Merge pull request #136 from AssetOverflow/feat/adr-0123-lane-shape-symbolic-logic-fix

feat: ADR-0123 — re-map symbolic_logic to inference_shape (unblocks ADR-0122)

core/capability/expert_demo.py

@@ -58,7 +58,7 @@ LANE_SHAPE_REGISTRY: dict[str, str] = {
     "cognition": "cognition_shape",
     "elementary_mathematics_ood": "accuracy_shape",
     "foundational_physics_ood": "accuracy_shape",
-    "symbolic_logic": "symbolic_logic_shape",
+    "symbolic_logic": "inference_shape",
     "hebrew_fluency": "accuracy_shape",
     "koine_greek_fluency": "accuracy_shape",
     "inference_closure": "inference_shape",
@@ -160,7 +160,6 @@ def _check_refusal_shape(lane_id: str, metrics: Mapping[str, Any]) -> tuple[bool
 SHAPE_CHECKERS: dict[str, Any] = {
     "cognition_shape": _check_cognition_shape,
     "accuracy_shape": _check_accuracy_shape,
-    "symbolic_logic_shape": _check_accuracy_shape,
     "inference_shape": _check_inference_shape,
     "refusal_shape": _check_refusal_shape,
 }

docs/decisions/ADR-0123-symbolic-logic-shape-remap.md

@@ -0,0 +1,71 @@
+# ADR-0123 — `symbolic_logic` Lane-Shape Remap (ADR-0109 Amendment)
+
+**Status:** Accepted
+**Date:** 2026-05-22
+**Author:** CORE agents + reviewers
+**Amends:** ADR-0109
+**Depends on:** ADR-0109, ADR-0122
+
+---
+
+## Context
+
+Under [ADR-0109](file:///Users/kaizenpro/.gemini/antigravity/worktrees/core/fix-symbolic-logic-shape/docs/decisions/ADR-0109-lane-shape-aware-thresholds.md), threshold verification rules are lane-shape-aware, mapping specific lane IDs to defined metric shapes. [ADR-0109](file:///Users/kaizenpro/.gemini/antigravity/worktrees/core/fix-symbolic-logic-shape/docs/decisions/ADR-0109-lane-shape-aware-thresholds.md) mapped the `symbolic_logic` lane to `symbolic_logic_shape`, which internally dispatched to the accuracy-shape threshold checker (`_check_accuracy_shape`).
+
+However, as documented in the deferred promotion of `systems_software` ([ADR-0122](file:///Users/kaizenpro/.gemini/antigravity/worktrees/core/fix-symbolic-logic-shape/docs/decisions/ADR-0122-systems-software-audit-passed-deferred.md)), the `symbolic_logic` lane output payload actually contains inference-style metrics (`all_pass_rate`, `replay_determinism`, and `overall_pass`) rather than accuracy-shape metrics (`accuracy` or `passed/total`). This mismatch caused the gate to fail closed with the error message: `lane 'symbolic_logic' missing accuracy (and no passed/total fallback)`.
+
+This amendment corrects the mapping to unblock the `systems_software` promotion.
+
+---
+
+## Decision
+
+Re-map the `symbolic_logic` lane to `inference_shape` within the `LANE_SHAPE_REGISTRY` in [core/capability/expert_demo.py](file:///Users/kaizenpro/.gemini/antigravity/worktrees/core/fix-symbolic-logic-shape/core/capability/expert_demo.py):
+
+```python
+LANE_SHAPE_REGISTRY["symbolic_logic"] = "inference_shape"
+```
+
+### Rationale
+The `symbolic_logic` lane validates propositional inference closure. Because it checks deterministic symbolic inferences rather than approximate/statistical accuracy scalars, it naturally produces the standard inference-style metrics:
+- `all_pass_rate`
+- `replay_determinism`
+- `overall_pass`
+
+Mapping it to `inference_shape` aligns the contract verification logic with the lane's actual runtime evidence schema.
+
+Additionally, because no other lane in the registry maps to `symbolic_logic_shape`, this shape checker is retired and removed from `SHAPE_CHECKERS` to preserve code cleanliness and avoid dead-shape drift.
+
+---
+
+## Invariants
+
+### `inference_shape_thresholds_applied`
+The existing `inference_shape` thresholds defined in [ADR-0109](file:///Users/kaizenpro/.gemini/antigravity/worktrees/core/fix-symbolic-logic-shape/docs/decisions/ADR-0109-lane-shape-aware-thresholds.md) now govern `symbolic_logic` verification:
+- `all_pass_rate >= 0.95`
+- `replay_determinism == 1.0`
+- `overall_pass == True`
+
+---
+
+## Acceptance Evidence
+
+Accepted when:
+- The registry mapping in [core/capability/expert_demo.py](file:///Users/kaizenpro/.gemini/antigravity/worktrees/core/fix-symbolic-logic-shape/core/capability/expert_demo.py) is amended to map `symbolic_logic` to `inference_shape`.
+- Unused `symbolic_logic_shape` is removed from `SHAPE_CHECKERS`.
+- A unit test `TestSymbolicLogicShapeGate` in [tests/test_lane_shape_thresholds.py](file:///Users/kaizenpro/.gemini/antigravity/worktrees/core/fix-symbolic-logic-shape/tests/test_lane_shape_thresholds.py) asserts that:
+  - `resolve_lane_shape("symbolic_logic") == "inference_shape"`
+  - `symbolic_logic` results carrying compliant inference-style metrics pass the gate successfully.
+
+---
+
+## Consequences
+
+- The contract blocker for `systems_software` is resolved: the lane gate now evaluates `symbolic_logic` outputs under the correct metric schema.
+- The deferral in [ADR-0122](file:///Users/kaizenpro/.gemini/antigravity/worktrees/core/fix-symbolic-logic-shape/docs/decisions/ADR-0122-systems-software-audit-passed-deferred.md) can be resolved in a subsequent promotion attempt (likely ADR-0124) when a signed promotion claim is recorded.
+
+---
+
+## Out of Scope
+
+- Actually signing the `systems_software` claim or updating the `audit_passed_claims` in `reviewers.yaml` (reserved for a follow-up promotion ADR).

tests/test_adr_0122_deferral.py

@@ -37,26 +37,12 @@ class TestAdr0122Deferral:
         assert row["predicates"]["audit_passed"] is False
 
     def test_named_blocker_matches_gate_reason(self) -> None:
-        reviewer = Reviewer(
-            reviewer_id="shay-j",
-            display_name="Joshua Shay",
-            role="primary",
-            domains=("*",),
-            review_scope=("pack", "proposal", "chain", "eval"),
-            provenance="adr-0092:bootstrap:2026-05-21",
-        )
-        claim = ExpertDemoClaim(
-            domain_id="systems_software",
-            evidence_lanes=_SYSTEMS_LANES,
-            evidence_revision="adr-0122:reviewed:2026-05-22",
-            signed_by="shay-j",
-            claim_digest="0" * 64,
-        )
-        registry = ReviewerRegistry(
-            schema_version=1,
-            reviewers=(reviewer,),
-            expert_demo_claims=(claim,),
-        )
+        from pathlib import Path
+        from core.capability.reviewers import load_reviewer_registry
+        from core.capability.sources import LEDGER_SOURCES
+
+        repo_root = Path(__file__).resolve().parent.parent
+        registry = load_reviewer_registry(repo_root / LEDGER_SOURCES.reviewers)
         lane_results = materialise_lane_results(_SYSTEMS_LANES, fetch_split=_fetch)
 
         verdict = evaluate_expert_demo(
@@ -68,7 +54,4 @@ class TestAdr0122Deferral:
         )
 
         assert verdict.passed is False
-        assert (
-            verdict.reason
-            == "lane 'symbolic_logic' missing accuracy (and no passed/total fallback) (split=public)"
-        )
+        assert verdict.reason == "no audit_passed_claims entry for this domain"

tests/test_expert_demo_contract.py

@@ -62,7 +62,7 @@ _SHAPE_FIXTURES = {
     "inference_closure": _INFERENCE_METRICS,
     "elementary_mathematics_ood": _ACCURACY_METRICS,
     "foundational_physics_ood": _ACCURACY_METRICS,
-    "symbolic_logic": _ACCURACY_METRICS,
+    "symbolic_logic": _INFERENCE_METRICS,
     "hebrew_fluency": _ACCURACY_METRICS,
     "koine_greek_fluency": _ACCURACY_METRICS,
 }

tests/test_lane_shape_thresholds.py

@@ -162,3 +162,62 @@ class TestShapeThresholdValues:
     def test_inference_shape_minimums(self) -> None:
         assert ALL_PASS_RATE_MIN == 0.95
         assert REPLAY_DETERMINISM_MIN == 1.0
+
+
+class TestSymbolicLogicShapeGate:
+    def test_symbolic_logic_resolves_to_inference_shape(self) -> None:
+        assert resolve_lane_shape("symbolic_logic") == "inference_shape"
+
+    def test_symbolic_logic_with_inference_metrics_passes(self) -> None:
+        reviewer = Reviewer(
+            reviewer_id="shay-j",
+            display_name="Joshua Shay",
+            role="primary",
+            domains=("*",),
+            review_scope=("pack", "proposal", "chain", "eval"),
+            provenance="adr-0092:bootstrap:2026-05-21",
+        )
+        
+        metrics = {
+            "all_pass_rate": 0.98,
+            "replay_determinism": 1.0,
+            "overall_pass": True,
+        }
+        
+        lane_results = {
+            "symbolic_logic": {
+                "public": metrics,
+                "holdout": metrics,
+            }
+        }
+        
+        from core.capability.expert_demo import derive_evidence_digest
+        digest = derive_evidence_digest(
+            domain_id="systems_software",
+            evidence_revision="rev1",
+            evidence_lanes=("symbolic_logic",),
+            lane_results=lane_results,
+        )
+        
+        claim = ExpertDemoClaim(
+            domain_id="systems_software",
+            evidence_lanes=("symbolic_logic",),
+            evidence_revision="rev1",
+            signed_by="shay-j",
+            claim_digest=digest,
+        )
+        
+        registry = ReviewerRegistry(
+            schema_version=1, reviewers=(reviewer,), expert_demo_claims=(claim,)
+        )
+        
+        verdict = evaluate_expert_demo(
+            domain_id="systems_software",
+            reasoning_capable=True,
+            registry=registry,
+            domain_lanes=("symbolic_logic",),
+            lane_results=lane_results,
+        )
+        assert verdict.passed is True
+        assert verdict.reason == "all audit-passed predicates satisfied"
+