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>

docs/spec/02-data-model.md

@@ -95,6 +95,19 @@ WS2 (#200) מבחין בין **מסמך-עיקרי** (מסמך-מהות שהיו
 `document_list` / `case_get` / API-המסמכים. אינדקס חלקי `idx_documents_primary(case_id) WHERE
 is_primary` משרת את שאילתת "מסמכים-עיקריים שטרם-נותחו" (#201).
 
+**דגל "לא-נותח" — per-מסמך (#201, SCHEMA_V49).** שני שדות מתעדים את *אירוע* חילוץ-הטענות
+של המסמך (לא נגזרים מ-`doc_type`): `claims_extracted_at TIMESTAMPTZ` (נחתם ע"י
+`claims_extractor` **אחרי** ששמרנו את טענות המסמך) ו-`claims_extraction_status TEXT`
+(`pending`/`completed`/`no_claims`/`failed`). `_row_to_doc` חושף `claims_analyzed`
+(`claims_extracted_at IS NOT NULL`). מקור-האמת היחיד ל"האם המסמך נכלל בניתוח" הוא
+`claims_extracted_at` — לא משוחזר ממקום אחר. אינדקס חלקי `idx_documents_claims_pending(case_id)
+WHERE is_primary AND claims_extracted_at IS NULL` (יחד עם `is_primary` של V47) הופך את
+"מסמך-עיקרי שנוסף-אחרי-ניתוח ולא-נכלל" (`db.primary_docs_not_analyzed`) לשאילתה זולה.
+נחשף ב-`workflow_status` (`primary_docs_not_analyzed` + next-step). הניתוח-מחדש המאחד
+(`reanalyze_claims`, [04-analysis-writing §1.3](04-analysis-writing.md)) מחלץ-מחדש רק את
+המסמכים-העיקריים החדשים/לא-נותחו, **מאחד** עם הטענות הקיימות, ומריץ צבירה-מחדש (G2 — מסלול
+קנוני אחד, לא fork).
+
 ### 2ד. ישויות-נגזרות (אחסון-ניתוחים)
 
 מעבר לישויות-המקור, המערכת **שומרת ניתוחים נגזרים** — תוצרי-חילוץ של LLM/קוד. אלו כפופים לכללי

docs/spec/04-analysis-writing.md

@@ -97,6 +97,26 @@ knowledge נגזר; G2: מקור-האמת הוא הפרוטוקול + `legal_arg
   דפנה (`build_party_claims_summary_docx`). מימוש: `tools/drafting.py` ·
   `services/party_claims_summary.py` · `services/analysis_docx_exporter.py`.
 
+### 1.5 ניתוח-מחדש מאחד אחרי מסמך-עיקרי חדש (#201)
+
+תיק מנותח לרוב מכתב-הערר לבד, ומסמך-עיקרי (תשובה/התנגדות/פרוטוקול…) מגיע מאוחר יותר.
+כל מסמך נושא **דגל "לא-נותח"** (`claims_extracted_at`, [02-data-model §2ג](02-data-model.md)),
+ו-`workflow_status` מסמן "מסמך-עיקרי שטרם-נכלל בניתוח". `reanalyze_claims(case_number,
+reanalyze_all_primary=False)` סוגר את הפער **בלי force-delete גורף**:
+
+1. **snapshot לפני** — הטיעונים המאוגדים הנוכחיים (בסיס בדיקת-ההשפעה).
+2. **חילוץ-מאחד** — מחלץ רק את המסמכים-העיקריים החדשים/לא-נותחו (`db.primary_docs_not_analyzed`)
+   דרך **אותו** `claims_extractor.extract_and_store_claims`; `store_claims` מחליף רק את טענות
+   *אותו* מסמך (לפי `source_document`), כך שטענות ממסמכים שכבר-נותחו **נשמרות** (האיחוד).
+3. **צבירה-מחדש** — `aggregate_claims_to_arguments(force=True)` מחשב את הטיעונים מחדש מתוך
+   מערך-הטענות המאוחד השלם. זהו **מסלול-החישוב הקנוני** ([G2](00-constitution.md#inv-g2-מקור-אמת-יחיד--אין-מסלולים-מקבילים-מתפצלים)),
+   לא מסלול-עיבוד מקביל; הוא מוחק רק `legal_arguments` (נגזר), לעולם לא `claims`.
+4. **בדיקת-השפעה ליו"ר** — snapshot אחרי + `_impact_diff` מחזיר per-צד אילו טיעונים
+   נוספו/הוסרו ואיך השתנה תמהיל-העדיפויות ("מאזן-ההמלצה"), עם דגל `changed`. הפלט **מוצג**
+   ליו"ר ולא מוחל אוטומטית ([G10](00-constitution.md#inv-g10-המערכת-מסייעת--שערים-אנושיים-הם-invariant)).
+
+ראה `tools/legal_arguments.py` (`reanalyze_claims`, `_snapshot`, `_impact_diff`).
+
 ---
 
 ## 2. ארכיטקטורת 12 הבלוקים (סיכום)

mcp-server/src/legal_mcp/server.py

@@ -572,6 +572,18 @@ async def get_legal_arguments(
     return await la_tools.get_legal_arguments(case_number, party)
 
 
+@mcp.tool()
+async def reanalyze_claims(
+    case_number: str,
+    reanalyze_all_primary: bool = False,
+) -> str:
+    """ניתוח-מחדש מאחד אחרי הוספת מסמך-עיקרי: מחלץ ממסמכים-עיקריים חדשים/לא-נותחו בלבד,
+    מאחד עם הטענות הקיימות (לא מוחק הכול), מריץ צבירה-מחדש, ומחזיר בדיקת-השפעה
+    (diff טיעונים/המלצה לפני↔אחרי) ליו"ר. reanalyze_all_primary=True = כל המסמכים-העיקריים.
+    """
+    return await la_tools.reanalyze_claims(case_number, reanalyze_all_primary)
+
+
 # References
 @mcp.tool()
 async def extract_references(

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

@@ -360,6 +360,10 @@ async def extract_and_store_claims(
     claims = await extract_claims_with_ai(text, doc_type, party_hint)
 
     if not claims:
+        # Stamp the document as analysed even with zero claims, so it is not
+        # perpetually flagged "not-analysed" (#201 — the not-analysed flag is
+        # about whether extraction *ran*, not whether it found anything).
+        await db.mark_document_claims_extracted(document_id, status="no_claims")
         return {"status": "no_claims", "total": 0, "source": source_name}
 
     # Determine claim_type from document type and title
@@ -368,6 +372,10 @@ async def extract_and_store_claims(
         c["claim_type"] = claim_type
 
     stored = await db.store_claims(case_id, claims, source_document=source_name)
+    # Mark this document analysed (WS2 / #201). store_claims already replaced
+    # this document's prior claims by source_document — so re-running is a clean
+    # per-document refresh that does NOT touch other documents' claims (the merge).
+    await db.mark_document_claims_extracted(document_id, status="completed")
 
     # Summarize by role
     role_counts: dict[str, int] = {}

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(

mcp-server/src/legal_mcp/tools/legal_arguments.py

@@ -4,9 +4,18 @@ from __future__ import annotations
 
 from uuid import UUID
 
-from legal_mcp.services import argument_aggregator, db
+from legal_mcp.services import argument_aggregator, claims_extractor, db
 from legal_mcp.tools.envelope import empty, err, ok  # GAP-48: SSoT envelope
 
+# Party labels reused across this module (display + impact diff).
+_PARTY_HE = {
+    "appellant": "עוררים",
+    "respondent": "משיבים",
+    "committee": "ועדה מקומית",
+    "permit_applicant": "מבקשי היתר",
+    "unknown": "צד לא מזוהה",
+}
+
 
 async def aggregate_claims_to_arguments(
     case_number: str,
@@ -55,16 +64,9 @@ async def get_legal_arguments(
         )
 
     # Group by party for nicer display.
-    party_he = {
-        "appellant": "עוררים",
-        "respondent": "משיבים",
-        "committee": "ועדה מקומית",
-        "permit_applicant": "מבקשי היתר",
-        "unknown": "צד לא מזוהה",
-    }
     by_party: dict[str, list[dict]] = {}
     for a in args:
-        label = party_he.get(a["party"], a["party"])
+        label = _PARTY_HE.get(a["party"], a["party"])
         by_party.setdefault(label, []).append(a)
 
     return ok({
@@ -72,3 +74,147 @@ async def get_legal_arguments(
         "total": len(args),
         "by_party": by_party,
     })
+
+
+# ── Re-analysis with merge + impact diff (WS2 / #201) ───────────────
+
+def _snapshot(args: list[dict]) -> dict:
+    """Build a comparable snapshot of aggregated arguments for the impact diff.
+
+    Captures, per party: the set of argument titles and a priority histogram —
+    enough to show the chair what changed without dumping full bodies. The
+    priority mix is the deterministic "recommendation" signal: it summarises the
+    balance of threshold/substantive/procedural/relief arguments per side.
+    """
+    by_party: dict[str, dict] = {}
+    for a in args:
+        party = a.get("party", "unknown")
+        bucket = by_party.setdefault(party, {"titles": [], "priorities": {}})
+        bucket["titles"].append((a.get("argument_title") or "").strip())
+        pr = a.get("priority", "substantive")
+        bucket["priorities"][pr] = bucket["priorities"].get(pr, 0) + 1
+    return {"total": len(args), "by_party": by_party}
+
+
+def _impact_diff(before: dict, after: dict) -> dict:
+    """Diff two argument snapshots → a chair-facing before↔after summary.
+
+    Reports, per party, which argument titles were added/removed and how the
+    priority mix (the "recommendation" balance) shifted. ``changed`` is a quick
+    boolean the UI/chair can gate on. Nothing here is auto-applied — it is purely
+    surfaced for the human gate (G10).
+    """
+    parties = sorted(set(before["by_party"]) | set(after["by_party"]))
+    per_party: list[dict] = []
+    any_change = False
+    for party in parties:
+        b = before["by_party"].get(party, {"titles": [], "priorities": {}})
+        a = after["by_party"].get(party, {"titles": [], "priorities": {}})
+        b_titles, a_titles = set(b["titles"]), set(a["titles"])
+        added = sorted(a_titles - b_titles)
+        removed = sorted(b_titles - a_titles)
+        prio_before = dict(sorted(b["priorities"].items()))
+        prio_after = dict(sorted(a["priorities"].items()))
+        changed = bool(added or removed or prio_before != prio_after)
+        any_change = any_change or changed
+        per_party.append({
+            "party": party,
+            "party_he": _PARTY_HE.get(party, party),
+            "count_before": len(b["titles"]),
+            "count_after": len(a["titles"]),
+            "added_arguments": added,
+            "removed_arguments": removed,
+            "priority_before": prio_before,
+            "priority_after": prio_after,
+            "changed": changed,
+        })
+    return {
+        "changed": any_change,
+        "total_before": before["total"],
+        "total_after": after["total"],
+        "by_party": per_party,
+    }
+
+
+async def reanalyze_claims(
+    case_number: str,
+    reanalyze_all_primary: bool = False,
+) -> str:
+    """ניתוח-מחדש מאחד של טענות — מחלץ ממסמכים-עיקריים חדשים/לא-נותחו בלבד,
+    מאחד עם הטענות הקיימות (לא מוחק הכול), מריץ צבירה-מחדש, ומחזיר בדיקת-השפעה
+    (diff טיעונים/המלצה לפני↔אחרי) ליו"ר.
+
+    Args:
+        case_number: מספר תיק הערר.
+        reanalyze_all_primary: True = לחלץ מחדש מכל המסמכים-העיקריים (ולא רק
+            מאלה שטרם-נותחו). ברירת-מחדל False = רק מסמכים-עיקריים חדשים/לא-נותחו.
+
+    מנגנון האיחוד (לא force-delete): כל מסמך מחולץ דרך
+    ``claims_extractor.extract_and_store_claims``, ש-``store_claims`` שלו מחליף רק
+    את טענות *אותו* מסמך (לפי ``source_document``) — כך טענות ממסמכים שכבר-נותחו
+    נשמרות. הצבירה-מחדש (``aggregate_claims_to_arguments(force=True)``) מחשבת את
+    הטיעונים מחדש מתוך **מערך-הטענות המאוחד השלם** — מסלול-החישוב הקנוני, לא מסלול
+    מקביל (G2).
+    """
+    case = await db.get_case_by_number(case_number)
+    if not case:
+        return err(f"תיק {case_number} לא נמצא.")
+
+    case_id = UUID(case["id"])
+
+    # 1. BEFORE snapshot — current aggregated arguments (the impact baseline).
+    before_args = await argument_aggregator.get_legal_arguments(case_id)
+    before = _snapshot(before_args)
+
+    # 2. Select PRIMARY documents to (re)extract. Default: only those not yet
+    #    analysed (the not-analysed flag). reanalyze_all_primary widens to every
+    #    primary doc. Source of truth for "primary" = is_primary (V47).
+    if reanalyze_all_primary:
+        all_docs = await db.list_documents(case_id)
+        targets = [d for d in all_docs if d.get("is_primary")]
+    else:
+        targets = await db.primary_docs_not_analyzed(case_id)
+
+    if not targets:
+        return ok({
+            "case_number": case_number,
+            "status": "no_pending_documents",
+            "message": "אין מסמכים-עיקריים חדשים/לא-נותחו. לא בוצע ניתוח-מחדש.",
+            "documents_analyzed": [],
+            "impact": _impact_diff(before, before),
+        })
+
+    # 3. Extract+merge claims from the selected documents only. Each call replaces
+    #    only that document's claims (merge), never the whole case (no force-delete).
+    analyzed: list[dict] = []
+    for doc in targets:
+        text = await db.get_document_text(UUID(doc["id"]))
+        if not text:
+            await db.mark_document_claims_extracted(UUID(doc["id"]), status="no_claims")
+            analyzed.append({"document": doc["title"], "status": "empty_text", "total": 0})
+            continue
+        res = await claims_extractor.extract_and_store_claims(
+            case_id=case_id,
+            document_id=UUID(doc["id"]),
+            text=text,
+            doc_type=doc["doc_type"],
+        )
+        analyzed.append({"document": doc["title"], **res})
+
+    # 4. Re-aggregate from the now-complete merged claim set. force=True is the
+    #    canonical recompute (deletes only legal_arguments, NOT claims) — same
+    #    path aggregate_claims_to_arguments always uses, not a fork.
+    agg = await argument_aggregator.aggregate_claims_to_arguments(case_id, force=True)
+
+    # 5. AFTER snapshot + impact diff for the chair.
+    after_args = await argument_aggregator.get_legal_arguments(case_id)
+    after = _snapshot(after_args)
+    impact = _impact_diff(before, after)
+
+    return ok({
+        "case_number": case_number,
+        "status": "completed",
+        "documents_analyzed": analyzed,
+        "aggregation": agg,
+        "impact": impact,
+    })

mcp-server/src/legal_mcp/tools/workflow.py

@@ -46,8 +46,19 @@ async def workflow_status(case_number: str) -> str:
             "extraction": doc["extraction_status"],
             "chunks": chunk_map.get(doc["id"], 0),
             "pages": doc.get("page_count"),
+            # WS2 / #201: primary/secondary + whether claims were analysed.
+            "is_primary": doc.get("is_primary", False),
+            "claims_analyzed": doc.get("claims_analyzed", False),
         })
 
+    # WS2 / #201: PRIMARY documents added after the analysis ran and not yet
+    # included → the "not-analysed" condition that should prompt a merging
+    # re-analysis (reanalyze_claims). Derived from is_primary + claims_extracted_at.
+    pending_primary = await db.primary_docs_not_analyzed(case_id)
+    primary_not_analyzed = [
+        {"title": d["title"], "type": d["doc_type"]} for d in pending_primary
+    ]
+
     # Check draft status
     from pathlib import Path
     from legal_mcp import config
@@ -64,15 +75,19 @@ async def workflow_status(case_number: str) -> str:
         "documents": doc_status,
         "total_documents": len(docs),
         "total_chunks": sum(chunk_map.values()),
+        "primary_docs_not_analyzed": primary_not_analyzed,
         "has_draft": has_draft,
         "draft_size_bytes": draft_size,
-        "next_steps": _suggest_next_steps(case, docs, has_draft),
+        "next_steps": _suggest_next_steps(case, docs, has_draft, primary_not_analyzed),
     }
 
     return ok(status)
 
 
-def _suggest_next_steps(case: dict, docs: list, has_draft: bool) -> list[str]:
+def _suggest_next_steps(
+    case: dict, docs: list, has_draft: bool,
+    primary_not_analyzed: list | None = None,
+) -> list[str]:
     """Suggest next steps based on case state."""
     steps = []
     doc_types = {d["doc_type"] for d in docs}
@@ -85,6 +100,13 @@ def _suggest_next_steps(case: dict, docs: list, has_draft: bool) -> list[str]:
         if "response" not in doc_types:
             steps.append("העלה תשובת ועדה/משיבים")
 
+    # WS2 / #201: a primary document was added but not yet analysed.
+    if primary_not_analyzed:
+        titles = ", ".join(d["title"] for d in primary_not_analyzed)
+        steps.append(
+            f"מסמך-עיקרי לא-נותח ({titles}) — הרץ ניתוח-מחדש מאחד (reanalyze_claims)"
+        )
+
     pending = [d for d in docs if d["extraction_status"] == "pending"]
     if pending:
         steps.append(f"עיבוד {len(pending)} מסמכים ממתינים")

mcp-server/tests/test_reanalyze_impact_diff.py

@@ -0,0 +1,76 @@
+"""Unit tests for the re-analysis impact diff — WS2 / task #201.
+
+`_snapshot` + `_impact_diff` are pure functions (no DB) that produce the
+before↔after summary surfaced to the chair after a merging re-analysis. They
+must report per-party argument titles added/removed and the shift in the
+priority ("recommendation balance") mix, and set ``changed`` correctly.
+"""
+
+from __future__ import annotations
+
+from legal_mcp.tools.legal_arguments import _impact_diff, _snapshot
+
+
+def _arg(party, title, priority="substantive"):
+    return {"party": party, "argument_title": title, "priority": priority}
+
+
+def test_no_change_is_flagged_false():
+    args = [_arg("appellant", "זכות עמידה"), _arg("committee", "שיהוי")]
+    snap = _snapshot(args)
+    diff = _impact_diff(snap, snap)
+    assert diff["changed"] is False
+    assert diff["total_before"] == diff["total_after"] == 2
+    # Every party entry reports changed=False.
+    assert all(p["changed"] is False for p in diff["by_party"])
+
+
+def test_added_argument_detected():
+    before = _snapshot([_arg("appellant", "זכות עמידה")])
+    after = _snapshot([_arg("appellant", "זכות עמידה"), _arg("appellant", "תחולת תמא 38")])
+    diff = _impact_diff(before, after)
+    assert diff["changed"] is True
+    assert diff["total_before"] == 1
+    assert diff["total_after"] == 2
+    appellant = next(p for p in diff["by_party"] if p["party"] == "appellant")
+    assert appellant["added_arguments"] == ["תחולת תמא 38"]
+    assert appellant["removed_arguments"] == []
+    assert appellant["party_he"] == "עוררים"
+
+
+def test_removed_argument_detected():
+    before = _snapshot([_arg("committee", "שיהוי"), _arg("committee", "סמכות")])
+    after = _snapshot([_arg("committee", "שיהוי")])
+    diff = _impact_diff(before, after)
+    committee = next(p for p in diff["by_party"] if p["party"] == "committee")
+    assert committee["removed_arguments"] == ["סמכות"]
+    assert committee["count_before"] == 2
+    assert committee["count_after"] == 1
+    assert diff["changed"] is True
+
+
+def test_priority_mix_shift_is_a_change():
+    # Same title, but priority moved threshold -> substantive: the recommendation
+    # balance shifted, so the chair must see a change even with identical titles.
+    before = _snapshot([_arg("appellant", "סמכות", priority="threshold")])
+    after = _snapshot([_arg("appellant", "סמכות", priority="substantive")])
+    diff = _impact_diff(before, after)
+    appellant = next(p for p in diff["by_party"] if p["party"] == "appellant")
+    assert appellant["added_arguments"] == []
+    assert appellant["removed_arguments"] == []
+    assert appellant["priority_before"] == {"threshold": 1}
+    assert appellant["priority_after"] == {"substantive": 1}
+    assert appellant["changed"] is True
+    assert diff["changed"] is True
+
+
+def test_new_party_appears():
+    before = _snapshot([_arg("appellant", "זכות עמידה")])
+    after = _snapshot([_arg("appellant", "זכות עמידה"), _arg("respondent", "מענה")])
+    diff = _impact_diff(before, after)
+    parties = {p["party"] for p in diff["by_party"]}
+    assert parties == {"appellant", "respondent"}
+    respondent = next(p for p in diff["by_party"] if p["party"] == "respondent")
+    assert respondent["count_before"] == 0
+    assert respondent["count_after"] == 1
+    assert respondent["added_arguments"] == ["מענה"]