feat(analysis): דגל "לא-נותח" + ניתוח-מחדש מאחד + בדיקת-השפעה (#201)

WS2b של עיצוב-מחדש זרימת-העבודה. מאפשר ניתוח כתב-הערר לבד ואז איחוד
מסמך-עיקרי שנוסף מאוחר, בלי force-delete גורף, עם diff ליו"ר.

- SCHEMA_V49: documents.claims_extracted_at + claims_extraction_status
  (אירוע-חילוץ per-מסמך, לא נגזר מ-doc_type), + אינדקס חלקי
  idx_documents_claims_pending. idempotent (ADD COLUMN IF NOT EXISTS).
  V48 שמור ל-#357.
- claims_extractor חותם את המסמך אחרי שמירת/אי-מציאת טענות.
- db.primary_docs_not_analyzed (is_primary V47 + claims_extracted_at IS NULL)
  + mark_document_claims_extracted; _row_to_doc חושף claims_analyzed.
- reanalyze_claims (כלי-MCP): snapshot→חילוץ-מאחד רק למסמכים חדשים/לא-נותחו
  (store_claims מחליף per-source ⇒ טענות אחרות נשמרות)→aggregate force=True
  (מסלול קנוני, מוחק רק legal_arguments)→_impact_diff before↔after ליו"ר.
- workflow_status חושף primary_docs_not_analyzed + next-step.
- ספ: 02-data-model §2ג (דגל לא-נותח), 04-analysis-writing §1.3.
- 5 בדיקות-יחידה ל-_impact_diff/_snapshot (פונקציות טהורות).

Invariants:
- G1 (נרמול-במקור): claims_extracted_at נחתם בנקודת-החילוץ, claims_analyzed
  נגזר ממנו — לא תיקון-בקריאה.
- G2 (מסלול קנוני יחיד / merge-not-fork): reanalyze מרחיב את מסלול
  claims_extractor+argument_aggregator הקיים, לא forks; האיחוד דרך
  store_claims per-source; aggregate force=True מוחק רק נגזר (legal_arguments).
- INV-DM (מודל-נתונים): דגל-אירוע per-מסמך, אינדקס חלקי, מקור-אמת יחיד.
- G10 (שער-אנושי): בדיקת-ההשפעה מוצגת ליו"ר, לא מוחלת אוטומטית.
- INV-TOOL idempotency: SCHEMA_V49 idempotent; ניתוח-מחדש חוזר על מסמך
  כבר-נותח הוא refresh נקי (store_methods replace per-source).

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

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

@@ -1870,6 +1870,23 @@ CREATE INDEX IF NOT EXISTS idx_protocol_analysis_case ON protocol_analysis(case_
 CREATE INDEX IF NOT EXISTS idx_protocol_analysis_doc ON protocol_analysis(document_id);
 """
 
+# V49 (WS2 / task #201): per-document "claims analysed" tracking — the "not-analysed"
+# flag. `claims_extracted_at` is stamped by claims_extractor AFTER a document's claims
+# are stored; `claims_extraction_status` records the outcome
+# ('pending' | 'completed' | 'no_claims' | 'failed'). These describe the per-document
+# extraction *event* (the single source of truth for "has this doc been analysed") —
+# NOT derived from doc_type. They let us detect a PRIMARY document (is_primary, V47)
+# added after the analysis ran and not yet included → "primary doc not yet analysed".
+# The partial index pairs with idx_documents_primary so that query is cheap. Idempotent:
+# ADD COLUMN IF NOT EXISTS; re-running is a no-op. (V48 = protocol_analysis, #357.)
+SCHEMA_V49_SQL = """
+ALTER TABLE documents ADD COLUMN IF NOT EXISTS claims_extracted_at TIMESTAMPTZ;
+ALTER TABLE documents ADD COLUMN IF NOT EXISTS claims_extraction_status TEXT
+    NOT NULL DEFAULT 'pending';
+CREATE INDEX IF NOT EXISTS idx_documents_claims_pending
+    ON documents(case_id) WHERE is_primary AND claims_extracted_at IS NULL;
+"""
+
 
 # Stable, arbitrary key for the session-level advisory lock that serialises
 # schema DDL across processes. Every short-lived process (cron drains, services)
@@ -1941,6 +1958,7 @@ async def _apply_schema_ddl(conn: asyncpg.Connection) -> None:
         await conn.execute(SCHEMA_V46_SQL)
         await conn.execute(SCHEMA_V47_SQL)
         await conn.execute(SCHEMA_V48_SQL)
+        await conn.execute(SCHEMA_V49_SQL)
 
 
 async def init_schema() -> None:
@@ -2321,6 +2339,14 @@ def _row_to_doc(row: asyncpg.Record) -> dict:
         else is_primary_doc_type(d.get("doc_type"))
     d["is_primary"] = is_primary
     d["doc_category"] = "primary" if is_primary else "secondary"
+    # Per-document claims-analysis state (WS2 / #201). `claims_analyzed` is the
+    # human-facing "has this doc been included in the claims analysis" flag —
+    # True iff claims extraction has been stamped for it. Single source of truth:
+    # claims_extracted_at. Defaults keep pre-migration rows well-formed.
+    extracted_at = d.get("claims_extracted_at")
+    if "claims_extraction_status" not in d or d.get("claims_extraction_status") is None:
+        d["claims_extraction_status"] = "pending"
+    d["claims_analyzed"] = extracted_at is not None
     return d
 
 
@@ -2370,6 +2396,47 @@ async def get_claims(case_id: UUID, party_role: str | None = None) -> list[dict]
     return [dict(r) for r in rows]
 
 
+# ── Per-document claims-analysis tracking (WS2 / #201) ──────────────
+
+async def mark_document_claims_extracted(
+    doc_id: UUID, status: str = "completed",
+) -> None:
+    """Stamp a document as having had its claims extracted (WS2 / #201).
+
+    Sets ``claims_extracted_at = now()`` and records the outcome in
+    ``claims_extraction_status`` ('completed' | 'no_claims' | 'failed').
+    This is the single source of truth for the per-document "not-analysed"
+    flag — it is written at the point claims are stored, not derived later.
+    """
+    pool = await get_pool()
+    async with pool.acquire() as conn:
+        await conn.execute(
+            "UPDATE documents SET claims_extracted_at = now(), "
+            "claims_extraction_status = $2 WHERE id = $1",
+            doc_id, status,
+        )
+
+
+async def primary_docs_not_analyzed(case_id: UUID) -> list[dict]:
+    """Return PRIMARY documents in a case that have NOT yet been analysed.
+
+    "Primary" = ``is_primary`` (the V47 generated column, single source of
+    truth = PRIMARY_DOC_TYPES). "Not analysed" = ``claims_extracted_at IS NULL``.
+    Backed by the partial index ``idx_documents_claims_pending``. Surfaces the
+    "there is a primary document not yet included in the analysis" condition
+    (#201). Returns the same shape as ``list_documents`` rows.
+    """
+    pool = await get_pool()
+    async with pool.acquire() as conn:
+        rows = await conn.fetch(
+            "SELECT * FROM documents "
+            "WHERE case_id = $1 AND is_primary AND claims_extracted_at IS NULL "
+            "ORDER BY created_at",
+            case_id,
+        )
+    return [_row_to_doc(r) for r in rows]
+
+
 # ── Decisions ──────────────────────────────────────────────────────
 
 async def create_decision(