate: +70pp on the substantive predicate
* primed_multi_sentence_rate: +50pp (0.5 → 1.0 post-classifier)
* connective_present_rate: +74pp (0.10 → 0.85)
* grounded_rate: +39pp (0.47 → 0.86)
Cognition eval byte-identical: public 100/100/91.7/100, holdout
100/100/83.3/100 — these prompts aren't in cognition cases, and the
new rules don't perturb any rule that fires for cognition prompts.
Conversational thread coherence unchanged.
docs/evals/discourse_runtime_baseline_2026-05-19.md updated with the
full delta table; the planner is now load-bearing across the warm
and cold pack/teaching paths and the lane measures real capability
rather than punctuation artifacts.
Two new intent shapes + composers turn the runtime's corpus
density into operator-visible articulation. Both consult the
cross-corpus aggregator from ADR-0064; no new ratification needed.
P3.3 — chat/narrative_surface.py + IntentTag.NARRATIVE.
Classifier patterns (registered BEFORE generic DEFINITION):
^tell\s+me\s+about\s+
^describe\s+
^what\s+(?:can|do)\s+you\s+(?:say|know)\s+about\s+
narrative_grounded_surface(subject, max_clauses=4) walks every
reviewed chain rooted on subject across all registered teaching
corpora. Dedupes by (connective, object) — cause + verification
carrying the same predicate emit one clause, not two. Sorts by
(intent, connective, object) for replay stability.
Surface format:
"{X} — narrative-grounded ({corpus_ids}): {dX1}; {dX2}.
{X} {conn1} {O1} ({dO1}); {X} {conn2} {O2} ({dO2}).
No session evidence yet."
Cross-corpus subjects (e.g. mother in relations_v2) emit
narrative-grounded (relations_chains_v2) tag; cognition subjects
emit cognition_chains_v1 tag. Multi-corpus subjects (when
applicable) emit composite "corpus_a + corpus_b" tag.
P3.4 — chat/example_surface.py + IntentTag.EXAMPLE.
Classifier patterns:
^(?:give|show)\s+(?:me\s+)?an?\s+(?:example|instance)\s+of\s+
^example\s+of\s+
example_grounded_surface(object_lemma, max_examples=3) walks chains
where the lemma is the OBJECT — inverts the typical subject-keyed
access pattern. Dedupes by subject; sorts by (intent, subject,
connective).
Surface format:
"{X} — example-grounded ({corpus_ids}): {dX1}.
Example: {subj1} {conn1} {X}; {subj2} {conn2} {X}.
No session evidence yet."
Cross-cutting:
- Both intents added to _OOV_INTENT_TAGS — fall through to OOV
invitation when subject is unknown (Phase 2 gradient discipline).
- Both tagged grounding_source="teaching" (same provenance tier
as the existing teaching_grounded_surface).
- No prose generation, no new mutation surface.
Live verification:
> Tell me about truth.
[teaching] truth — narrative-grounded (cognition_chains_v1):
cognition.truth; logos.core. truth grounds knowledge
(cognition.knowledge); truth requires evidence (cognition.evidence).
> Give me an example of knowledge.
[teaching] knowledge — example-grounded (cognition_chains_v1):
cognition.knowledge. Example: truth grounds knowledge;
understanding requires knowledge; evidence grounds knowledge.
> Tell me about mother.
[teaching] mother — narrative-grounded (relations_chains_v2):
kinship.parent.female. mother precedes daughter (kinship.child.female).
> Describe photosynthesis.
[oov] I haven't learned 'photosynthesis' yet (intent: narrative). ...
ADR-0066 (this commit completes the ADR). 30 new tests passed.
Full lane: 2067 passed, 2 skipped, 0 failed in 2:32.
Mirrors the chain-gap pipeline (Phase 1.1+1.2) for vocabulary gaps:
the OOV invitation surface (P2.1) now emits structured signals that
operators can aggregate, rank, and auto-promote into reviewed
PackMutationProposal candidates — closing the OOV loop the same way
Phase 1 closed the chain loop.
Three new modules + two new CLI surfaces:
teaching/oov_sink.py.
OOVCandidate dataclass mirroring teaching.discovery.DiscoveryCandidate.
OOVBufferSink (in-memory) + OOVMonthlyFileSink (append-only JSONL
under <root>/<YYYY>/<YYYY-MM>.jsonl — same layout as discovery sink
so the aggregator reuses the file-walk machinery).
hash_oov_candidate_id(token, intent, trace_hash) — deterministic
32-char hex id matching DiscoveryCandidate's replay invariant.
format_oov_candidate_jsonl — sorted-keys compact JSONL line.
teaching/oov_gaps.py.
aggregate_oov_gaps(root, since, sample_limit) groups emitted
candidates by token, tracks intent-shape union (a token asked under
multiple intents is a stronger curriculum signal), splits
boundary_clean from boundary_tainted counts, supports --since
YYYY-MM filtering via the sink's file naming convention.
Pure reader; never mutates the sink. Deterministic ordering:
(count desc, token asc).
teaching/oov_promotion.py.
promote_oov_gaps(gaps, threshold, include_tainted, suggested_packs)
lifts threshold-crossing tokens to OOVPromotion records.
- boundary_clean_count gates promotion by default (tainted-only
tokens may indicate the prompt hit a safety axis rather than a
vocab gap).
- --include-tainted flag for operator override.
- threshold < 1 raises.
- queue_id deterministic: ``oov:<token>@<threshold>`` — diffable
across runs.
- suggested_packs lists mounted packs but does NOT recommend one
— domain inference is out of scope (would require a stochastic
classifier). Operator picks the destination.
Runtime wiring:
ChatRuntime.attach_oov_sink(sink) mirrors attach_discovery_sink.
Runtime emits one OOVCandidate JSONL line per turn whose
grounding_source == "oov", no-op when no sink is attached.
Intent classifier is now invoked when EITHER sink is attached
(was: only discovery sink) — both downstream paths need it.
CLI:
core teaching oov-gaps [--top N] [--since YYYY-MM] [--root PATH]
[--sample-limit N] [--json]
core teaching oov-queue [--threshold N] [--include-tainted]
[--root PATH] [--since YYYY-MM] [--json]
ADR-0065 documents the full design (five-tier honesty gradient,
P2.1-P2.4 architecture). README.md updated with the ADR-0065
index entry.
Verification:
tests/test_oov_pipeline.py 24 passed
Operator workflow round-trip verified live:
> rt.attach_oov_sink(sink); rt.chat("What is photosynthesis?")
→ sink receives:
{"boundary_clean":true,"candidate_id":"f51bf8...",
"intent":"definition","token":"photosynthesis","trigger":"unresolved_subject",
"source_turn_trace":"","review_state":"unreviewed"}
> core teaching oov-gaps --root /tmp/oov_demo
→ ranked table by count, intent-set per token
> core teaching oov-queue --root /tmp/oov_demo --threshold 2
→ promoted tokens + suggested mounted packs
Full lane: 2005 passed, 2 skipped, 0 failed in 2:34 (xdist).
ADR-0064 is the corpus-layer sibling of ADR-0063. The teaching-grounded
surface composer was hardcoded to cognition_chains_v1, so kinship CAUSE/
VERIFICATION prompts fell through to the universal disclosure even though
en_core_relations_v1 was mounted on the live runtime (ADR-0063).
Architectural change in chat/teaching_grounding.py:
- New TeachingCorpusSpec dataclass (corpus_id, path, pack_id).
- TEACHING_CORPORA tuple registers every active corpus. Each
corpus is 1:1-bound to one lexicon pack — cross-domain triples
deferred per docs/teaching_order.md §5.
- _load_corpus(spec) loads one corpus with pack-residency scoped
to its declared pack.
- _all_chains_index() aggregates across all registered corpora
(first-match-wins; cognition first preserves byte-identity).
- _pack_for_corpus(corpus_id) → bound pack lexicon.
- clear_teaching_caches() atomic cache invalidation.
- TeachingChain gains corpus_id field → surface tag follows resolving corpus.
Wiring updates:
- teaching_grounded_surface + teaching_grounded_surface_composed
consult _all_chains_index; surface tag follows chain.corpus_id.
- teaching/discovery.py gate uses chat.pack_resolver.is_resolvable
(any mounted pack) + _all_chains_index (any registered corpus).
- teaching/replay.py _swap_corpus_path rewrites the registry path
+ clears all teaching caches during the gate's transient phase.
Active corpus bytes unchanged (replay invariant preserved).
- evals/learning_loop/run_demo.py scene-5 swap mirrors the new
pattern so the demo still grounds against transient corpora.
Back-compat preserved: _corpus_index, _CORPUS_PATH, TEACHING_CORPUS_ID
remain cognition-corpus-specific for audit/replay consumers.
Phase 1.4 — relations_chains_v1 seeded with 7 reviewed kinship chains:
cause_parent_precedes_child
cause_child_follows_parent
cause_ancestor_precedes_descendant
cause_descendant_follows_ancestor
cause_family_grounds_parent
verification_child_requires_parent
verification_descendant_requires_ancestor
5 of 8 relations lemmas covered. All connectives already humanised.
Strict pack-internal to en_core_relations_v1 (no cross-domain in v1).
Seed pattern matches cognition_chains_v1's original pre-ADR-0055 seed.
Live verification:
> Why does parent exist?
parent — teaching-grounded (relations_chains_v1):
kinship.ascendant.direct; kinship.parent.
parent precedes child (kinship.descendant.direct).
grounding_source = teaching
Cognition eval byte-identical to pre-ADR baseline:
public: intent 100% / surface 100% / term 91.7% / closure 100%
holdout: intent 100% / surface 100% / term 83.3% / closure 100%
Lanes green: smoke 67 / cognition 121 / teaching 17 / packs 6 /
runtime 19 / algebra 132 / full 1933 passed.
ADR-0063 closes the ADR-0048/0050/0053/0061 hardcoded-cognition-pack
asymmetry. New chat/pack_resolver.py provides resolve_lemma(lemma,
pack_ids) → (resolving_pack_id, semantic_domains) across an ordered
tuple of mounted lexicon packs (first-match-wins, lru_cache per-pack).
Surface composers in chat/pack_grounding.py now consult the resolver
instead of a hardcoded en_core_cognition_v1. en_core_relations_v1
joins RuntimeConfig.input_packs defaults; kinship lemmas now ground
on the live path:
> What is a parent?
parent — pack-grounded (en_core_relations_v1):
kinship.ascendant.direct; kinship.parent; biology.progenitor.
No session evidence yet.
Cross-pack comparison (knowledge × parent) renders composite tag
(en_core_cognition_v1 × en_core_relations_v1). Cognition lane
remains byte-identical: cognition is resolved first and the surface
format for cognition lemmas is unchanged.
Cognition eval (byte-identical to pre-ADR baseline):
public → intent 100% / surface 100% / term 91.7% / closure 100%
holdout → intent 100% / surface 100% / term 83.3% / closure 100%
Curated lanes green: smoke 67 / cognition 121 / teaching 17 /
packs 6 / runtime 19 / algebra 132.
New tests: test_pack_resolver.py (28) + test_cross_pack_grounding.py
(17). test_en_core_relations_v1_pack.py: default-input-packs guard
inverted. test_pack_grounding.py: two stale ADR-0048 tests rewritten
(premises invalidated by ADR-0052/0061; now use fully-out-of-pack
prompts).
chat/teaching_grounding.py UNCHANGED — cognition_chains_v1 corpus
stays cognition-only. Cross-pack teaching corpora are the natural
ADR-0064.
Per teaching_order.md §5 — pick one commercial domain and run the
full 1→4 progression inside it before opening a second. Kinship is
the doctrinally classic starter: tight DAG, well-bounded primitives,
and orthogonal to the cognition pack.
Lemmas (8): parent, child, sibling, family, ancestor, descendant,
spouse, offspring. Each carries ≥2 semantic_domains under a
deterministic taxonomy (kinship.*, lineage.*, biology.*, social.*).
Deliberate exclusions:
- `person` — lives in en_core_cognition_v1; orthogonality test
pins that boundary.
- Specializations (mother/father/son/daughter/grandparent/...) —
derived from v1 primitives; land in v2 after v1 produces
reviewed chains.
- Quantifiers (one/two/many) — separate domain
(en_core_quantification_v1); cross-domain triples come last.
- Verbs of relation (begets/marries/...) — separate composer
work; no relations_chains_v1.jsonl yet.
Engagement is opt-in:
- Pack is NOT in RuntimeConfig.input_packs defaults.
- Programmatic mount via RuntimeConfig(input_packs=(..., "en_core_relations_v1")).
- CLI: core chat --pack en_core_relations_v1 (existing surface).
- Default-not-mounted preserves the cognition lane unchanged
until cross-pack teaching-grounded composition exists.
- language_packs/data/en_core_relations_v1/lexicon.jsonl
— 8 entries, JSONL format matching en_core_cognition_v1.
- language_packs/data/en_core_relations_v1/manifest.json
— pack_id, language, role=operational_base, checksum
(SHA-256 of lexicon bytes per CLAUDE.md pack-discipline),
version 1.0.0, determinism_class D0, oov_policy tagged_fallback.
- tests/test_en_core_relations_v1_pack.py — 6 tests pin:
checksum-match load, lemma roster, per-lemma primary domain,
≥2 domains/lemma (composer headroom), zero collision with
cognition pack (kinship DAG stays orthogonal), pack-not-in-
default-input-packs (opt-in engagement contract).
- docs/curriculum/relations_pack_v1.md — full pack log:
rationale per included/excluded lemma, opt-in engagement path,
4-step ADR roadmap (cross-pack composition → first kinship
chains → pronoun v2 → cross-domain triples).
Mounted-manifold sanity check (en_core_cognition_v1 +
en_core_relations_v1): 93 lemmas combined, no collisions, both
packs' surfaces individually addressable.
Lanes (regression): smoke 67 / packs 6 / algebra 132 / relations-pack 6.
The non-negotiable field invariant (versor_condition < 1e-6) is
unaffected: this is pure pack data + a contract test.
Pre-ADR-0062, the teaching-grounded composer emitted exactly one
reviewed chain per surface — "light reveals truth" — even when the
corpus already contained an immediate follow-up "truth grounds
knowledge". With 21 active chains after curriculum saturation v2,
many grounded prompts had a corpus-ratified follow-up the composer
silently dropped.
ADR-0062 adds the composed composer + an opt-in config flag:
flag OFF (default):
light — teaching-grounded (cognition_chains_v1): cognition.illumination;
logos.core. light reveals truth (cognition.truth). No session evidence yet.
flag ON:
light — teaching-grounded (cognition_chains_v1): cognition.illumination;
logos.core. light reveals truth (cognition.truth), which grounds
knowledge (cognition.knowledge). No session evidence yet.
Follow-up resolution:
- prefer cause; fall back to verification (deterministic preference)
- cycle guard: 1-step cycles (A→B, B→A) blocked
- pack-residency guard: follow-up's object must be pack-resident
- bounded depth: v1 follows exactly one hop
- degrades to single-chain BYTE-IDENTICALLY when no follow-up
survives the guards (drop-in replacement)
Trust-boundary invariants preserved:
- Every visible non-template token is lemma / pack-domain /
humanize_predicate connective / template constant. Only added
template constant: ", which "
- Deterministic: same chains → same surface bytes
- Default-False flag pattern mirrors ADR-0047/0058
- `versor_condition < 1e-6` invariant untouched (surface composition only)
Cognition lane null-drop invariant CI-pinned:
Composed mode emits a strictly LONGER surface (extra follow-up
clause); every expected_term passing flag-OFF must still pass flag-ON.
Asserted in test_cognition_lane_metrics_unchanged_with_composed_flag
for both public and holdout splits. If a future change drops tokens,
the test fails as a deliberate regression.
public flag OFF: intent 100% / surface 100% / term 91.7% / versor 100%
public flag ON : intent 100% / surface 100% / term 91.7% / versor 100% (identical)
holdout flag OFF: intent 100% / surface 100% / term 83.3% / versor 100%
holdout flag ON : intent 100% / surface 100% / term 83.3% / versor 100% (identical)
Live-prompt lift visible on ~12 of 21 active chains; the rest hit
cycle or pack-residency guards. Saturation v2's clusters were
authored partly with composition in mind (thought→meaning→
understanding, inference→evidence→knowledge, etc.).
- core/config.py — `RuntimeConfig.composed_surface: bool = False`
- chat/teaching_grounding.py — `teaching_grounded_surface_composed`
sibling to `teaching_grounded_surface`
- chat/runtime.py — dispatch branch in `_maybe_pack_grounded_surface`
selects composed vs single-chain based on config flag
- tests/test_composed_surface.py — 11 tests pin: function-level
(None on no chain / degrades when no follow-up / two-clause when
follow-up exists / includes intermediate + final domains /
deterministic / cycle guard / trust label preserved); runtime
integration (default single-chain / flag-on composed / frozen
config); cognition-lane null-drop invariant.
Lanes (regression): smoke 67 / cognition 121 / teaching 17 /
composed-surface 11 — all green.
Second curriculum unit through the production operator surfaces.
Pure saturation — no cognition-lane lift expected (the eval splits
test fixed 32 cases that don't overlap with this unit's subjects),
but the live-prompt grounding surface expands materially: seven
prompts that previously fell through to disclosure now route to
deterministic teaching-grounded surfaces.
Three coherent clusters:
A. Cognition-source
cause_thought_reveals_meaning
cause_question_reveals_understanding
cause_recall_reveals_memory
B. Conceptual structure (bidirectional)
cause_definition_grounds_concept
verification_concept_requires_definition
C. Semantic content
cause_meaning_grounds_understanding
cause_analogy_reveals_relation
All pack-consistent (subject + object in en_core_cognition_v1),
canonical predicates (reveals / grounds / requires), each opens a
previously-empty (subject, intent) cell.
Replay-equivalence gate reported replay_equivalent=True for all
seven proposals (public cognition lane byte-identical pre/post
every accept).
Cognition lane:
public : intent 100% / surface 100% / term 91.7% / versor 100% (unchanged)
holdout : intent 100% / surface 100% / term 83.3% / versor 100% (unchanged)
Saturation lift is visible at the live-prompt level, not at the
eval level:
Why does thought exist? → [teaching] thought reveals meaning (...)
Why does a question exist? → [teaching] question reveals understanding (...)
Why does definition exist? → [teaching] definition grounds concept (...)
Why does meaning exist? → [teaching] meaning grounds understanding (...)
Why does an analogy exist? → [teaching] analogy reveals relation (...)
Does a concept require definition? → [teaching] concept requires definition (...)
Why does recall exist? → [teaching] recall reveals memory (...)
Why saturation matters: the cognition pack has 78 lemmas; we've
now covered ~21 (subject, intent) cells of the hundreds available.
Without saturation, prompts outside the 32 fixed eval cases are
coin-flips between vault recall and disclosure. Saturation moves
marginal prompts to deterministic teaching-grounded surfaces — the
foundation the composed-surface ADR (next) will compose over.
- teaching/cognition_chains/cognition_chains_v1.jsonl — 15 → 22 lines
(7 appends). Active set: 14 → 21 chains.
- teaching/proposals/proposals.jsonl — 7 new (created → replay →
transition → accepted_corpus_append) event sequences appended.
- docs/curriculum/cognition_saturation_v2.md — full curriculum log:
cluster rationale, live-prompt lift, operator-wall-time profile,
saturation-state-of-the-pack.
Lanes (regression check):
core test --suite smoke 67 passed
core test --suite cognition 121 passed
core test --suite teaching 17 passed
The non-negotiable field invariant (versor_condition < 1e-6) is
unaffected: this is corpus growth only; no code path changed.
Pre-ADR-0061 every "How do I X?" question fell through to the
universal disclosure even when X was a pack-resident lemma. The
teaching corpus carries CAUSE/VERIFICATION chains only — procedural
knowledge is fundamentally different in kind from propositional
claims and deserves its own ratification path (deliberately out of
scope; a future parallel `procedure_chains_v1.jsonl` schema is
discussed in the ADR's non-goals).
ADR-0061 adds the honest cold-start fallback: ground the topic in
pack semantic_domains and note explicitly that ratified step-by-step
guidance does not exist yet.
Surface format:
"procedure-grounded ({pack_id}): {lemma} ({d1}; {d2}).
Step-by-step guidance for {lemma} is not yet ratified
in this session."
Selector — **last** pack-resident lemma in the verb-phrase subject:
"define a concept" → concept (object beats verb)
"verify a claim" → verify (verb wins when object is OOV)
"correct an error" → correct
"learn this" → learn
"do stuff" → None (falls through to universal disclosure)
Stopwords: only `be` and `have` (dialogue fillers). Procedure verbs
are deliberately NOT stopworded so the verb-as-fallback rule fires
when the object is OOV — keeps surface coverage.
Trust-boundary invariants:
- Every visible non-template token is lemma / pack-domain / template.
- Deterministic: same subject_text → same bytes.
- Returns None for fully-unknown utterances → universal disclosure
fires. Never fabricates surface from nothing (ADR-0053 contract).
- "not yet ratified" trust-label preserved.
Cognition lane lift:
public : intent 100% / surface 100% / term 91.7% / versor 100% (unchanged)
holdout : intent 100% / surface 94.7%→100.0% / term 79.2%→83.3% / versor 100%
Two cases fixed:
- procedure_define_010 ("How do I define a concept?") — surface +
term `concept` now captured.
- procedure_verify_034 ("How do I verify a claim?") — surface only
(case has no expected_terms; the verb fallback grounds it).
Combined effect: holdout `surface_groundedness` closes to 100%; 4 of
5 architectural holdout misses now resolved (this ADR + ADR-0060 +
the supersede from epistemology v1). Remaining 2 are UNKNOWN-intent
cases (unknown_spirit_041, unknown_word_018) — out of scope; deserve
their own ADR with distinct selector semantics.
- chat/pack_grounding.py — `_extract_procedure_topic_lemma` helper +
`pack_grounded_procedure_surface` composer.
- chat/runtime.py — import + dispatch branch for `IntentTag.PROCEDURE`.
- tests/test_procedure_surface.py — 15 tests pin: extraction
(last-wins / verb-by-elimination / be+have skipped / None on empty /
strips punctuation / case-insensitive); surface (contains lemma /
contains domains / pack_id / "not yet ratified" label / None for
no-pack-lemma / deterministic); end-to-end through ChatRuntime.
Lanes (regression): smoke 67 / cognition 121 / teaching 17 /
procedure 15 — all green.
The non-negotiable field invariant (versor_condition < 1e-6) is
unaffected: this ADR changes surface composition only.
ADR-0053's cold-start CORRECTION surface was topic-blind: a user who
said "Actually, truth requires evidence" got a response referencing
`correction` but never `truth`. The holdout case correction_truth_040
expected `term=['truth']` and missed — one of the architectural gaps
surfaced by the epistemology v1 curriculum unit.
ADR-0060 closes that gap by weaving the first pack-resident topical
lemma from the utterance into a fixed-template extension:
correction received — pack-grounded ({pack_id}):
{correction_domains}. Noted topic: {lemma} ({lemma_domains}).
No prior turn in this session to correct yet.
Selection rule (deterministic, left-to-right token order):
- skip stopwords: `correction`, `correct`, `be`, `have`
- pick first pack-resident lemma
- if none found → ADR-0053 topic-less template byte-identically
Trust-boundary invariants preserved:
- Every visible non-template token is still lemma / pack-domain / template
- Deterministic: same text → same bytes
- Backward compatible: existing 15 ADR-0053 tests pass byte-identically
- "No prior turn in this session to correct yet." trust label kept
Cognition lane lift:
public : intent 100% / surface 100% / term 91.7% / versor 100% (unchanged)
holdout : intent 100% / surface 94.7% / term 75.0%→79.2% / versor 100%
The +4.2pp matches the single-case fix exactly (correction_truth_040).
Remaining 3 holdout misses (procedure_define_010, unknown_spirit_041,
unknown_word_018) are out of scope for this ADR.
- chat/pack_grounding.py — `_extract_correction_topic_lemma` helper +
optional `text` parameter on `pack_grounded_correction_surface`.
- chat/runtime.py — single-line call-site change to pass `text` through.
- tests/test_correction_topic_lemma.py — 14 new tests pin:
extraction (first lemma / skips correction / skips fillers / None on
empty / strips punctuation / case-insensitive); surface (contains
corrected lemma / contains topic domains / degrades to ADR-0053
byte-identically / preserves trust label / deterministic / correct
pack_id); end-to-end (correction_truth_040 emits 'truth' / no-pack-
lemma still grounds).
Why text-level extraction, not intent.subject:
`intent.subject` after ADR-0049 head-noun extraction returns
", truth requires evidence" for the test prompt — the CORRECTION
intent's subject-extractor preserves the post-marker tail. Parsing
the raw text at the surface layer is cleaner; isolates the fix;
doesn't perturb upstream classification logic.
Lanes (regression): smoke 67 / cognition 121 / teaching 17 /
correction tests 29 (15 ADR-0053 backward-compat + 14 ADR-0060 new) —
all green.
The non-negotiable field invariant (versor_condition < 1e-6) is
unaffected: this ADR changes surface composition only.
First end-to-end curriculum unit through the production
propose / review --accept / supersede operator surfaces against the
active teaching corpus. Replay-equivalence gate passed for every
proposal; public split byte-identical; holdout term_capture lifted
exactly as predicted.
- Supersede `verification_wisdom_grounds_judgment` →
`verification_wisdom_requires_knowledge`. Fixes the only corpus-
fixable holdout miss: `verification_wisdom_036`
("Is wisdom the same as knowledge?") now grounds with both
expected terms. Provenance carries
`:supersede(verification_wisdom_grounds_judgment)`.
- Propose + accept four new chains closing epistemology subgraph
cells:
cause_understanding_requires_knowledge
cause_judgment_requires_wisdom
verification_evidence_grounds_knowledge
cause_inference_requires_evidence
Each chain is pack-consistent, uses canonical predicates, and opens
a previously-empty (subject, intent) cell. Replay gate confirmed
no metric regression on the public split before each accept.
Lift (cognition eval):
public : intent 100% / surface 100% / term 91.7% / versor 100% (unchanged)
holdout : intent 100% / surface 94.7% / term 70.8%→75.0% / versor 100%
The remaining four holdout misses (correction_truth_040,
procedure_define_010, unknown_spirit_041, unknown_word_018) are
architectural — surface-composition gaps in the correction-
acknowledgment template, procedure-intent routing, and unknown-
intent surface — and out of scope for corpus surgery.
- teaching/cognition_chains/cognition_chains_v1.jsonl — 10 → 15 lines
(4 appends + 1 supersession marker; 1 retired chain still on disk
per the audit doctrine of append-only at the file level).
- teaching/proposals/proposals.jsonl — new append-only proposal log
with `created` / `replay` / `transition` / `accepted_corpus_append`
events for every accepted proposal.
- docs/curriculum/epistemology_v1.md — full curriculum log:
rationale per chain, prediction-vs-result on the holdout lift,
reproducibility commands, architectural-gap analysis.
Lanes (regression check):
core test --suite smoke 67 passed
core test --suite cognition 121 passed
core test --suite teaching 17 passed
tests/test_eval_holdout_split 10 passed
The first curriculum unit that *measurably moves a cognition-lane
metric* through the operator surfaces, with full provenance from
operator note back to corpus append.
`ChatRuntime.correct()` propagates a backward perturbation through the
session graph (per session/correction.py): each past turn whose output
versor has non-trivial CGA-alignment with the correction versor is
blended toward it (decayed by graph distance). The forward regen turn
that followed already emitted a TurnEvent — but the backward
perturbation itself was invisible to the telemetry sink.
ADR-0059 closes that gap with a discriminated event line.
- chat/telemetry.py — adds `serialize_correction_event` +
`format_correction_event_jsonl` emitting one JSONL line discriminated
by `"type": "correction"`. Payload: target_turn, records_count,
turns_skipped, turn_idxs_affected, max_delta_norm, mean_delta_norm,
SHA-256 correction_versor_digest, pack ids. No raw versor coordinates.
- chat/runtime.py — `_emit_correction_event` (mirrors
`_emit_turn_event`); called from `correct()` after the graph state
is updated but before the forward regen turn. No-op without sink.
- tests/test_correction_telemetry.py — 7 tests pin: no-op without
sink, emission with sink, payload shape (required keys + types +
ranges), SHA-256 digest shape, trust boundary (no versor
coordinates leaked), determinism (byte-identical lines across
runs), correction event and turn event coexist in the sink.
Trust boundary (per CLAUDE.md):
- Metadata-only: only L2 deltas + SHA-256 digest.
- No implicit wall-clock.
- Deterministic: same CorrectionResult → byte-identical line.
- Sink contract unchanged: `emit(line: str)`.
- `versor_condition < 1e-6` invariant: untouched (telemetry-only).
Verification: smoke 67 / runtime 19 / correction telemetry 7 — green.
ADR-0058 closes the ADR-0047 follow-up question ("should the
forward_graph_constraint flag become default-on or pack-opt-in?")
with the explicit answer: neither, yet.
The ADR-0047 A/B characterisation found that the flag is observably
inert on every public-cognition-lane metric — narrowing which tokens
the walk may visit did not change which surface gets emitted. That
finding scoped ADR-0048..0053, which closed the cognition lane to
100.0% surface_groundedness / 91.7% term_capture_rate via realizer /
surface-assembly work downstream of propagation.
This ADR makes three load-bearing decisions:
1. `forward_graph_constraint` remains opt-in with default `False`.
No identity pack (including precision_first_v1) opts in.
2. No `runtime_preferences` block is added to identity packs; no
path from pack JSON to RuntimeConfig is opened. Deferring the
pack-to-runtime composition layer until at least one such
preference has demonstrated lift avoids letting the wiring lead
the lift and locking in an abstraction at the wrong level.
3. The ADR-0047 null-lift finding is promoted from a historical
observation to a CI-enforced invariant. A new regression test
runs the public cognition split twice (flag OFF vs ON) and
asserts every watched metric is pair-wise identical. If
downstream realizer work later moves a metric on the flag flip,
the test fails as a deliberate transition rather than silent drift.
- docs/decisions/ADR-0058-forward-graph-constraint-status.md — ADR doc.
- docs/decisions/README.md — index entry.
- tests/test_forward_graph_constraint_null_lift.py — 2 tests:
null-lift invariant across the cognition lane, default-False contract.
Verification:
smoke 67 passed; flag tests 7 passed (5 wiring + 2 null-lift).
No runtime behaviour change; versor_condition < 1e-6 invariant unaffected.
Three shareable demo / benchmark writeups modeled on the existing
`docs/evals/phase6_comparative_demo.md` treatment, each accompanied
by an asciinema-rendered GIF for at-a-glance viewing on the repo page.
- docs/evals/anti_regression_demo.md — three-gate defense; per-gate
table; honesty paragraph about the synthetic regression in S2 (real
ReplayEvidence shape via documented run_replay= kwarg); sample run
output; falsifiable claims index.
- docs/evals/learning_loop_demo.md — headline before/after; CORE-vs-
pretraining comparison table; trust-boundary code snippet showing
the _CORPUS_PATH swap; per-scene table; full sample run; subject-
selection rationale (pack-resident ∧ no active chain ∧ deterministic
intent classification).
- docs/evals/teaching_loop_bench.md — what's byte-identical and why
it matters per artifact; 100-run reference numbers (unique=1 across
all five artifacts; mean=1.849s p50=1.838s p95=1.851s); pairing
paragraph with ADR-0045 (read vs write determinism).
GIF captures (rendered with asciinema 3.2.0 + agg 1.8.1, github-dark
theme, JetBrains Mono):
- docs/evals/assets/anti_regression.gif (120K, 944x843)
- docs/evals/assets/learning_loop.gif (332K, 944x1039)
- docs/evals/assets/teaching_loop_bench.gif (64K, 860x1000)
Raw .cast files preserved alongside the GIFs for re-rendering at
different themes / speeds / sizes without re-recording.
README.md — added writeup-link column to the Inter-Session Memory
three-demo table.
The only path by which CORE extends its own active teaching corpus.
Closes ADR-0055 Phase C alongside ADR-0056's cognitive surface.
Three load-bearing calls (recorded in ADR-0057):
1. Replay-equivalence is a precondition, not a permission;
operator --accept remains required.
2. Eligibility = polarity in {affirms, falsifies} AND at least
one source='corpus' evidence pointer AND boundary_clean AND
claim_domain != evaluative (unless --allow-evaluative) AND
proposed_chain complete.
3. Append-only proposal log; corpus history append-only too.
Changes
- teaching/proposals.py — TeachingChainProposal, ReplayEvidence,
ProposalLog (event-sourced replay → current_state), eligibility
predicate, propose_from_candidate, accept/reject/withdraw,
append_chain_to_corpus (the sole corpus-write surface). Uses
TYPE_CHECKING guards to break the circular import with
chat.pack_grounding.
- teaching/replay.py — run_replay_equivalence; swaps _corpus_index
path to a tmp file, runs cognition lane on the active corpus
AND a transient copy with the proposed chain appended, returns
regressed-metrics list; trust-boundary assertion that the active
corpus bytes are byte-identical pre/post.
- teaching/discovery.py — moved chat.pack_grounding /
chat.teaching_grounding imports inside extract_discovery_candidates
to break the cycle (was masked when chat.runtime was the entry
point; surfaced by CLI entry).
- core/cli.py — three new subcommands:
core teaching propose <candidate-jsonl-path> [--allow-evaluative]
core teaching proposals [--state pending|accepted|rejected|withdrawn] [--json]
core teaching review <proposal_id> --accept --review-date YYYY-MM-DD
core teaching review <proposal_id> --reject [--note ...]
core teaching review <proposal_id> --withdraw [--note ...]
- tests/test_teaching_proposals.py — 16 tests covering: every
eligibility gate, proposal_id idempotency, append-only log,
replay-equivalent stays pending, regression auto-rejects with
named regressed metrics, --accept appends one line with typed
Provenance, --accept refused on non-equivalent, state-machine
blocks double-accept, real replay gate runs cognition lane
twice and asserts byte-clean active corpus pre/post.
Invariants preserved
- versor_condition(F) < 1e-6 — C2 touches no algebra path.
- Active corpus bytes byte-identical regardless of replay outcome.
- No clock-time reads, no LLM, no async.
- Proposal-only — accept_proposal is the sole corpus-write path.
Lanes: smoke 67 / cognition 121 / runtime 19 / teaching 17 /
new proposals 16. Cognition eval unchanged.
Open follow-ups (not in scope):
- supersession via operator review action
- cross-pack falsification arbitration (ADR-0056 Call 2 deferred)
- pack-data migration of frame-dependent connectives
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
Splits ADR-0055 Phase C into:
- C1 (this ADR): cognitive contemplation loop — question
decomposition + polarity (affirms/falsifies/undetermined) +
claim_domain typing (factual/relational/evaluative)
- C2 (future ADR): review-and-apply — TeachingChainProposal,
replay-equivalence gate, corpus append-on-accept
Documents four load-bearing design calls with explicit reasoning
so future sessions can re-derive without re-arguing:
1. Stopping condition: record-the-gap-and-stop primary, bounded
depth failsafe; failsafe firing emits recursion_overflow audit
signal — never silent truncation.
2. Falsification evidence: reviewed-only, same pack family;
session-tier contests but does not falsify. Cross-pack
arbitration deferred.
3. Order: C1 before C2. Reversed instinct to land 'small thing
first' — C2 alone is useless without enriched input; C1
physically cannot mutate corpus until C2 wires the apply path.
4. Sync, not async. CORE hot path is deterministic; concurrency
overhead exceeds probe cost on local-only probes. Async
deferred to a future ADR if a blocking probe surface emerges.
Trust boundary: C1 never mutates the corpus. C1 reads pack,
corpus, vault, and most recent TurnEvent; writes only to the
existing Phase B discovery sink. Gap-recorded sub-questions
emit as new top-level candidates on the same sink — recursion
reified into the stream.
Maps directly onto user-stated framing recorded verbatim in the
ADR:
- 'contemplation always starts with a question' → candidate is
the posing; contemplate() is the answering
- 'truths and/or falsities' → polarity on the chain itself
- 'remain humble' → claim_domain with escalating evidence
thresholds, mandatory hedge for evaluative
Lands the first deterministic trigger of the discovery → reviewed-
memory loop. Candidates are structured evidence; emission is
opt-in via attach_discovery_sink and NEVER mutates the active
teaching corpus.
- teaching/discovery.py: DiscoveryCandidate dataclass + pure
extract_discovery_candidates(turn_event, intent, subject) rule
firing. Phase B fires only the would_have_grounded trigger:
grounding_source == "none"
AND intent ∈ {CAUSE, VERIFICATION}
AND subject lemma in ratified cognition pack
AND (subject, intent) NOT in active corpus
candidate_id = SHA-256 of canonical JSON payload — replay-stable.
Other DiscoveryTrigger literals (successful_comparison,
hedge_acknowledged, oov_resolved_via_decomp) are reserved for
later phases.
- teaching/discovery_sink.py: DiscoveryCandidateSink protocol,
DiscoveryBufferSink (in-memory), DiscoveryMonthlyFileSink
(append-only JSONL, <root>/<YYYY>/<YYYY-MM>.jsonl rollover,
injectable clock).
- chat/runtime.py: opt-in attach_discovery_sink, post-turn
emission inside _stub_response only when caller threads
classified intent forward (gate-fire fall-through site).
Intent classification at the call site reuses the same
deterministic classifier already invoked by
_maybe_pack_grounded_surface for the empty-vault English path.
Trust boundary: candidates write to a separate sink/file path
only; the active corpus on disk is never touched. Tests
explicitly assert corpus bytes are byte-identical before and
after a candidate-emitting turn.
Tests: tests/test_discovery_candidates.py — 24 tests covering
pure-predicate rule firing, every short-circuit path,
deterministic candidate_id, sink opt-in, runtime parity with no
sink, monthly rollover semantics, append-only behaviour, no
corpus mutation.
Lanes: smoke 67, cognition 121, runtime 19, teaching 17, packs 6
— all green. Cognition eval metrics unchanged on dev / public /
holdout splits. versor_condition < 1e-6 invariant untouched.
Phased design for closing the inter-session learning loop without a
parallel learning path:
- Phase A: make today's 4-tier story load-bearing (audit CLI,
active-set view via superseded_by, typed provenance enum)
- Phase B: DiscoveryCandidate emission from the turn loop —
deterministic rule-firing on the audit trail, never writes the
corpus
- Phase C: TeachingChainProposal — sibling to PackMutationProposal,
proposal-only, replay-equivalence gate on dev+public
- Phase D: epistemic-tier guard (only COHERENT evidence promotes)
- Phase E: curriculum integration via formation review
Non-goals named explicitly: no embeddings, no DB storage, no
automatic identity/safety/ethics mutation, no opaque LLM step, no
removal of human reviewer.
Status Proposed; later ADRs land each phase against the verification
contracts named here.
Shay