feat(x11): treatment-aware citation authority wired into research agents (#154)

The internal citation graph fed only RANKING (raw in-degree), and the per-citation
TREATMENT was never classified — so a precedent distinguished N times got the same
authority boost as one followed N times (INV-COR2 violation), and the signal never
reached the agents' reasoning. Wires the full path:

Phase 1 — scripts/classify_citation_treatments.py: classify each linked edge's
  treatment (followed/distinguished/…) from its match_context via
  corroboration.classify_treatment (Opus 4.8 @ xhigh, local), filling
  precedent_internal_citations.treatment. Idempotent.
Phase 2 — db.refresh_verified_layer: count only NON-negative treatments toward
  verified/cite_count (INV-COR2/COR4). Unclassified counts as neutral-positive so
  the signal degrades gracefully before classification runs.
Phase 3 — db.citation_authority(ids): per-precedent {total, positive, negative,
  unclassified, by_treatment}. Surfaced as `cited_by` in search_precedent_library
  hits and precedent_library_get, and `treatment` per incoming citation.
Phase 4 — legal-researcher/analyst/writer prompts: weigh & ARGUE authority
  ("הלכה שאומצה ב-N החלטות ועדת-ערר"), flag distinguished/overruled, never invent
  the count (INV-AH; writer is read-only of the analyst).

Auto-approval stays kill-switched off (chair gate preserved, INV-G10). No schema
change (treatment column already existed). Operational: run the classifier +
refresh_verified_layer over the 379 edges, then sync agents across companies.

Invariants: G2 (one classifier + one authority query, reused), INV-COR2/COR3/COR4
(negative never corroborates; point-specific; ≥N), INV-G10 (no auto-approval),
INV-AH (no invented numbers).

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

scripts/classify_citation_treatments.py

@@ -0,0 +1,99 @@
+"""Classify the TREATMENT of each internal citation edge (X11 Phase 2, #154).
+
+Each row in ``precedent_internal_citations`` records that a committee decision
+cited a precedent, with the surrounding ``match_context``. Until now the edge's
+``treatment`` column was empty, so the verified/authority layer counted every
+citation as if it were positive — a precedent *distinguished* N times got the
+same authority boost as one *followed* N times (an INV-COR2 violation).
+
+This script fills ``treatment`` per edge by classifying the context with
+``corroboration.classify_treatment`` (Opus 4.8 @ xhigh via the local
+claude_session bridge — LOCAL ONLY, the claude CLI is not in the container):
+
+    followed | explained        → positive (counts toward authority)
+    distinguished | criticized |
+    questioned | overruled       → negative (never counts; overruled = demote)
+
+Scope: only LINKED edges (``cited_case_law_id IS NOT NULL``) with an empty
+``treatment`` and a non-empty ``match_context``. Idempotent — a second run skips
+rows already classified. After applying, run ``scripts/build_verified_layer.py``
+(or ``db.refresh_verified_layer``) so the treatment-aware count takes effect.
+
+Run (dry-run, default — classifies and PRINTS, writes nothing):
+    HOME=/home/chaim mcp-server/.venv/bin/python scripts/classify_citation_treatments.py
+Apply:
+    HOME=/home/chaim mcp-server/.venv/bin/python scripts/classify_citation_treatments.py --apply
+Options:
+    --limit N            classify at most N edges (smoke test)
+    --case-law-id UUID   restrict to citations TO this one precedent
+"""
+
+from __future__ import annotations
+
+import argparse
+import asyncio
+import os
+import sys
+from uuid import UUID
+
+sys.path.insert(0, os.path.join(os.path.dirname(__file__), "..", "mcp-server", "src"))
+
+from legal_mcp.services import corroboration, db  # noqa: E402
+
+
+async def _pending(limit: int | None, case_law_id: str | None) -> list[dict]:
+    pool = await db.get_pool()
+    where = ["cited_case_law_id IS NOT NULL", "coalesce(treatment,'') = ''",
+             "coalesce(match_context,'') <> ''"]
+    params: list = []
+    if case_law_id:
+        params.append(UUID(case_law_id))
+        where.append(f"cited_case_law_id = ${len(params)}")
+    sql = (f"SELECT id, cited_case_number, match_context "
+           f"FROM precedent_internal_citations WHERE {' AND '.join(where)} "
+           f"ORDER BY created_at")
+    if limit:
+        sql += f" LIMIT {int(limit)}"
+    rows = await pool.fetch(sql, *params)
+    return [dict(r) for r in rows]
+
+
+async def main() -> None:
+    ap = argparse.ArgumentParser()
+    ap.add_argument("--apply", action="store_true", help="write changes (default: dry-run)")
+    ap.add_argument("--limit", type=int, default=None)
+    ap.add_argument("--case-law-id", type=str, default=None)
+    args = ap.parse_args()
+
+    rows = await _pending(args.limit, args.case_law_id)
+    print(f"קצוות לא-מסווגים לעיבוד: {len(rows)}\n")
+
+    pool = await db.get_pool()
+    counts: dict[str, int] = {}
+    errors = 0
+    for r in rows:
+        try:
+            t = await corroboration.classify_treatment(
+                r["cited_case_number"] or "", r["match_context"] or "")
+        except Exception as e:  # noqa: BLE001 — one bad row must not abort the batch
+            errors += 1
+            print(f"  ✗ [error] {r['cited_case_number']}: {type(e).__name__}: {e}")
+            continue
+        counts[t] = counts.get(t, 0) + 1
+        sign = "＋" if corroboration.is_positive(t) else ("－" if corroboration.is_negative(t) else "·")
+        print(f"  {sign} {t:<14} {r['cited_case_number']}")
+        if args.apply:
+            await pool.execute(
+                "UPDATE precedent_internal_citations SET treatment = $2 WHERE id = $1",
+                r["id"], t,
+            )
+
+    print(f"\nסיכום טיפול: {counts}  שגיאות={errors}"
+          + ("" if args.apply else "   (dry-run — לא נכתב)"))
+    if args.apply:
+        print("הרץ עכשיו: scripts/build_verified_layer.py (או db.refresh_verified_layer) "
+              "כדי שהספירה מודעת-הטיפול תיכנס לתוקף.")
+
+
+if __name__ == "__main__":
+    asyncio.run(main())