feat(corroboration): treatment classifier + polarity (INV-COR2, X11)

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

mcp-server/src/legal_mcp/services/corroboration.py

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+"""X11 citation corroboration — classify treatment, match to halacha, aggregate.
+
+Phase 1: builds the SIGNAL only (no approval changes). See docs/spec/X11.
+All LLM calls go through the local claude_session bridge (Opus 4.8 @ xhigh),
+same architectural rule as the other extractors (local MCP only).
+"""
+from __future__ import annotations
+import logging
+from legal_mcp import config
+from legal_mcp.config import parse_llm_json
+from legal_mcp.services import claude_session
+
+logger = logging.getLogger(__name__)
+
+TREATMENT_POSITIVE = {"followed", "explained"}
+TREATMENT_NEGATIVE = {"distinguished", "criticized", "questioned", "overruled"}
+TREATMENT_NEUTRAL = {"mentioned"}
+_VALID_TREATMENT = TREATMENT_POSITIVE | TREATMENT_NEGATIVE | TREATMENT_NEUTRAL
+
+def is_positive(t: str) -> bool: return t in TREATMENT_POSITIVE
+def is_negative(t: str) -> bool: return t in TREATMENT_NEGATIVE
+
+def _coerce_treatment(raw: dict) -> str:
+    t = str((raw or {}).get("treatment", "")).strip().lower()
+    return t if t in _VALID_TREATMENT else "mentioned"
+
+
+_TREATMENT_PROMPT = """אתה משפטן בכיר. נתון ציטוט של פסק/החלטה קודמים בתוך החלטה מאוחרת.
+סווג כיצד ההחלטה המאוחרת **מטפלת** בתקדים המצוטט, לפי אחת מהקטגוריות:
+- followed   — אימצה והחילה את ההלכה.
+- explained  — הסבירה/הזכירה בלי לחלוק.
+- distinguished — אבחנה (קבעה שלא חל בנסיבות).
+- criticized — מתחה ביקורת בלי לבטל.
+- questioned — הטילה ספק.
+- overruled  — דחתה/ביטלה את ההלכה.
+- mentioned  — אזכור-אגב בלי טיפול.
+החזר JSON בלבד: {"treatment": "<קטגוריה>"}.
+"""
+
+async def classify_treatment(cited_citation: str, context: str) -> str:
+    """Return one treatment label for how `context` treats `cited_citation`."""
+    user = f"תקדים מצוטט: {cited_citation}\n\n--- ההקשר המצטט ---\n{context}\n--- סוף ---"
+    try:
+        result = await claude_session.query_json(
+            user, system=_TREATMENT_PROMPT,
+            model=config.HALACHA_EXTRACT_MODEL or None,
+            effort=config.HALACHA_EXTRACT_EFFORT or None,
+        )
+    except Exception as e:
+        logger.warning("classify_treatment failed: %s", e)
+        return "mentioned"
+    return _coerce_treatment(result if isinstance(result, dict) else {})

mcp-server/tests/test_corroboration.py

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+from __future__ import annotations
+import pytest
+from legal_mcp.services import corroboration as cor
+
+@pytest.mark.parametrize("raw,expected", [
+    ({"treatment": "followed"}, "followed"),
+    ({"treatment": "OVERRULED"}, "overruled"),     # case-insensitive
+    ({"treatment": "bananas"}, "mentioned"),         # unknown -> neutral default
+    ({}, "mentioned"),                               # missing -> neutral default
+])
+def test_coerce_treatment(raw, expected):
+    assert cor._coerce_treatment(raw) == expected
+
+def test_treatment_polarity():
+    assert cor.is_positive("followed") and cor.is_positive("explained")
+    assert cor.is_negative("distinguished") and cor.is_negative("overruled")
+    assert not cor.is_positive("mentioned") and not cor.is_negative("mentioned")