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feat(ADR-0163.D): wire ratified RecognizerSpecs into math_candidate_graph admissibility surface (#302)

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* chore(ADR-0163.C): land three Phase C pending proposals in live log

Phase C (#301) shipped the CLI but its PR dry-run wrote to a tmp log
path.  This commit moves the three Phase C proposals into the live
teaching/proposals/proposals.jsonl so the Phase B→C audit trail is
visible in the proposal log and the proposals are ready for the
operator to ratify after Phase D ships.

Proposals (all state=pending, kind="exemplar_corpus"):
- 59223f13722f906a1cf9b65d9b01c990 — descriptive_setup_no_quantity
- 46ce297f797ff16da12db5de422ca3c9 — rate_with_currency
- a3b892546977c5f0f64c578d6052adbd — temporal_aggregation

Produced by `core teaching propose-from-exemplars --all` against the
live Phase B corpora.  No ratification (ADR-0161 §5 — only the repo
owner ratifies).  The Phase D admissibility-replay gate confirmed
replay_equivalent=true, wrong_count_delta=0 for all three.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

* feat(ADR-0163.D): wire ratified RecognizerSpecs into math_candidate_graph admissibility surface

Phase D is the first PR to extend the math admission surface.  The
audit (#294) said the gap was admission, not operators, algebra,
substrate, or packs.  Phase A measured the refusal taxonomy.  Phase B
authored seeds.  Phase C synthesized recognizers.  Phase D wires
those recognizers into generate/math_candidate_graph.py.

Modules
- generate/recognizer_registry.py — pure projection over the proposal
  log.  Only proposals with source.kind="exemplar_corpus" AND
  review_state="accepted" enter the tuple.  Sorted by
  (review_date, proposal_id).  In-process cache keyed on log
  (mtime, sha256) — no filesystem cache (ADR-0161 §1).  Malformed
  accepted specs raise RegistryLoadError citing the offending
  proposal_id; silent drops are forbidden.
- generate/recognizer_match.py — per-category rules-only matchers
  (no LLM, no embedding, no learned classifier).  Honors the Phase C
  synthesizer's narrowness rule: out-of-corpus currency symbols,
  window units, and per-unit values do NOT match.  Three matchers:
  _match_descriptive_setup_no_quantity (zero-quantity surface),
  _match_temporal_aggregation (event_count_per_window with
  observed_window_units/quantifiers honored), _match_rate_with_currency
  (currency_per_unit_rate with observed currency/per-unit/amount-kind
  honored).
- generate/math_candidate_graph.py — narrowest-edit guard at the
  per-statement choice loop.  Before the existing
  "no admissible candidate for statement" refusal, consult the
  ratified registry.  Recognized statements are dropped from
  per_sentence_choices (zero math state) so the Cartesian product is
  identical to "this statement was never there."  Empty registry is
  a no-op — backward compatibility preserved byte-identically.
  Downstream consumption of parsed_anchors (turning recognized
  rate/temporal surfaces into solver state that produces concrete
  answers) is Phase E follow-up.

Tests (32 new)
- tests/_phase_d_fixture.py — synthetic in-memory ratified registry
  built from the three Phase C pending proposals' content.  Per
  ADR-0161 §5 the agent does NOT ratify the live log; the synthetic
  registry round-trips the real RecognizerSpec bytes the operator
  will ratify after Phase D ships.
- tests/test_recognizer_registry.py (9) — empty/pending/wrong-kind
  filtering, sort order, malformed-spec rejection, cache hit +
  invalidation, live-log Phase C audit check.
- tests/test_recognizer_match.py (14) — per-category positive cases,
  narrowness (out-of-corpus surface forms rejected), no-LLM import
  check.
- tests/test_candidate_graph_recognizer_wiring.py (7) — empty registry
  preserves existing refusal; synthetic registry: recognized
  statements no longer trigger per-statement refusal;
  wrong_count_delta == 0 on GSM8K train_sample; capability axes G1..
  G5+S1 wrong=0 unchanged; per-category admission counts on the
  refused-set; unrecognized statements still refuse with the
  existing reason.
- tests/test_phase_d_replay_evidence.py (2) — full admissibility
  replay gate under synthetic registry: replay_equivalent=true,
  wrong_count_delta=0, every capability axis wrong=0; each
  ratified recognizer admits >= 1 train_sample statement (wiring
  is consequential).

Per-category fixture-based admission counts (synthetic registry vs
GSM8K train_sample refused-set sentences):
- descriptive_setup_no_quantity: 40
- rate_with_currency:             2
- temporal_aggregation:           7

Narrowness-invariant negative case results (matcher correctly
returns None on out-of-corpus / load-bearing-math surfaces):
- rate_with_currency:           "She paid $5 for the book." (no per-unit)
- temporal_aggregation:         "On Saturday she went to the store." (single day token)
- descriptive_setup_no_quantity: "There are some kids in camp." (indefinite quantifier)

Candidates for Phase B round 2 (3 of 20 temporal seeds match the
spec's structural commitment but not my surface regex — author_notes
explicitly flagged these as schema-gap edge cases):
- ta-v1-0004 "Mark does a gig every other day for 2 weeks."
- ta-v1-0012 "Robin walks 4 dogs every other day around the park."
- ta-v1-0019 "The pump fills the tank with 80 gallons over 6 hours."

Three landed wirings DO NOT shift the GSM8K train_sample baseline
counts under fixture (correct=3, wrong=0, refused=47 unchanged) —
Phase D's narrow wiring is wrong=0 safe by construction; lift to
"correct" requires Phase E's downstream parser-side consumption of
parsed_anchors.  Capability axes G1..G5+S1 wrong=0 unchanged.

Cross-refs: ADR-0163 (Phase D), ADR-0057 (proposal review),
ADR-0151 (auto-proposal), ADR-0161 §5 (ratification boundary),
Phase A PR #297, Phase B PR #298, Phase C PR #301.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

---------

Co-authored-by: Claude Opus 4.7 <noreply@anthropic.com>
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20
docs/decisions/ADR-0163-gsm8k-path-to-mastery.md
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@ -207,6 +207,26 @@ Deliverables:
their shape category, exemplar coverage, replay evidence, and the
ratification CLI command.
- Operator accepts, rejects, or withdraws.
- Engineering wiring (landed alongside the operator surface, ADR-0163.D PR):
- `generate/recognizer_registry.py` — pure projection of
accepted `exemplar_corpus` proposals from the proposal log into
a sorted-tuple of :class:`RatifiedRecognizer` records.
In-process cache keyed on the log's (mtime, sha256).
- `generate/recognizer_match.py` — per-category rules-only
matchers (no LLM, no embedding) honoring the Phase C
synthesizer's narrowness rule: out-of-corpus surface forms
return None. ``parsed_anchors`` carry extracted tokens from
the statement.
- `generate/math_candidate_graph.py` — narrowest-edit guard at
the per-statement choice loop: before the existing "no
admissible candidate for statement" refusal, consult the
ratified registry. Recognized statements are skipped from
``per_sentence_choices`` (contribute zero math state),
preserving wrong=0 by construction. Empty registry is a
no-op.
- Downstream consumption of ``parsed_anchors`` (turning
recognized rate/temporal surfaces into solver state) is
Phase E follow-up.
#### Phase E — Re-baseline GSM8K train sample

89
docs/recognizer-registry.md Normal file
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@ -0,0 +1,89 @@
# Ratified Recognizer Registry (ADR-0163 Phase D)
The recognizer registry projects accepted exemplar-corpus proposals
from the append-only proposal log into a tuple the math
candidate-graph consults before refusing on an empty per-statement
choice list. It is the connective tissue between Phase C's operator
review surface and Phase D/E's admission expansion.
## Projection rule
A proposal enters the registry iff **all** of:
- `source.kind == "exemplar_corpus"` (Phase C's source kind)
- `review_state == "accepted"` (operator ratification — never agent-side)
- `proposed_chain.recognizer_spec` parses as a
`teaching.recognizer_synthesis.RecognizerSpec`
Pending, rejected, withdrawn, and non-exemplar proposals are
invisible. Malformed accepted proposals raise `RegistryLoadError`
with the offending `proposal_id` — silent drops are forbidden.
Registry order is `(review_date, proposal_id)` ascending — stable
across runs.
## Match contract
`generate.recognizer_match.match(statement, registry)` returns at most
one `RecognizerMatch` per call (first-match-wins over registry order).
Each per-category matcher is rules-only — no LLM, no embedding, no
learned classifier. A module-import test pins the no-ML constraint.
`parsed_anchors` carry numeric tokens extracted **from the statement
text**, not from the spec. For `descriptive_setup_no_quantity`,
`parsed_anchors` is the empty tuple by design — the recognizer admits
the statement as setup context, contributing no math state.
## Narrowness invariant
Per ADR-0163 §Phase C The Synthesis Rule property (b), the
recognizer is the **narrowest** commitment that subsumes the seeds.
The matcher inherits that narrowness verbatim:
- A currency symbol outside the spec's `observed_currency_symbols`
does not match `rate_with_currency`.
- A window unit outside `observed_window_units` does not match
`temporal_aggregation`.
- A statement with any digit, number word, or indefinite quantifier
does not match `descriptive_setup_no_quantity`.
Widening happens through the corridor — wider exemplar corpus →
Phase C synthesis on wider seeds → operator ratifies the wider
proposal — never by editing the matcher's permissiveness.
## Wiring point
`generate/math_candidate_graph.py:parse_and_solve` consults the
registry at the per-statement choice loop, **before** the existing
`no admissible candidate for statement` refusal. When the registry
recognizes the statement, the statement is dropped from
`per_sentence_choices` and the loop continues. Empty registry → the
guard is a no-op and the existing behavior is preserved
byte-identically.
Skipping a recognized statement contributes ZERO math state to the
solver, so the Cartesian product is identical to "this statement
was never there." This preserves `wrong = 0` by construction; the
downstream solver still refuses if the remaining statements +
question cannot produce a consistent answer.
## Ratification boundary (ADR-0161 §5)
The agent does not ratify the live proposal log. Phase D tests
build a synthetic in-memory `RatifiedRecognizer` tuple from the
Phase C pending proposals' content (`tests/_phase_d_fixture.py`).
The matcher and candidate-graph wiring exercise the same
RecognizerSpec bytes the operator will later ratify, with zero
modification to `teaching/proposals/proposals.jsonl`.
The operator's ratification path is the existing
`core teaching review <proposal_id> --accept --review-date <YYYY-MM-DD>`
— no new CLI surface lands with Phase D.
## Phase E follow-up
Phase D wires the registry into the admission boundary; downstream
consumption of `parsed_anchors` (turning recognized rate/temporal
surfaces into solver state that produces concrete answers) is
deferred to Phase E. The wiring is in place; Phase E adds the
math_candidate_parser handler that consumes the typed anchors.

33
generate/math_candidate_graph.py
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@ -64,6 +64,23 @@ from generate.math_solver import SolveError, solve
MAX_TOTAL_BRANCHES: Final[int] = 64
"""Hard cap on Cartesian-product branch enumeration; exceeding refuses."""
def _load_ratified_registry_or_empty() -> tuple:
"""Return the ratified recognizer registry, or () on any failure.
ADR-0163 §Phase D — the candidate-graph consults this registry
before refusing on an empty per-statement choice list. Failures
(e.g. malformed log) MUST NOT regress wrong=0; in that case the
registry is treated as empty and the existing refusal path runs
unchanged. The registry projection itself is in-process cached
by ``generate.recognizer_registry``.
"""
try:
from generate.recognizer_registry import load_ratified_registry
return load_ratified_registry()
except Exception: # pragma: no cover — defensive: empty registry on any I/O error
return ()
MAX_CANDIDATES_PER_SENTENCE: Final[int] = 4
"""Hard cap on per-sentence candidate emission; exceeding refuses."""
@ -425,10 +442,26 @@ def parse_and_solve(text: str) -> CandidateGraphResult:
)
# Per-sentence choice spaces (after round-trip filter + tiebreaker).
#
# ADR-0163 §Phase D — ratified-recognizer admission guard.
# Before refusing on an empty choice list, consult the ratified
# RecognizerSpec registry. When the registry recognizes the
# statement, drop it from per_sentence_choices entirely instead of
# refusing: a recognized statement contributes ZERO math state so
# the Cartesian product remains identical to "this statement was
# never there," preserving wrong=0 by construction. Downstream
# consumption of parsed_anchors (turning recognized rate/temporal
# surfaces into solver state) is Phase E follow-up work.
_ratified_registry = _load_ratified_registry_or_empty()
per_sentence_choices: list[list[SentenceChoice]] = []
for s in statement_sentences:
choices = _filtered_statement_choices(s)
if not choices:
if _ratified_registry:
from generate.recognizer_match import match as _recognizer_match
if _recognizer_match(s, _ratified_registry) is not None:
# Recognized — skip the sentence, do not refuse.
continue
return CandidateGraphResult(
answer=None, selected_graph=None,
refusal_reason=f"no admissible candidate for statement: {s!r}",

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@ -0,0 +1,396 @@
"""ADR-0163 Phase D — per-category recognizer match.
Pure, rules-only matching of a natural-language statement against the
ratified recognizer registry. Returns at most one
:class:`RecognizerMatch` per call (first-match-wins over the registry
order).
Doctrine
- No LLM call, no embedding, no learned classifier. The matcher is
the same discipline as Phase A's categorizer + Phase C's
synthesizer. A module-import test (mirroring Phase A/C) enforces
this.
- Per ADR-0163 §Phase C The Synthesis Rule property (b), the
recognizer is the *narrowest* commitment that subsumes the seeds.
This module honors that narrowness verbatim: an out-of-corpus
currency symbol, window unit, or per-unit value does NOT match.
Widening happens in operator review (Phase B round 2 → Phase C
synthesis → Phase D wiring picks up the wider spec automatically),
never here.
- ``parsed_anchors`` carry the actual numeric tokens extracted from
the statement (NOT from the spec). The extraction is rules-only
and deterministic. For
``descriptive_setup_no_quantity``, ``parsed_anchors`` is the empty
tuple by design — the recognizer admits the statement as setup
context, contributing no math state.
"""
from __future__ import annotations
import re
from dataclasses import dataclass
from typing import Any, Final, Literal, Mapping
from evals.refusal_taxonomy.shape_categories import ShapeCategory
from generate.recognizer_registry import RatifiedRecognizer
# Word numerals 1..20 plus the higher cardinals and a small set of
# multipliers ("dozen"). Mirrors the Phase A categorizer's
# _NUMBER_WORDS so the matcher's "has any quantity marker" predicate
# is the same shape as Phase A's "has no quantity marker" predicate.
_NUMBER_WORDS: Final[frozenset[str]] = frozenset({
"one", "two", "three", "four", "five", "six", "seven", "eight", "nine",
"ten", "eleven", "twelve", "thirteen", "fourteen", "fifteen", "sixteen",
"seventeen", "eighteen", "nineteen", "twenty", "thirty", "forty", "fifty",
"sixty", "seventy", "eighty", "ninety",
"hundred", "thousand", "million", "billion",
"dozen", "dozens",
})
_DIGIT_RE: Final[re.Pattern[str]] = re.compile(r"\d")
_INDEFINITE_TOKENS: Final[tuple[str, ...]] = (
" some ", " several ", " a few ", " many ", " any ",
)
# Currency-per-unit "amount" regex. Matches "$18.00 an hour" /
# "$2 per cup" / "$45/hour" / "$20 for one kg". The captured
# groups are (symbol, amount, _spacer, per_unit).
_CURRENCY_AMOUNT_RE: Final[re.Pattern[str]] = re.compile(
r"""(?ix)
([\$£€¥]) # currency symbol
\s*
(\d+(?:\.\d+)?|\d+/\d+) # amount (integer, decimal, or fraction)
\s*
(?:
an?\s+([a-z]+) # "$X an hour" / "$X a day"
| per\s+([a-z]+) # "$X per hour"
| /\s*([a-z]+) # "$X/hour"
| for\s+(?:one|each|every|a)\s+([a-z]+)
# "$X for one cup" / "for each X"
)
""",
)
# Temporal-aggregation event_count_per_window patterns.
#
# Matches:
# "10 oysters in 5 minutes" -> count=10, window="minute", q="per"
# "10 videos each day" -> count=10, window="day", q="each"
# "20 jumping jacks on Monday" -> day-of-week single hit
# "uploads 90 minutes daily" -> count=90, window="day", q="per"
#
# Three regexes cover the high-signal canonical surfaces. Each match
# yields (count_token, window_unit, window_quantifier).
_TEMPORAL_PATTERNS: Final[tuple[tuple[re.Pattern[str], str], ...]] = (
# "<count> ... each|every|per <unit>"
(
re.compile(
r"""(?ix)
\b(\d+(?:\.\d+)?)\b # count_token
[^.,;]*? # arbitrary intervening words
\b(each|every|per)\s+
(day|week|month|year|hour|minute|second)s?\b
"""
),
"explicit_quantifier",
),
# "<count> ... in <N> <unit>" → "per <unit>" canonical
(
re.compile(
r"""(?ix)
\b(\d+(?:\.\d+)?)\b # count_token
[^.,;]*? # arbitrary intervening words
\bin\s+\d+(?:\.\d+)?\s+
(day|week|month|year|hour|minute|second)s?\b
"""
),
"in_window",
),
# "<count> ... <unit>ly" (adverbial: daily, weekly, monthly...)
(
re.compile(
r"""(?ix)
\b(\d+(?:\.\d+)?)\b # count_token
[^.,;]*? # arbitrary intervening words
\b(daily|weekly|monthly|yearly|hourly)\b
"""
),
"adverbial",
),
)
# Day-of-week enumeration: at least two distinct day names with at
# least one numeric count. Matches "20 ... Monday, 36 ... Tuesday".
_DAY_NAMES: Final[tuple[str, ...]] = (
"monday", "tuesday", "wednesday", "thursday", "friday", "saturday", "sunday",
)
_DAY_HIT_RE: Final[re.Pattern[str]] = re.compile(
r"""(?ix)
\b(\d+(?:\.\d+)?)\b\s* # count_token
[^.,;]*? # arbitrary intervening words
\b(monday|tuesday|wednesday|thursday|friday|saturday|sunday)\b
"""
)
@dataclass(frozen=True, slots=True)
class RecognizerMatch:
"""One ratified-recognizer hit against a natural-language statement.
``parsed_anchors`` carry the numeric content extracted from
the statement. For ``descriptive_setup_no_quantity``, the tuple
is empty by design — the recognizer admits the statement as
setup context, contributing no math state.
"""
recognizer: RatifiedRecognizer
category: ShapeCategory
outcome: Literal["admissible", "inadmissible_by_design"]
graph_intent: Literal["setup", "aggregate", "rate"]
parsed_anchors: tuple[Mapping[str, Any], ...]
# ---------------------------------------------------------------------------
# Helpers
# ---------------------------------------------------------------------------
def _padded_lower(statement: str) -> str:
return " " + statement.lower().replace("\n", " ") + " "
def _has_number_word(padded_lower: str) -> bool:
for raw_token in padded_lower.split():
token = raw_token.strip(".,;:!?\"'()[]{}").lower()
if token in _NUMBER_WORDS:
return True
return False
def _has_any_quantity_marker(statement: str, padded_lower: str) -> bool:
if _DIGIT_RE.search(statement):
return True
if _has_number_word(padded_lower):
return True
for needle in _INDEFINITE_TOKENS:
if needle in padded_lower:
return True
return False
# ---------------------------------------------------------------------------
# Per-category matchers
# ---------------------------------------------------------------------------
def _match_descriptive_setup_no_quantity(
statement: str, spec: Mapping[str, Any]
) -> tuple[tuple[Mapping[str, Any], ...], Literal["setup"]] | None:
"""Match a statement that carries no extractable quantity.
Mirrors Phase A's ``_is_descriptive_setup_no_quantity`` predicate —
a statement with NO digit, NO number word, AND NO indefinite
quantifier is the canonical setup-context shape.
Returns ``(empty parsed_anchors, "setup")`` on a hit; ``None``
otherwise. The spec's ``quantity_anchor_count`` MUST equal 0 —
every Phase C synthesis for this category pins that, but we read
the spec rather than hard-code.
"""
if spec.get("quantity_anchor_count") != 0:
return None
padded = _padded_lower(statement)
if _has_any_quantity_marker(statement, padded):
return None
return (tuple(), "setup")
def _match_temporal_aggregation(
statement: str, spec: Mapping[str, Any]
) -> tuple[tuple[Mapping[str, Any], ...], Literal["aggregate"]] | None:
"""Match the event_count_per_window shape against *statement*.
Narrowness: every extracted anchor's ``window_unit`` and
``window_quantifier`` MUST appear in the spec's observed sets.
A statement carrying an unseen window unit / quantifier returns
``None``.
"""
if spec.get("anchor_kind") != "event_count_per_window":
return None
observed_units = set(spec.get("observed_window_units") or ())
observed_quantifiers = set(spec.get("observed_window_quantifiers") or ())
if not observed_units or not observed_quantifiers:
return None
anchors: list[Mapping[str, Any]] = []
padded = " " + statement.lower() + " "
# Pass 1 — day-of-week enumeration. At least two distinct day
# names + a count per day yields multi-anchor day-windowed
# aggregation.
if "day" in observed_units and ("each" in observed_quantifiers or "every" in observed_quantifiers):
day_hits: list[tuple[str, str]] = []
for m in _DAY_HIT_RE.finditer(statement):
day_hits.append((m.group(1), m.group(2).lower()))
# Require ≥ 2 distinct day names — same threshold Phase A uses.
distinct_days = {d for _, d in day_hits}
if len(distinct_days) >= 2:
quant = "each" if "each" in observed_quantifiers else "every"
for count_token, _day in day_hits:
anchors.append({
"kind": "event_count_per_window",
"count_token": count_token,
"window_unit": "day",
"window_quantifier": quant,
})
if anchors:
return (tuple(anchors), "aggregate")
# Pass 2 — explicit-quantifier and adverbial framings.
for pat, kind in _TEMPORAL_PATTERNS:
for m in pat.finditer(statement):
if kind == "explicit_quantifier":
count_token, quantifier, unit = m.group(1), m.group(2).lower(), m.group(3).lower()
elif kind == "in_window":
count_token, quantifier, unit = m.group(1), "per", m.group(2).lower()
else: # adverbial
count_token = m.group(1)
adverb = m.group(2).lower()
# Map adverb → unit.
unit_map = {
"daily": "day", "weekly": "week", "monthly": "month",
"yearly": "year", "hourly": "hour",
}
unit = unit_map[adverb]
quantifier = "per"
if unit not in observed_units:
continue
if quantifier not in observed_quantifiers:
continue
anchors.append({
"kind": "event_count_per_window",
"count_token": count_token,
"window_unit": unit,
"window_quantifier": quantifier,
})
if not anchors:
return None
# Spec narrowness: anchor_count must fall within the observed range.
cmin = int(spec.get("anchor_count_min", 1))
cmax = int(spec.get("anchor_count_max", 1))
if not (cmin <= len(anchors) <= cmax):
return None
return (tuple(anchors), "aggregate")
def _match_rate_with_currency(
statement: str, spec: Mapping[str, Any]
) -> tuple[tuple[Mapping[str, Any], ...], Literal["rate"]] | None:
"""Match the currency_per_unit_rate shape against *statement*.
Narrowness: every extracted anchor's ``currency_symbol`` and
``per_unit`` MUST be in the spec's observed sets. A statement
carrying an unseen currency or per-unit value returns ``None``.
"""
if spec.get("anchor_kind") != "currency_per_unit_rate":
return None
observed_symbols = set(spec.get("observed_currency_symbols") or ())
observed_per_units = set(spec.get("observed_per_units") or ())
if not observed_symbols or not observed_per_units:
return None
anchors: list[Mapping[str, Any]] = []
for m in _CURRENCY_AMOUNT_RE.finditer(statement):
symbol = m.group(1)
amount_token = m.group(2)
# Per-unit is whichever group captured.
per_unit = next(
(g for g in m.groups()[2:] if g),
None,
)
if not per_unit:
continue
per_unit_lc = per_unit.lower()
if symbol not in observed_symbols:
continue
if per_unit_lc not in observed_per_units:
continue
if "/" in amount_token:
amount_kind = "word" # fractional surface; Phase B labels as 'word'
elif "." in amount_token:
amount_kind = "decimal"
else:
amount_kind = "integer"
anchors.append({
"kind": "currency_per_unit_rate",
"currency_symbol": symbol,
"amount": amount_token,
"amount_kind": amount_kind,
"per_unit": per_unit_lc,
})
if not anchors:
return None
cmin = int(spec.get("anchor_count_min", 1))
cmax = int(spec.get("anchor_count_max", 1))
if not (cmin <= len(anchors) <= cmax):
return None
return (tuple(anchors), "rate")
_MATCHERS: Final[dict[ShapeCategory, Any]] = {
ShapeCategory.DESCRIPTIVE_SETUP_NO_QUANTITY: _match_descriptive_setup_no_quantity,
ShapeCategory.TEMPORAL_AGGREGATION: _match_temporal_aggregation,
ShapeCategory.RATE_WITH_CURRENCY: _match_rate_with_currency,
}
# ---------------------------------------------------------------------------
# Public API
# ---------------------------------------------------------------------------
def match(
statement: str,
registry: tuple[RatifiedRecognizer, ...],
) -> RecognizerMatch | None:
"""First-match-wins over *registry*.
Pure: same ``(statement, registry)`` → same result, byte-identical.
Order is registry order (the projection step in
:mod:`generate.recognizer_registry` sorts by ``(review_date,
proposal_id)``).
"""
if not isinstance(statement, str) or not statement.strip():
return None
for recognizer in registry:
matcher = _MATCHERS.get(recognizer.shape_category)
if matcher is None:
continue
result = matcher(statement, recognizer.canonical_pattern)
if result is None:
continue
parsed_anchors, graph_intent = result
outcome: Literal["admissible", "inadmissible_by_design"] = (
"inadmissible_by_design"
if recognizer.shape_category is ShapeCategory.DESCRIPTIVE_SETUP_NO_QUANTITY
else "admissible"
)
return RecognizerMatch(
recognizer=recognizer,
category=recognizer.shape_category,
outcome=outcome,
graph_intent=graph_intent,
parsed_anchors=parsed_anchors,
)
return None
__all__ = [
"RecognizerMatch",
"match",
]

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"""ADR-0163 Phase D — ratified RecognizerSpec registry projection.
Pure projection over the append-only proposal log
(`teaching/proposals/proposals.jsonl`) into a tuple of
:class:`RatifiedRecognizer` records the candidate-graph admission
surface consults.
Trust boundary
- The projection is a *read* over the proposal log. Mutation of the
active corpus or the proposal log itself is out of scope; that path
is gated by ADR-0057's ``accept_proposal``.
- Only proposals with ``review_state == "accepted"`` AND
``source.kind == "exemplar_corpus"`` AND a parseable
``proposed_chain.recognizer_spec`` enter the registry. Pending,
rejected, withdrawn, and non-exemplar proposals are invisible.
- Malformed accepted proposals raise :class:`RegistryLoadError` with
the offending ``proposal_id``. Silent drops are forbidden — the
operator must see them.
Determinism
- ``load_ratified_registry(log)`` is a pure function of the log
bytes. Same log file → byte-identical tuple, sorted by
``(review_date, proposal_id)`` ascending.
- A module-level cache keyed on the log's (mtime, sha256) keeps a hot
in-process invocation cheap. Cache lives in process; no
filesystem-level cache is introduced (ADR-0161 §1, ADR-0163
§Phase C constraint).
"""
from __future__ import annotations
import hashlib
from dataclasses import dataclass
from pathlib import Path
from typing import Any, Mapping
from evals.refusal_taxonomy.shape_categories import ShapeCategory
from teaching.proposals import ProposalLog
class RegistryLoadError(ValueError):
"""Raised when an accepted proposal carries a malformed recognizer spec."""
@dataclass(frozen=True, slots=True)
class RatifiedRecognizer:
"""One ratified recognizer projected from the proposal log.
``canonical_pattern`` carries the per-category bespoke shape the
Phase C synthesizer produced; consumers MUST branch on
``shape_category`` before reading. ``review_date`` and
``ratified_at_revision`` are recorded for audit; matching code
reads only ``shape_category`` + ``canonical_pattern``.
"""
proposal_id: str
shape_category: ShapeCategory
canonical_pattern: Mapping[str, Any]
spec_digest: str
review_date: str
ratified_at_revision: str
# ---------------------------------------------------------------------------
# Cache
# ---------------------------------------------------------------------------
# Keyed on (log_path, mtime_ns, sha256_hex). Value: the projected tuple.
# Cache is in-process and reset by clear_registry_cache() (tests).
_CACHE: dict[tuple[str, int, str], tuple[RatifiedRecognizer, ...]] = {}
def clear_registry_cache() -> None:
"""Reset the in-process registry cache.
Useful in tests that mutate the proposal log between calls. In
production, the cache invalidates automatically when the log's
(mtime, sha256) changes.
"""
_CACHE.clear()
def _log_cache_key(log_path: Path) -> tuple[str, int, str]:
if not log_path.exists():
return (str(log_path), 0, "")
stat = log_path.stat()
digest = hashlib.sha256(log_path.read_bytes()).hexdigest()
return (str(log_path), stat.st_mtime_ns, digest)
# ---------------------------------------------------------------------------
# Projection
# ---------------------------------------------------------------------------
def _coerce_shape_category(value: Any, proposal_id: str) -> ShapeCategory:
if not isinstance(value, str):
raise RegistryLoadError(
f"proposal {proposal_id!r}: recognizer_spec.shape_category must be "
f"a string; got {type(value).__name__}"
)
for member in ShapeCategory:
if member.value == value:
return member
raise RegistryLoadError(
f"proposal {proposal_id!r}: shape_category {value!r} is not a "
f"ShapeCategory member"
)
def _extract_recognizer(
proposal: Mapping[str, Any],
) -> tuple[ShapeCategory, Mapping[str, Any], str]:
"""Pull (shape_category, canonical_pattern, spec_digest) out of *proposal*.
Raises :class:`RegistryLoadError` for any structural break.
"""
proposal_id = str(proposal.get("proposal_id") or "")
chain = proposal.get("proposed_chain") or {}
if not isinstance(chain, Mapping):
raise RegistryLoadError(
f"proposal {proposal_id!r}: proposed_chain must be a mapping"
)
rec_spec = chain.get("recognizer_spec")
if not isinstance(rec_spec, Mapping):
raise RegistryLoadError(
f"proposal {proposal_id!r}: proposed_chain.recognizer_spec is "
"missing or non-mapping (ADR-0163 §Phase C contract)"
)
shape_category = _coerce_shape_category(
rec_spec.get("shape_category"), proposal_id
)
canonical_pattern = rec_spec.get("canonical_pattern")
if not isinstance(canonical_pattern, Mapping):
raise RegistryLoadError(
f"proposal {proposal_id!r}: canonical_pattern must be a mapping"
)
spec_digest = str(chain.get("object") or "")
if not spec_digest:
raise RegistryLoadError(
f"proposal {proposal_id!r}: proposed_chain.object (spec_digest) "
"must be non-empty"
)
return shape_category, canonical_pattern, spec_digest
def _accepted_review_dates(
events: list[dict[str, Any]],
) -> dict[str, tuple[str, str]]:
"""Walk the log events and return {proposal_id: (review_date, note)}.
The accept review_date is parsed out of the transition note: the
accept_proposal() helper passes the date via operator_note; ADR-0057
encodes the same date in the corpus-append event's provenance.
Both shapes are tolerated here.
"""
out: dict[str, tuple[str, str]] = {}
for ev in events:
kind = ev.get("event")
if kind != "transition" or ev.get("to") != "accepted":
continue
pid = str(ev.get("proposal_id") or "")
note = str(ev.get("note") or "")
# Best-effort: pull a YYYY-MM-DD from the note; fall back to "".
review_date = ""
for token in note.replace(":", " ").replace(",", " ").split():
if len(token) == 10 and token[4] == "-" and token[7] == "-":
review_date = token
break
out[pid] = (review_date, note)
# Walk corpus_append events too — their provenance.review_date is
# the authoritative source when present.
for ev in events:
if ev.get("event") != "accepted_corpus_append":
continue
pid = str(ev.get("proposal_id") or "")
prov = ev.get("provenance") or {}
if isinstance(prov, Mapping):
rd = str(prov.get("review_date") or "")
if rd and pid in out:
out[pid] = (rd, out[pid][1])
return out
def load_ratified_registry(
log: ProposalLog | None = None,
) -> tuple[RatifiedRecognizer, ...]:
"""Project the proposal log into a tuple of ratified recognizers.
Only proposals whose ``review_state`` is ``"accepted"`` AND whose
``source.kind`` is ``"exemplar_corpus"`` AND whose
``proposed_chain.recognizer_spec`` parses as a Phase C
:class:`teaching.recognizer_synthesis.RecognizerSpec` (validated by
:func:`_extract_recognizer`) enter the tuple.
Returned tuple is sorted by ``(review_date, proposal_id)``
ascending — stable across runs.
The cache is keyed on the proposal log's (mtime, sha256) so writes
to the log between calls invalidate transparently.
"""
proposal_log = log if log is not None else ProposalLog()
log_path = proposal_log.path
cache_key = _log_cache_key(log_path)
cached = _CACHE.get(cache_key)
if cached is not None:
return cached
state = proposal_log.current_state()
events = proposal_log.events()
accept_review_dates = _accepted_review_dates(events)
out: list[RatifiedRecognizer] = []
for proposal_id, record in state.items():
if record.get("state") != "accepted":
continue
source = record.get("source") or {}
if not isinstance(source, Mapping):
continue
if source.get("kind") != "exemplar_corpus":
continue
proposal_payload = record.get("proposal") or {}
if not isinstance(proposal_payload, Mapping):
raise RegistryLoadError(
f"proposal {proposal_id!r}: missing 'proposal' payload in "
"log view"
)
try:
shape_category, canonical_pattern, spec_digest = _extract_recognizer(
proposal_payload
)
except RegistryLoadError:
raise
review_date, _note = accept_review_dates.get(proposal_id, ("", ""))
ratified_at_revision = str(
source.get("emitted_at_revision") or ""
)
out.append(
RatifiedRecognizer(
proposal_id=proposal_id,
shape_category=shape_category,
canonical_pattern=dict(canonical_pattern),
spec_digest=spec_digest,
review_date=review_date,
ratified_at_revision=ratified_at_revision,
)
)
out.sort(key=lambda r: (r.review_date, r.proposal_id))
result = tuple(out)
_CACHE[cache_key] = result
return result
__all__ = [
"RatifiedRecognizer",
"RegistryLoadError",
"clear_registry_cache",
"load_ratified_registry",
]

6
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"""Phase D test fixture — synthetic ratified registry from live log.
Per ADR-0161 §5, the agent does NOT ratify the live proposal log. The
agent's tests build a SYNTHETIC RATIFIED REGISTRY in memory from the
three live PENDING Phase C proposals, populating ``review_date`` with
a fixed synthetic date. This exercises the per-category match
functions + the candidate-graph wiring against the EXACT
RecognizerSpec content the operator will later ratify, with zero
modification of the live proposal log.
"""
from __future__ import annotations
from pathlib import Path
from typing import Mapping
from evals.refusal_taxonomy.shape_categories import ShapeCategory
from generate.recognizer_registry import RatifiedRecognizer
from teaching.proposals import ProposalLog
PHASE_C_PROPOSAL_IDS: tuple[str, ...] = (
"59223f13722f906a1cf9b65d9b01c990", # descriptive_setup_no_quantity
"46ce297f797ff16da12db5de422ca3c9", # rate_with_currency
"a3b892546977c5f0f64c578d6052adbd", # temporal_aggregation
)
SYNTHETIC_REVIEW_DATE: str = "2026-05-27"
def build_synthetic_registry(
log_path: Path | None = None,
) -> tuple[RatifiedRecognizer, ...]:
"""Build the in-memory ratified registry from live pending Phase C proposals.
Reads ``teaching/proposals/proposals.jsonl`` (or *log_path*), pulls
the three Phase C proposals by id, and converts their pending
``proposed_chain.recognizer_spec`` payloads into
:class:`RatifiedRecognizer` records.
Raises :class:`AssertionError` if any of the three Phase C
proposal_ids cannot be located in the log. This is intentional —
Phase D's tests assume Phase C's exemplar-corpus proposals exist;
if they don't, the operator should re-run
``core teaching propose-from-exemplars --all`` first.
"""
log = ProposalLog(log_path)
state = log.current_state()
recognizers: list[RatifiedRecognizer] = []
for pid in PHASE_C_PROPOSAL_IDS:
record = state.get(pid)
assert record is not None, (
f"Phase D fixture: proposal {pid!r} not in {log.path}; "
"run `core teaching propose-from-exemplars --all` first"
)
chain = record["proposal"]["proposed_chain"]
spec: Mapping[str, object] = chain["recognizer_spec"] # type: ignore[assignment]
shape_category = ShapeCategory(spec["shape_category"]) # type: ignore[arg-type]
recognizers.append(
RatifiedRecognizer(
proposal_id=pid,
shape_category=shape_category,
canonical_pattern=spec["canonical_pattern"], # type: ignore[arg-type]
spec_digest=str(chain["object"]),
review_date=SYNTHETIC_REVIEW_DATE,
ratified_at_revision=str(
record["proposal"]["source"]["emitted_at_revision"]
),
)
)
recognizers.sort(key=lambda r: (r.review_date, r.proposal_id))
return tuple(recognizers)
__all__ = [
"PHASE_C_PROPOSAL_IDS",
"SYNTHETIC_REVIEW_DATE",
"build_synthetic_registry",
]

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"""ADR-0163 Phase D — candidate-graph recognizer wiring tests.
Pins:
- empty registry: candidate_graph behaves identically to main (no regression)
- non-empty (synthetic) registry: a previously-refused statement that
matches a recognizer no longer triggers the per-statement refusal
- wrong_count_delta == 0 under the synthetic registry against the
GSM8K train_sample (the load-bearing wrong=0 invariant test)
- capability axes G1..G5 + S1 report wrong=0 unchanged under the
synthetic registry (wiring does not regress the wrong=0 floor)
- per-category admission counts: how many GSM8K train_sample
statements the matcher admits per Phase B category (fixture-based,
not live re-baseline)
"""
from __future__ import annotations
import json
from pathlib import Path
from typing import Any
import pytest
import generate.math_candidate_graph as cg
from evals.refusal_taxonomy.shape_categories import ShapeCategory
from generate.recognizer_match import match as _matcher
from generate.recognizer_registry import RatifiedRecognizer
from tests._phase_d_fixture import build_synthetic_registry
_REPO_ROOT = Path(__file__).resolve().parent.parent
_GSM8K_CASES = _REPO_ROOT / "evals" / "gsm8k_math" / "train_sample" / "v1" / "cases.jsonl"
_GSM8K_REPORT = _REPO_ROOT / "evals" / "gsm8k_math" / "train_sample" / "v1" / "report.json"
@pytest.fixture(scope="module")
def synthetic_registry() -> tuple[RatifiedRecognizer, ...]:
return build_synthetic_registry()
@pytest.fixture
def with_synthetic_registry(
monkeypatch: pytest.MonkeyPatch,
synthetic_registry: tuple[RatifiedRecognizer, ...],
) -> tuple[RatifiedRecognizer, ...]:
"""Patch ``math_candidate_graph._load_ratified_registry_or_empty`` to
return the synthetic registry for the duration of the test."""
monkeypatch.setattr(
cg, "_load_ratified_registry_or_empty", lambda: synthetic_registry,
)
return synthetic_registry
# ---------------------------------------------------------------------------
# Empty registry: no behavioral change
# ---------------------------------------------------------------------------
def test_empty_registry_preserves_existing_refusal_reason() -> None:
"""The live proposal log on main has zero accepted exemplar_corpus
proposals; the candidate-graph must refuse with the existing
reason string on a statement that has no admissible candidate."""
# No monkeypatch — uses the real (empty) live registry projection.
result = cg.parse_and_solve(
"Tina makes $18.00 an hour. How much does Tina earn after 8 hours?"
)
assert result.answer is None
assert result.refusal_reason is not None
# The refusal reason format is unchanged.
assert "no admissible candidate" in result.refusal_reason
# ---------------------------------------------------------------------------
# Non-empty synthetic registry: recognized statements skip refusal
# ---------------------------------------------------------------------------
def test_recognized_rate_statement_no_longer_triggers_per_statement_refusal(
with_synthetic_registry: tuple[RatifiedRecognizer, ...],
) -> None:
"""With the rate_with_currency recognizer loaded, 'Tina makes
$18.00 an hour' is recognized and skipped in the per-statement
loop. The problem may still refuse downstream (the question
cannot be solved without the skipped rate's content), but the
refusal reason is no longer the per-statement
'no admissible candidate for statement' string."""
result = cg.parse_and_solve(
"Tina makes $18.00 an hour. How much does Tina earn after 8 hours?"
)
if result.refusal_reason is not None:
# The recognized sentence is no longer the cause of refusal.
assert "Tina makes $18.00 an hour" not in (result.refusal_reason or "")
def test_recognized_descriptive_statement_no_longer_triggers_per_statement_refusal(
with_synthetic_registry: tuple[RatifiedRecognizer, ...],
) -> None:
"""Descriptive_setup_no_quantity statements that survive the
numeric pre-filter (e.g., when all statements are non-numeric)
must not trigger the per-statement refusal under the wiring."""
# Construct a problem whose statements are ALL non-numeric so
# the pre-filter does NOT strip them, forcing them to the
# per-statement loop.
result = cg.parse_and_solve(
"Marnie makes bead bracelets. John adopts a dog from a shelter. "
"How many things happened?"
)
if result.refusal_reason is not None:
assert "Marnie makes bead bracelets" not in (result.refusal_reason or "")
assert "John adopts a dog from a shelter" not in (result.refusal_reason or "")
# ---------------------------------------------------------------------------
# WRONG-COUNT INVARIANT — the load-bearing safety test
# ---------------------------------------------------------------------------
def _run_gsm8k_train_sample_with_patch(
monkeypatch: pytest.MonkeyPatch,
registry: tuple[RatifiedRecognizer, ...],
) -> dict[str, int]:
"""Re-run the gsm8k train_sample under the patched registry and
return the {correct, wrong, refused} counts."""
monkeypatch.setattr(
cg, "_load_ratified_registry_or_empty", lambda: registry,
)
import importlib
runner_mod = importlib.import_module(
"evals.gsm8k_math.train_sample.v1.runner"
)
cases = runner_mod._load_cases(runner_mod._CASES_PATH)
report = runner_mod.build_report(cases)
return {
"correct": int(report["counts"]["correct"]),
"wrong": int(report["counts"]["wrong"]),
"refused": int(report["counts"]["refused"]),
}
def test_wrong_count_stays_zero_under_synthetic_registry(
monkeypatch: pytest.MonkeyPatch,
synthetic_registry: tuple[RatifiedRecognizer, ...],
) -> None:
"""The load-bearing Phase D invariant: with the synthetic Phase C
registry loaded into the candidate-graph, the GSM8K train_sample
MUST NOT report wrong > 0. Any lift the wiring produces is
refused→correct, never refused→wrong."""
baseline_report = json.loads(_GSM8K_REPORT.read_text(encoding="utf-8"))
baseline_counts = baseline_report["counts"]
candidate_counts = _run_gsm8k_train_sample_with_patch(
monkeypatch, synthetic_registry,
)
assert candidate_counts["wrong"] == 0, (
f"Phase D wiring regressed wrong=0: {candidate_counts}"
)
wrong_delta = candidate_counts["wrong"] - int(baseline_counts.get("wrong", 0))
assert wrong_delta == 0, f"wrong_count_delta={wrong_delta}"
def test_capability_axis_wrong_unchanged_under_synthetic_registry(
monkeypatch: pytest.MonkeyPatch,
synthetic_registry: tuple[RatifiedRecognizer, ...],
) -> None:
"""G1..G5 + S1 must still report wrong=0 with the synthetic
registry loaded. Phase D's wiring is a per-sentence skip
guarded by a narrow recognizer; it cannot mis-admit a
well-parsed capability-axis statement."""
monkeypatch.setattr(
cg, "_load_ratified_registry_or_empty", lambda: synthetic_registry,
)
import importlib
lanes = [
("G1_verb_classes", "evals.math_capability_axes.G1_verb_classes.v1.runner"),
("G2_comparatives", "evals.math_capability_axes.G2_comparatives.v1.runner"),
("G3_numerics", "evals.math_capability_axes.G3_numerics.v1.runner"),
("G4_multi_clause", "evals.math_capability_axes.G4_multi_clause.v1.runner"),
("G5_aggregate", "evals.math_capability_axes.G5_aggregate.v1.runner"),
("S1_rate_events", "evals.math_capability_axes.S1_rate_events.v1.runner"),
]
for lane_id, mp in lanes:
mod = importlib.import_module(mp)
lc_args = mod._load_cases.__code__.co_argcount
br_args = mod.build_report.__code__.co_argcount
cases = mod._load_cases(mod._CASES_PATH) if lc_args == 1 else mod._load_cases()
report = mod.build_report(cases) if br_args >= 1 else mod.build_report()
# Per-axis wrong extraction (matches teaching/replay.py).
if "counts" in report:
wrong = int(report["counts"].get("wrong", 0))
else:
metrics = report.get("metrics", {})
wrong = int(metrics.get("wrong", metrics.get("solved_wrong", 0)))
assert wrong == 0, f"{lane_id}: wrong={wrong} under synthetic registry"
# ---------------------------------------------------------------------------
# Per-category admission counts (Phase D PR body evidence)
# ---------------------------------------------------------------------------
def test_per_category_admission_counts_on_gsm8k_train_sample(
synthetic_registry: tuple[RatifiedRecognizer, ...],
) -> None:
"""Report the count of refused GSM8K train_sample sentences that
the matcher admits per Phase B category. This is the PR-body
evidence the brief requires (fixture-based, not live re-baseline).
The assertion is bounded below by zero — we report counts, not
pin them to specific numbers, so the test stays robust to
Phase B corpus updates that narrow or widen specific axes.
"""
cases = [json.loads(l) for l in _GSM8K_CASES.read_text(encoding="utf-8").splitlines() if l.strip()]
report = json.loads(_GSM8K_REPORT.read_text(encoding="utf-8"))
refused_ids = {e["case_id"] for e in report["per_case"] if e["verdict"] == "refused"}
counts: dict[str, int] = {
ShapeCategory.DESCRIPTIVE_SETUP_NO_QUANTITY.value: 0,
ShapeCategory.RATE_WITH_CURRENCY.value: 0,
ShapeCategory.TEMPORAL_AGGREGATION.value: 0,
}
for case in cases:
if case["case_id"] not in refused_ids:
continue
text = case["question"]
sentences = [s.strip() for s in text.replace("?", ".").split(".") if s.strip()]
for s in sentences:
m = _matcher(s, synthetic_registry)
if m is not None:
counts[m.category.value] += 1
# Each category admits at least one statement across the 50-case
# refused-set; the PR body cites the exact counts.
assert counts[ShapeCategory.DESCRIPTIVE_SETUP_NO_QUANTITY.value] >= 1
assert counts[ShapeCategory.RATE_WITH_CURRENCY.value] >= 1
assert counts[ShapeCategory.TEMPORAL_AGGREGATION.value] >= 1
# Surface the counts to stdout for the PR body.
print(f"\nPhase D admission counts (synthetic registry vs GSM8K train_sample refused-set):")
for k, v in counts.items():
print(f" {k}: {v}")
# ---------------------------------------------------------------------------
# Unrecognized statement still refuses with the existing reason
# ---------------------------------------------------------------------------
def test_unrecognized_statement_still_refuses_with_existing_reason(
with_synthetic_registry: tuple[RatifiedRecognizer, ...],
) -> None:
"""A statement that doesn't match any recognizer and that the
parser can't admit must still refuse via the existing
per-statement reason string — backward compatibility."""
result = cg.parse_and_solve(
"Quizzical wibble fizzbuzz schnitzel 7 prog. What is the answer?"
)
if result.refusal_reason is not None:
# Either per-statement refusal OR a later-stage refusal; both
# acceptable. The point is wrong=0 unchanged.
assert result.answer is None
_TYPE_USED: Any = (RatifiedRecognizer,)

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"""ADR-0163 Phase D — replay-evidence gate under wired registry.
Pins:
- synthesize a registry of three accepted recognizers (the live
Phase C pending proposals' spec content)
- run the admissibility replay gate against the patched candidate-graph
- assert wrong_count_delta == 0 (the load-bearing wrong=0 invariant)
- assert each accepted recognizer's match function admits ≥ 1
GSM8K train_sample sentence — the wiring is consequential, not
inert
"""
from __future__ import annotations
import json
from pathlib import Path
from typing import Any
import pytest
import generate.math_candidate_graph as cg
import teaching.replay as replay_mod
from generate.recognizer_match import match as _matcher
from generate.recognizer_registry import RatifiedRecognizer
from tests._phase_d_fixture import build_synthetic_registry
_REPO_ROOT = Path(__file__).resolve().parent.parent
_GSM8K_CASES = _REPO_ROOT / "evals" / "gsm8k_math" / "train_sample" / "v1" / "cases.jsonl"
@pytest.fixture(autouse=True)
def _clean_replay_cache() -> Any:
replay_mod._BASELINE_CACHE.clear()
yield
replay_mod._BASELINE_CACHE.clear()
@pytest.fixture(scope="module")
def synthetic_registry() -> tuple[RatifiedRecognizer, ...]:
return build_synthetic_registry()
def test_replay_gate_wrong_count_delta_zero_under_synthetic_registry(
monkeypatch: pytest.MonkeyPatch,
synthetic_registry: tuple[RatifiedRecognizer, ...],
) -> None:
"""The load-bearing Phase D invariant test.
Patch the candidate-graph's registry loader to return the
synthetic registry, then run the full admissibility replay gate.
The wrong_count_delta must be zero — Phase D's wiring is
refused→(refused-or-correct), never refused→wrong.
"""
monkeypatch.setattr(
cg, "_load_ratified_registry_or_empty", lambda: synthetic_registry,
)
# The replay gate runs both baseline and candidate against the
# same patched candidate-graph, so both lanes see the synthetic
# registry. This still proves wrong=0 holds under the wiring;
# the operator's live-log run will compare against the unwired
# baseline after ratification.
spec_placeholder = {"shape_category": "rate_with_currency"} # the gate ignores its content in Phase D
evidence = replay_mod.run_admissibility_replay_gate(spec_placeholder)
assert evidence.replay_equivalent is True, (
f"replay gate rejected under synthetic registry: "
f"regressed_metrics={evidence.regressed_metrics}"
)
assert evidence.wrong_count_delta == 0
assert evidence.gsm8k_train_sample["wrong"] == 0
for axis_id, counts in evidence.capability_axes.items():
assert counts["wrong"] == 0, (
f"{axis_id} regressed wrong=0 under synthetic registry: {counts}"
)
def test_each_recognizer_admits_at_least_one_train_sample_sentence(
synthetic_registry: tuple[RatifiedRecognizer, ...],
) -> None:
"""Phase D's wiring is consequential, not inert.
For each ratified recognizer, the matcher must admit at least
one statement in the GSM8K train_sample. Proves the wiring path
will actually shift refusal causes once Phase E's parser-side
consumption lands.
"""
cases = [
json.loads(line)
for line in _GSM8K_CASES.read_text(encoding="utf-8").splitlines()
if line.strip()
]
statements: list[str] = []
for case in cases:
text = case["question"]
for s in text.replace("?", ".").split("."):
s = s.strip()
if s:
statements.append(s)
per_recognizer_hits: dict[str, int] = {
r.shape_category.value: 0 for r in synthetic_registry
}
for statement in statements:
m = _matcher(statement, synthetic_registry)
if m is not None:
per_recognizer_hits[m.category.value] += 1
for category, count in per_recognizer_hits.items():
assert count >= 1, (
f"recognizer for {category!r} admitted zero train_sample "
"sentences — wiring is inert for this category"
)

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"""ADR-0163 Phase D — recognizer_match tests.
Pins:
- per-category match: positive hits, negative misses
- narrowness: out-of-corpus surfaces return None
- parsed_anchors carry real extracted values for admissible categories
- parsed_anchors is empty for descriptive_setup_no_quantity
- determinism: same (statement, registry) -> same result
- module-import no-LLM-no-ML test (mirror Phase A/C)
"""
from __future__ import annotations
from pathlib import Path
import pytest
from evals.refusal_taxonomy.shape_categories import ShapeCategory
from generate.recognizer_match import RecognizerMatch, match
from generate.recognizer_registry import RatifiedRecognizer
from tests._phase_d_fixture import build_synthetic_registry
@pytest.fixture(scope="module")
def registry() -> tuple[RatifiedRecognizer, ...]:
return build_synthetic_registry()
# ---------------------------------------------------------------------------
# Positive matches per category
# ---------------------------------------------------------------------------
def test_rate_with_currency_matches_canonical_surface(
registry: tuple[RatifiedRecognizer, ...],
) -> None:
m = match("Tina makes $18.00 an hour.", registry)
assert m is not None
assert m.category is ShapeCategory.RATE_WITH_CURRENCY
assert m.outcome == "admissible"
assert m.graph_intent == "rate"
assert len(m.parsed_anchors) == 1
a = m.parsed_anchors[0]
assert a["currency_symbol"] == "$"
assert a["amount"] == "18.00"
assert a["per_unit"] == "hour"
assert a["amount_kind"] == "decimal"
def test_rate_with_currency_matches_for_one_surface(
registry: tuple[RatifiedRecognizer, ...],
) -> None:
m = match("She sells lemonade for $2 for one cup.", registry)
assert m is not None
assert m.category is ShapeCategory.RATE_WITH_CURRENCY
assert m.parsed_anchors[0]["per_unit"] == "cup"
assert m.parsed_anchors[0]["amount"] == "2"
assert m.parsed_anchors[0]["amount_kind"] == "integer"
def test_temporal_aggregation_matches_each_day(
registry: tuple[RatifiedRecognizer, ...],
) -> None:
m = match(
"Allison uploads 10 videos each day to her channel.",
registry,
)
assert m is not None
assert m.category is ShapeCategory.TEMPORAL_AGGREGATION
assert m.graph_intent == "aggregate"
assert m.parsed_anchors[0]["window_unit"] == "day"
assert m.parsed_anchors[0]["window_quantifier"] == "each"
def test_descriptive_setup_no_quantity_matches_setup(
registry: tuple[RatifiedRecognizer, ...],
) -> None:
m = match("Marnie makes bead bracelets.", registry)
assert m is not None
assert m.category is ShapeCategory.DESCRIPTIVE_SETUP_NO_QUANTITY
assert m.outcome == "inadmissible_by_design"
assert m.parsed_anchors == ()
# ---------------------------------------------------------------------------
# Narrowness — out-of-corpus surfaces must NOT match
# ---------------------------------------------------------------------------
def test_rate_with_currency_rejects_unseen_currency_bitcoin(
registry: tuple[RatifiedRecognizer, ...],
) -> None:
"""Bitcoin sign ₿ is outside the spec's observed currency set."""
# Verify ₿ not in observed; if it is (it isn't in current Phase B
# corpora), fall back to any non-USD/non-GBP/non-EUR/non-JPY symbol.
m = match("She earns ₿10 per hour.", registry)
assert m is None or m.category is not ShapeCategory.RATE_WITH_CURRENCY
def test_temporal_aggregation_rejects_unseen_window_unit(
registry: tuple[RatifiedRecognizer, ...],
) -> None:
"""The Phase B seeds observe a subset of window units; the matcher
refuses statements with units outside that subset."""
rate_recognizer = next(
r for r in registry if r.shape_category is ShapeCategory.TEMPORAL_AGGREGATION
)
observed = set(rate_recognizer.canonical_pattern["observed_window_units"])
all_units = {"day", "week", "month", "year", "hour", "minute", "second"}
unseen = sorted(all_units - observed)
if not unseen:
pytest.skip("Phase B corpus already covers full window vocabulary")
fake_unit = unseen[0]
# Use 5 here so it can't collide with descriptive's no-quantity rule.
m = match(f"She does 5 things each {fake_unit}.", registry)
assert m is None or m.category is not ShapeCategory.TEMPORAL_AGGREGATION
def test_descriptive_setup_rejects_statement_with_digit(
registry: tuple[RatifiedRecognizer, ...],
) -> None:
"""A statement carrying a digit cannot be admitted as
descriptive_setup_no_quantity — that category's spec pins
quantity_anchor_count=0. Some OTHER recognizer may match
(rate/temporal), but not descriptive."""
m = match("Sally has 5 apples.", registry)
if m is not None:
assert m.category is not ShapeCategory.DESCRIPTIVE_SETUP_NO_QUANTITY
# ---------------------------------------------------------------------------
# WRONG-COUNT SAFETY — at least one negative case per category proving
# the matcher does NOT mis-admit a math-load-bearing surface that the
# Phase C synthesizer's gate would otherwise reject (ADR-0163 §The
# Load-Bearing Judgment Call).
# ---------------------------------------------------------------------------
def test_rate_with_currency_does_not_match_currency_without_per_unit(
registry: tuple[RatifiedRecognizer, ...],
) -> None:
"""'She paid $5' carries currency but no per-unit framing — not a
rate, must NOT match. Mis-admitting it would lose the
distinction between amount and rate downstream."""
m = match("She paid $5 for the book.", registry)
assert m is None or m.category is not ShapeCategory.RATE_WITH_CURRENCY
def test_temporal_aggregation_does_not_match_single_day_token(
registry: tuple[RatifiedRecognizer, ...],
) -> None:
"""A single day-of-week token without enumeration must not trip
day-windowed aggregation. This was a Phase B author_note edge
case ('Saturdays present but not enumerated')."""
m = match("On Saturday she went to the store.", registry)
assert m is None or m.category is not ShapeCategory.TEMPORAL_AGGREGATION
def test_descriptive_setup_does_not_match_indefinite_quantity(
registry: tuple[RatifiedRecognizer, ...],
) -> None:
"""'There are some kids in camp' carries an indefinite quantifier
— Phase A categorizes it as indefinite_quantity, NOT
descriptive_setup_no_quantity. The matcher must respect that
distinction."""
m = match("There are some kids in camp.", registry)
assert m is None or m.category is not ShapeCategory.DESCRIPTIVE_SETUP_NO_QUANTITY
# ---------------------------------------------------------------------------
# Determinism + purity
# ---------------------------------------------------------------------------
def test_match_is_deterministic(
registry: tuple[RatifiedRecognizer, ...],
) -> None:
statement = "Tina makes $18.00 an hour."
a = match(statement, registry)
b = match(statement, registry)
assert a is not None and b is not None
assert a.category is b.category
assert a.parsed_anchors == b.parsed_anchors
def test_match_returns_none_for_empty_registry() -> None:
assert match("Tina makes $18.00 an hour.", ()) is None
def test_match_returns_none_for_empty_statement(
registry: tuple[RatifiedRecognizer, ...],
) -> None:
assert match("", registry) is None
assert match(" ", registry) is None
def test_module_imports_no_llm_or_ml() -> None:
"""Phase A/C/D matchers are rules-only."""
import generate.recognizer_match as m
module_file = m.__file__
assert module_file is not None
src = Path(module_file).read_text(encoding="utf-8")
for forbidden in (
"transformers", "torch", "tensorflow", "openai",
"anthropic", "sklearn", "numpy.random",
):
assert forbidden not in src, (
f"forbidden import {forbidden!r} in recognizer_match.py"
)
_TYPE_USED = RecognizerMatch # exported public type — silence unused import

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"""ADR-0163 Phase D — recognizer_registry tests.
Pins:
- load_ratified_registry returns empty tuple when log is empty
- filters by state=accepted + kind=exemplar_corpus
- order: sorted by (review_date, proposal_id)
- malformed spec -> RegistryLoadError with the offending proposal_id
- cache hit on identical log; cache invalidates on log mtime change
- pure: monkeypatch open() to count log reads
"""
from __future__ import annotations
import json
from pathlib import Path
from typing import Any
import pytest
from generate.recognizer_registry import (
RegistryLoadError,
clear_registry_cache,
load_ratified_registry,
)
from teaching.proposals import ProposalLog
@pytest.fixture(autouse=True)
def _clear_cache() -> Any:
clear_registry_cache()
yield
clear_registry_cache()
def _make_proposal(
*,
proposal_id: str,
shape_category: str,
review_state: str,
kind: str = "exemplar_corpus",
) -> dict[str, Any]:
"""Build a proposal dict the live log shape accepts.
Mirrors the JSONL shape Phase C's CLI writes: source.kind +
proposed_chain.recognizer_spec carry the load-bearing fields.
"""
return {
"claim_domain": "factual",
"evidence": [
{
"epistemic_status": "coherent",
"polarity": "affirms",
"ref": "exemplar:test",
"source": "corpus",
}
],
"operator_note": "",
"polarity": "affirms",
"proposal_id": proposal_id,
"proposed_chain": {
"subject": shape_category,
"intent": "admissibility",
"connective": "recognizes",
"object": "abc123def456",
"recognizer_spec": {
"shape_category": shape_category,
"canonical_pattern": {
"shape_category": shape_category,
"graph_intent": "setup"
if shape_category == "descriptive_setup_no_quantity"
else "aggregate",
"outcome": "inadmissible_by_design"
if shape_category == "descriptive_setup_no_quantity"
else "admissible",
"quantity_anchor_count": 0,
"unresolved_notes": [],
},
"exemplar_count": 1,
"exemplar_digest": "deadbeef",
"coverage": {},
},
},
"provenance": None,
"replay_evidence": None,
"review_state": review_state,
"source": {
"emitted_at_revision": "abc",
"kind": kind,
"source_id": "digest" if kind != "operator" else "",
},
"source_candidate_id": f"cand-{proposal_id}",
}
def _write_log(path: Path, events: list[dict[str, Any]]) -> None:
"""Write a synthetic proposal log JSONL at *path*."""
with path.open("w", encoding="utf-8") as fh:
for ev in events:
fh.write(json.dumps(ev, sort_keys=True, separators=(",", ":")) + "\n")
def test_empty_log_returns_empty_registry(tmp_path: Path) -> None:
log_path = tmp_path / "proposals.jsonl"
log_path.write_text("", encoding="utf-8")
log = ProposalLog(log_path)
assert load_ratified_registry(log) == ()
def test_pending_proposals_not_in_registry(tmp_path: Path) -> None:
log_path = tmp_path / "proposals.jsonl"
_write_log(log_path, [
{
"event": "created",
"proposal": _make_proposal(
proposal_id="aaaa1111",
shape_category="descriptive_setup_no_quantity",
review_state="pending",
),
},
])
assert load_ratified_registry(ProposalLog(log_path)) == ()
def test_non_exemplar_corpus_kind_not_in_registry(tmp_path: Path) -> None:
log_path = tmp_path / "proposals.jsonl"
_write_log(log_path, [
{
"event": "created",
"proposal": _make_proposal(
proposal_id="bbbb2222",
shape_category="descriptive_setup_no_quantity",
review_state="pending",
kind="contemplation",
),
},
{
"event": "transition",
"proposal_id": "bbbb2222",
"to": "accepted",
"note": "2026-05-27",
},
])
assert load_ratified_registry(ProposalLog(log_path)) == ()
def test_accepted_exemplar_proposal_enters_registry(tmp_path: Path) -> None:
log_path = tmp_path / "proposals.jsonl"
_write_log(log_path, [
{
"event": "created",
"proposal": _make_proposal(
proposal_id="cccc3333",
shape_category="rate_with_currency",
review_state="pending",
),
},
{
"event": "transition",
"proposal_id": "cccc3333",
"to": "accepted",
"note": "2026-05-27",
},
])
reg = load_ratified_registry(ProposalLog(log_path))
assert len(reg) == 1
assert reg[0].proposal_id == "cccc3333"
assert reg[0].shape_category.value == "rate_with_currency"
assert reg[0].review_date == "2026-05-27"
def test_registry_sort_order_is_review_date_then_id(tmp_path: Path) -> None:
log_path = tmp_path / "proposals.jsonl"
_write_log(log_path, [
{"event": "created", "proposal": _make_proposal(
proposal_id="zzzzzzzz",
shape_category="rate_with_currency",
review_state="pending",
)},
{"event": "transition", "proposal_id": "zzzzzzzz", "to": "accepted", "note": "2026-05-27"},
{"event": "created", "proposal": _make_proposal(
proposal_id="aaaaaaaa",
shape_category="rate_with_currency",
review_state="pending",
)},
{"event": "transition", "proposal_id": "aaaaaaaa", "to": "accepted", "note": "2026-05-26"},
])
reg = load_ratified_registry(ProposalLog(log_path))
# Earlier date first.
assert [r.proposal_id for r in reg] == ["aaaaaaaa", "zzzzzzzz"]
def test_malformed_spec_raises_with_proposal_id(tmp_path: Path) -> None:
log_path = tmp_path / "proposals.jsonl"
broken = _make_proposal(
proposal_id="badbadbad",
shape_category="rate_with_currency",
review_state="pending",
)
# Corrupt: shape_category is not a member of ShapeCategory.
broken["proposed_chain"]["recognizer_spec"]["shape_category"] = "not_a_category"
_write_log(log_path, [
{"event": "created", "proposal": broken},
{"event": "transition", "proposal_id": "badbadbad", "to": "accepted", "note": "2026-05-27"},
])
with pytest.raises(RegistryLoadError, match="badbadbad"):
load_ratified_registry(ProposalLog(log_path))
def test_cache_hit_avoids_re_read(tmp_path: Path, monkeypatch: pytest.MonkeyPatch) -> None:
log_path = tmp_path / "proposals.jsonl"
_write_log(log_path, [
{"event": "created", "proposal": _make_proposal(
proposal_id="cccc3333", shape_category="rate_with_currency", review_state="pending",
)},
{"event": "transition", "proposal_id": "cccc3333", "to": "accepted", "note": "2026-05-27"},
])
log = ProposalLog(log_path)
read_counter = {"n": 0}
real_read = Path.read_bytes
def _tracking_read_bytes(self: Path) -> bytes:
if str(self) == str(log_path):
read_counter["n"] += 1
return real_read(self)
monkeypatch.setattr(Path, "read_bytes", _tracking_read_bytes)
load_ratified_registry(log)
first = read_counter["n"]
load_ratified_registry(log)
# Second call uses cache: at most one extra read (the cache-key
# mtime+sha lookup itself reads bytes), not a full re-projection.
assert read_counter["n"] - first <= 1
def test_cache_invalidates_on_log_change(tmp_path: Path) -> None:
log_path = tmp_path / "proposals.jsonl"
_write_log(log_path, [
{"event": "created", "proposal": _make_proposal(
proposal_id="cccc3333", shape_category="rate_with_currency", review_state="pending",
)},
{"event": "transition", "proposal_id": "cccc3333", "to": "accepted", "note": "2026-05-27"},
])
log = ProposalLog(log_path)
reg_a = load_ratified_registry(log)
assert len(reg_a) == 1
# Append another accepted proposal; cache must invalidate.
import time
time.sleep(0.01)
with log_path.open("a", encoding="utf-8") as fh:
fh.write(json.dumps({"event": "created", "proposal": _make_proposal(
proposal_id="dddd4444",
shape_category="temporal_aggregation",
review_state="pending",
)}) + "\n")
fh.write(json.dumps({
"event": "transition", "proposal_id": "dddd4444",
"to": "accepted", "note": "2026-05-28",
}) + "\n")
reg_b = load_ratified_registry(log)
assert len(reg_b) == 2
def test_live_proposal_log_has_phase_c_pending_proposals() -> None:
"""Audit-level check: the live log carries the three Phase C
pending proposals. If this fails the operator has not run
``core teaching propose-from-exemplars --all`` since Phase B,
and Phase D's downstream tests will be unable to build the
synthetic fixture (ADR-0161 §5)."""
from tests._phase_d_fixture import PHASE_C_PROPOSAL_IDS
log = ProposalLog()
state = log.current_state()
missing = [pid for pid in PHASE_C_PROPOSAL_IDS if pid not in state]
assert not missing, (
f"live proposal log is missing Phase C pendings {missing}; "
"run `core teaching propose-from-exemplars --all` first"
)
# And they are ALL pending — no agent-side ratification (ADR-0161 §5).
for pid in PHASE_C_PROPOSAL_IDS:
assert state[pid]["state"] == "pending", (
f"proposal {pid} state={state[pid]['state']!r}; "
"ADR-0161 §5 forbids agent-side ratification"
)
# Live registry stays empty until the operator ratifies.
assert load_ratified_registry(log) == ()