feat(reasoning): Regulatory Reasoning Engine MVP (scope/obligations/implementation/interpretation)

Deterministic reasoning layer ON TOP of the Legal Knowledge Graph (obligation
registry) and the Compliance Execution Graph (control mapping/evidence). Answers
which regulations apply to a concrete product, which obligations follow, whether
the customer's implementation covers them, and whether a customer interpretation
is too narrow/broad/plausible.

- ProductProfile with tri-state facts (Optional[bool]=None => uncertain, never
  false security); safe predicate evaluator (no eval).
- 6 regulation triggers (CRA/MaschinenVO/RED/EMV/DataAct/NIS2) with missing-fact
  prompts; 24 obligation scope rules.
- CRA obligation_ids RE-USED verbatim from the registry (93 ids) — never re-minted
  (control_uuid trap); Machine/Data-Act flagged proposed=True.
- required_evidence constrained to the framework-agnostic shared evidence catalog;
  capabilities echo the planned Obligation->Capability layer.
- Overlap groups (CRA<->MaschinenVO cyber-safety) + evidence-for-multiple (USP).
- 4 endpoints POST /reasoning/{scope,obligations,implementation-assessment,
  interpretation-assessment}; thin handlers, registered in api/__init__.py.
- 22 tests (5 machine-builder scenarios + 10 acceptance questions). No DB
  migration, no RAG, no new controls.

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

backend-compliance/compliance/reasoning/interpretation_engine.py

@@ -0,0 +1,65 @@
+"""Interpretation review engine (spec Modus 4).
+
+Evaluates whether a customer's legal interpretation is plausible, too narrow,
+too broad, etc. Matches the interpretation against a curated pattern library;
+no match -> `uncertain` plus a request for the missing context (never invent a
+verdict, spec §6.3).
+"""
+
+from __future__ import annotations
+
+import hashlib
+from typing import Optional
+
+from .enums import Confidence, InterpretationVerdict
+from .schemas import InterpretationAssessment, ProductProfile
+from .taxonomy_interpretations import INTERPRETATION_PATTERNS, InterpretationPattern
+
+
+def _interpretation_id(raw: str) -> str:
+    digest = hashlib.sha1(raw.strip().lower().encode("utf-8")).hexdigest()
+    return "interp_%s" % digest[:10]
+
+
+def _best_match(text: str) -> Optional[InterpretationPattern]:
+    low = text.lower()
+    best: Optional[InterpretationPattern] = None
+    best_score = 0
+    for pattern in INTERPRETATION_PATTERNS:
+        score = sum(1 for t in pattern.triggers if t in low)
+        if score > best_score:
+            best, best_score = pattern, score
+    return best
+
+
+def assess_interpretation(
+    raw_interpretation: str, profile: Optional[ProductProfile] = None
+) -> InterpretationAssessment:
+    interp_id = _interpretation_id(raw_interpretation)
+    pattern = _best_match(raw_interpretation)
+
+    if pattern is None:
+        return InterpretationAssessment(
+            interpretation_id=interp_id,
+            raw_interpretation=raw_interpretation,
+            assessment=InterpretationVerdict.UNCERTAIN,
+            corrected_interpretation=(
+                "Diese Auslegung lässt sich ohne weitere Angaben nicht bewerten. Bitte Produkt, "
+                "Rolle, Marktzugang und die konkret betroffene Pflicht benennen."
+            ),
+            explanation="Kein bekanntes Auslegungsmuster erkannt — bewusst keine Scheinsicherheit.",
+            confidence=Confidence.LOW,
+        )
+
+    return InterpretationAssessment(
+        interpretation_id=interp_id,
+        raw_interpretation=raw_interpretation,
+        affected_regulations=pattern.affected_regulations,
+        affected_obligations=pattern.affected_obligations,
+        assessment=pattern.verdict,
+        risks=pattern.risks,
+        corrected_interpretation=pattern.corrected_interpretation,
+        legal_basis_refs=pattern.legal_basis_refs,
+        explanation=pattern.explanation,
+        confidence=pattern.confidence,
+    )