feat(precedents): metadata auto-fill, edit sheet, persuasive extraction

Three improvements to the precedent library based on usage feedback:

1. Auto-fill metadata at upload time. New service
   precedent_metadata_extractor reads the ruling's full_text and
   suggests case_name (short), summary, headnote, key_quote,
   subject_tags, appeal_subtype. The merge policy fills only empty
   fields, preserving everything the chair typed in the upload form.
   Wired into the ingest pipeline; also exposed as a re-run endpoint
   POST /api/precedent-library/{id}/extract-metadata for existing
   records.

2. Edit sheet in the UI. Pencil icon on each library row opens a
   pre-populated form covering every field. A Sparkles button on the
   sheet runs the metadata extractor on demand and refreshes the
   form. The case_number is read-only because halachot are FK'd to
   it; renaming requires delete + re-upload.

3. Halacha extractor branches on is_binding. Sources marked binding
   (Supreme/Administrative) keep the strict halacha prompt. Non-binding
   sources (other appeals committees, district courts on planning
   matters) get a different prompt that extracts applications,
   interpretive principles, and persuasive conclusions — labeled with
   new rule_types 'application' and 'persuasive'. The fallback also
   widens chunk selection: if the chunker labeled nothing as
   legal_analysis/ruling/conclusion, we now run on all chunks rather
   than returning zero halachot for a usable ruling.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

.taskmaster/tasks/tasks.json

@@ -1089,13 +1089,79 @@
         "priority": "medium",
         "subtasks": [],
         "updatedAt": "2026-05-03T08:36:24.711Z"
+      },
+      {
+        "id": "9",
+        "title": "Service: precedent_metadata_extractor.py",
+        "description": "LLM-based extractor that auto-fills empty metadata fields after upload: short case_name (e.g. 'אהרון ברק' from long citation), summary (2-3 sentences), headnote, key_quote, subject_tags array, appeal_subtype. Reuses claude_session.query_json. Returns dict; caller decides which empty fields to merge (never overrides user values).",
+        "details": "",
+        "testStrategy": "",
+        "status": "done",
+        "dependencies": [],
+        "priority": "high",
+        "subtasks": [],
+        "updatedAt": "2026-05-03T10:19:15.105Z"
+      },
+      {
+        "id": "10",
+        "title": "Halacha extractor: dual mode (binding vs persuasive)",
+        "description": "Update halacha_extractor.py prompt to branch on is_binding: binding=true → strict halacha extraction (current). binding=false → extract reasoning principles, applications of established halachot, persuasive conclusions. New rule_types: 'application' (applying known rule to facts), 'persuasive' (committee's reasoning citable as authority). Schema unchanged (rule_type already TEXT).",
+        "details": "",
+        "testStrategy": "",
+        "status": "done",
+        "dependencies": [],
+        "priority": "high",
+        "subtasks": [],
+        "updatedAt": "2026-05-03T10:19:15.117Z"
+      },
+      {
+        "id": "11",
+        "title": "Ingest pipeline: add metadata extraction stage",
+        "description": "In services/precedent_library.py:ingest_precedent, after halacha extraction, run metadata_extractor and PATCH the case_law row with auto-filled fields (only those left empty by user). Publish progress 'extracting_metadata'.",
+        "details": "",
+        "testStrategy": "",
+        "status": "done",
+        "dependencies": [
+          "9"
+        ],
+        "priority": "high",
+        "subtasks": [],
+        "updatedAt": "2026-05-03T10:19:15.128Z"
+      },
+      {
+        "id": "12",
+        "title": "UI: precedent edit sheet",
+        "description": "Add edit button to library-list-panel rows that opens a Sheet with all editable fields (case_name, citation, court, date, practice_area, appeal_subtype, subject_tags, summary, headnote, key_quote, source_type, precedent_level, is_binding). Pre-populated from current values. Submit calls PATCH /api/precedent-library/{id} via useUpdatePrecedent. After save, invalidate library list query.",
+        "details": "",
+        "testStrategy": "",
+        "status": "done",
+        "dependencies": [],
+        "priority": "high",
+        "subtasks": [],
+        "updatedAt": "2026-05-03T10:19:15.134Z"
+      },
+      {
+        "id": "13",
+        "title": "Test on 403-17: fix metadata + re-extract",
+        "description": "After deploy: PATCH 403-17 to set case_name='ערר 403/17', then trigger precedent_extract_halachot to test the dual-mode extraction on a non-binding committee decision.",
+        "details": "",
+        "testStrategy": "",
+        "status": "pending",
+        "dependencies": [
+          "9",
+          "10",
+          "11",
+          "12"
+        ],
+        "priority": "medium",
+        "subtasks": []
       }
     ],
     "metadata": {
       "version": "1.0.0",
-      "lastModified": "2026-05-03T08:36:24.711Z",
-      "taskCount": 8,
-      "completedCount": 8,
+      "lastModified": "2026-05-03T10:19:15.134Z",
+      "taskCount": 13,
+      "completedCount": 12,
       "tags": [
         "legal-ai"
       ]

mcp-server/src/legal_mcp/server.py

@@ -210,6 +210,12 @@ async def precedent_extract_halachot(case_law_id: str) -> str:
     return await plib.precedent_extract_halachot(case_law_id)
 
 
+@mcp.tool()
+async def precedent_extract_metadata(case_law_id: str) -> str:
+    """חילוץ מטא-דאטה (case_name קצר, summary, headnote, key_quote, subject_tags, appeal_subtype) מהטקסט. ממלא רק שדות ריקים."""
+    return await plib.precedent_extract_metadata(case_law_id)
+
+
 @mcp.tool()
 async def search_precedent_library(
     query: str,

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

@@ -41,7 +41,23 @@ CHUNK_RETRY_ATTEMPTS = 1
 EXTRACTABLE_SECTIONS = ("legal_analysis", "ruling", "conclusion")
 
 
-HALACHA_EXTRACTION_PROMPT = """אתה משפטן בכיר המתמחה בדיני תכנון ובניה (ועדות ערר, היטל השבחה, פיצויים לפי סעיף 197 לחוק התכנון והבניה). תפקידך: לחלץ הלכות מחייבות מתוך פסק דין/החלטה משפטית.
+# Two prompts — choose by source's is_binding flag.
+#
+# The binding prompt extracts strict halachot (rules a future panel MUST
+# follow). It rejects obiter dicta, factual findings, and citations of
+# other rulings that the present court only mentioned in passing.
+#
+# The persuasive prompt is for sources that don't establish binding law
+# (most appeals committee decisions, district courts on planning matters,
+# etc.). For those, the value is in **how the panel reasoned and applied**
+# established law to facts — not in new halachot. The user explicitly
+# wants to be able to cite "another committee reached the same conclusion"
+# even though it is not binding.
+#
+# The schema's rule_type field accepts six values:
+#   binding | interpretive | procedural | obiter | application | persuasive
+
+HALACHA_EXTRACTION_PROMPT_BINDING = """אתה משפטן בכיר המתמחה בדיני תכנון ובניה (ועדות ערר, היטל השבחה, פיצויים לפי סעיף 197 לחוק התכנון והבניה). תפקידך: לחלץ הלכות מחייבות מתוך פסק דין/החלטה משפטית של ערכאה עליונה (עליון / מנהלי).
 
 ## הגדרות מחייבות
 
@@ -94,8 +110,60 @@ HALACHA_EXTRACTION_PROMPT = """אתה משפטן בכיר המתמחה בדינ
 """
 
 
+HALACHA_EXTRACTION_PROMPT_PERSUASIVE = """אתה משפטן בכיר המתמחה בדיני תכנון ובניה. תפקידך: לחלץ עקרונות, יישומים ומסקנות מתוך החלטה של ועדת ערר אחרת או של בית משפט שאינו ערכאה עליונה לסוגיה.
+
+## חשוב — מה לחלץ ומה לא
+
+המקור הזה **אינו** מקור להלכות מחייבות חדשות (binding rules). הלכות מחייבות מגיעות מהעליון/מנהלי. עם זאת, יש כאן ערך משמעותי שצריך לחלץ — איך הפנל הזה ניתח ויישם את הדין הקיים. כשנכתוב החלטה עתידית, נצטט מהמקור הזה כ"גם ועדת הערר ב-X הגיעה למסקנה דומה" — לא כסמכות מחייבת, אלא כתמיכה משכנעת.
+
+**יש לחלץ:**
+- **יישום של הלכה ידועה** (rule_type=`application`) — הפנל החיל הלכה ידועה (של עליון/מנהלי) על עובדות הנידונות. תצטט את ניסוח הכלל **כפי שהוצג כאן** (לא בהכרח כפי שנקבע במקור) ואת התוצאה.
+- **עקרון פרשני שאומץ** (rule_type=`interpretive`) — איך הפנל פירש סעיף חוק / תכנית, באופן שניתן לאמץ.
+- **כלל פרוצדורלי** (rule_type=`procedural`) — קביעות בנושאי סמכות, מועדים, הליך.
+- **מסקנה מנומקת ומשכנעת** (rule_type=`persuasive`) — מסקנה שלמה של הפנל בסוגיה, עם ההיגיון התומך, ניתנת לציטוט כאסמכתא משכנעת.
+
+**אין לחלץ:**
+- ממצאים עובדתיים ספציפיים לתיק ("העורר לא הוכיח X").
+- ציטוטים מפסקי דין אחרים ללא ניתוח של הפנל.
+- אמרות אגב חסרות חשיבות.
+
+## תחומים אפשריים (practice_areas) — תחומי ועדת הערר בלבד
+- rishuy_uvniya — רישוי ובניה (תיקי 1xxx: היתרים, שימוש חורג, תכניות, קווי בניין, גובה, חניה)
+- betterment_levy — היטל השבחה (תיקי 8xxx: שומה, מערכות, תכניות המקנות בה, מועד קובע, סופיות ההחלטה)
+- compensation_197 — פיצויים לפי ס' 197 (תיקי 9xxx: פגיעה במקרקעין, ירידת ערך, ס' 200/פטור)
+
+## פלט נדרש
+החזר JSON array בלבד, ללא markdown, ללא הסברים:
+[
+  {
+    "rule_statement": "ניסוח הכלל / המסקנה / היישום בלשון משפטית מדויקת, 1-3 משפטים.",
+    "rule_type": "application",
+    "reasoning_summary": "תמצית ההיגיון של הפנל (1-2 משפטים).",
+    "supporting_quote": "ציטוט מילולי מדויק מהקלט שתומך בכלל. חייב להופיע מילה במילה.",
+    "page_reference": "פס' 12 / עמ' 8 — ככל שניתן לזהות.",
+    "practice_areas": ["betterment_levy"],
+    "subject_tags": ["מועד_קביעת_שומה", "תכנית_רחביה"],
+    "cites": ["עע\\"מ 3975/22"],
+    "confidence": 0.85
+  }
+]
+
+## כללי איכות
+1. **נאמנות מוחלטת לציטוט** — supporting_quote חייב להיות הדבקה מדויקת מהקלט. אם אין ציטוט מתאים — אל תוסיף את ההלכה.
+2. **מספר הלכות** — החלטה ארוכה של ועדת ערר יכולה להניב 2-8 פריטים (יישומים + מסקנות). אם אין מה לחלץ — החזר [].
+3. **rule_type מדויק** — application = יישום הלכה ידועה. interpretive = פרשנות. procedural = פרוצדורה. persuasive = מסקנה כללית בעלת ערך כאסמכתא.
+4. **לא לפצל יתר על המידה** — שני סעיפים זהים מבחינה רעיונית = פריט אחד.
+5. **שפה** — עברית משפטית מקצועית, גוף שלישי.
+6. **subject_tags** — 2-5 תגיות בעברית, snake_case.
+7. **confidence** — 0..1. דייק.
+"""
+
+
 _VALID_PRACTICE_AREAS = {"rishuy_uvniya", "betterment_levy", "compensation_197"}
-_VALID_RULE_TYPES = {"binding", "interpretive", "procedural", "obiter"}
+_VALID_RULE_TYPES = {
+    "binding", "interpretive", "procedural", "obiter",
+    "application", "persuasive",
+}
 
 
 def _normalize_for_comparison(text: str) -> str:
@@ -135,10 +203,13 @@ def _verify_quote(supporting_quote: str, full_text: str) -> bool:
     return False
 
 
-def _coerce_halacha(raw: dict) -> dict | None:
+def _coerce_halacha(raw: dict, is_binding: bool = True) -> dict | None:
     """Validate and normalize one LLM-returned halacha dict.
 
-    Returns ``None`` if the entry is missing required fields.
+    Returns ``None`` if the entry is missing required fields. ``is_binding``
+    only affects the default rule_type when the LLM returned an unknown
+    value — for binding sources we default to ``binding``, otherwise to
+    ``persuasive`` (never pretend an appeals committee created halacha).
     """
     if not isinstance(raw, dict):
         return None
@@ -147,9 +218,13 @@ def _coerce_halacha(raw: dict) -> dict | None:
     if not rule_statement or not supporting_quote:
         return None
 
-    rule_type = (raw.get("rule_type") or "binding").strip().lower()
+    default_rule_type = "binding" if is_binding else "persuasive"
+    rule_type = (raw.get("rule_type") or default_rule_type).strip().lower()
     if rule_type not in _VALID_RULE_TYPES:
-        rule_type = "binding"
+        rule_type = default_rule_type
+    # Guard: don't let a non-binding source produce 'binding' rule_type
+    if not is_binding and rule_type == "binding":
+        rule_type = "persuasive"
 
     practice_areas_raw = raw.get("practice_areas") or []
     if isinstance(practice_areas_raw, str):
@@ -191,11 +266,21 @@ async def _extract_chunk(
     chunk_index: int,
     chunk_total: int,
     context: str,
+    is_binding: bool,
 ) -> list[dict]:
-    """Run the halacha extractor on one chunk with retry."""
+    """Run the halacha extractor on one chunk with retry.
+
+    The prompt branches on ``is_binding`` so that non-binding sources
+    (other appeals committees, district courts) yield application /
+    persuasive entries rather than a forced 0-result strict halacha pass.
+    """
+    base_prompt = (
+        HALACHA_EXTRACTION_PROMPT_BINDING if is_binding
+        else HALACHA_EXTRACTION_PROMPT_PERSUASIVE
+    )
     chunk_label = f" (חלק {chunk_index + 1}/{chunk_total})" if chunk_total > 1 else ""
     prompt = (
-        f"{HALACHA_EXTRACTION_PROMPT}\n\n"
+        f"{base_prompt}\n\n"
         f"## הקלט\n"
         f"סוג קטע: {section_type}\n"
         f"{context}{chunk_label}\n\n"
@@ -241,9 +326,24 @@ async def extract(case_law_id: UUID | str) -> dict:
     if not record:
         return {"status": "not_found", "extracted": 0, "stored": 0}
 
+    is_binding = bool(record.get("is_binding"))
+
+    # Try the targeted sections first (legal_analysis / ruling / conclusion).
+    # If the chunker labeled everything as 'other' (common when a ruling
+    # uses non-standard headings or the section markers aren't bracketed
+    # cleanly), fall back to ALL chunks — better to over-include than to
+    # silently skip a ruling that has reasoning under an unexpected label.
     chunks = await db.list_precedent_chunks(
         case_law_id, section_types=EXTRACTABLE_SECTIONS,
     )
+    if not chunks:
+        chunks = await db.list_precedent_chunks(case_law_id)
+        if chunks:
+            logger.info(
+                "halacha_extractor: case_law=%s — no targeted sections, "
+                "falling back to all %d chunks",
+                case_law_id, len(chunks),
+            )
     if not chunks:
         await db.set_case_law_halacha_status(case_law_id, "completed")
         return {"status": "no_chunks", "extracted": 0, "stored": 0}
@@ -262,7 +362,7 @@ async def extract(case_law_id: UUID | str) -> dict:
         async with sem:
             return await _extract_chunk(
                 chunk_row["content"], chunk_row["section_type"],
-                idx, len(chunks), context,
+                idx, len(chunks), context, is_binding,
             )
 
     chunk_results = await asyncio.gather(
@@ -281,7 +381,7 @@ async def extract(case_law_id: UUID | str) -> dict:
 
     cleaned: list[dict] = []
     for raw in raw_halachot:
-        coerced = _coerce_halacha(raw)
+        coerced = _coerce_halacha(raw, is_binding=is_binding)
         if coerced is None:
             continue
         coerced["quote_verified"] = _verify_quote(

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

@@ -28,6 +28,7 @@ from legal_mcp.services import (
     embeddings,
     extractor,
     halacha_extractor,
+    precedent_metadata_extractor,
 )
 
 logger = logging.getLogger(__name__)
@@ -188,16 +189,27 @@ async def ingest_precedent(
         ]
         stored_chunks = await db.store_precedent_chunks(case_law_id, chunk_dicts)
 
-        await progress("extracting_halachot", 75, "מחלץ הלכות מחייבות")
         await db.set_case_law_extraction_status(case_law_id, "completed")
+
+        await progress("extracting_metadata", 65, "מחלץ מטא-דאטה (תקציר, תגיות)")
+        try:
+            metadata_result = await precedent_metadata_extractor.extract_and_apply(
+                case_law_id,
+            )
+        except Exception as e:
+            logger.warning("metadata extraction failed (non-fatal): %s", e)
+            metadata_result = {"status": "failed", "fields": []}
+
+        await progress("extracting_halachot", 80, "מחלץ הלכות / יישומים")
         halacha_result = await halacha_extractor.extract(case_law_id)
 
-        await progress(
-            "completed",
-            100,
+        msg = (
             f"הוכנס לספרייה: {stored_chunks} chunks, "
-            f"{halacha_result.get('stored', 0)} הלכות ממתינות לאישור",
+            f"{halacha_result.get('stored', 0)} פריטים ממתינים לאישור"
         )
+        if metadata_result.get("fields"):
+            msg += f"; מולאו אוטומטית: {', '.join(metadata_result['fields'])}"
+        await progress("completed", 100, msg)
 
         return {
             "status": "completed",
@@ -206,6 +218,7 @@ async def ingest_precedent(
             "halachot": halacha_result.get("stored", 0),
             "halachot_extracted_raw": halacha_result.get("extracted", 0),
             "halachot_verified": halacha_result.get("verified", 0),
+            "metadata_filled": metadata_result.get("fields", []),
             "pages": page_count,
         }
 
@@ -239,6 +252,36 @@ async def reextract_halachot(
     return result
 
 
+async def reextract_metadata(
+    case_law_id: UUID | str,
+    progress: ProgressCb | None = None,
+) -> dict:
+    """Re-run metadata extraction on an existing precedent.
+
+    Only fills empty fields (subject_tags, summary, headnote, key_quote,
+    appeal_subtype, and case_name when it equals the citation). User
+    values are preserved.
+    """
+    progress = progress or _noop_progress
+    if isinstance(case_law_id, str):
+        case_law_id = UUID(case_law_id)
+
+    record = await db.get_case_law(case_law_id)
+    if not record or record.get("source_kind") != "external_upload":
+        raise ValueError("precedent not found or not chair-uploaded")
+
+    await progress("extracting_metadata", 40, "מחלץ מטא-דאטה (תקציר, תגיות)")
+    result = await precedent_metadata_extractor.extract_and_apply(case_law_id)
+    fields = result.get("fields") or []
+    msg = (
+        f"מולאו {len(fields)} שדות: {', '.join(fields)}"
+        if fields
+        else "לא נמצא מה למלא (כל השדות מאוכלסים או לא ניתן לחלץ)"
+    )
+    await progress("completed", 100, msg)
+    return result
+
+
 async def delete_precedent(case_law_id: UUID | str) -> bool:
     """Delete a precedent and cascade chunks + halachot."""
     if isinstance(case_law_id, str):

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

@@ -0,0 +1,216 @@
+"""Auto-extract precedent metadata from a freshly-uploaded ruling.
+
+Runs after chunking. Reads the precedent's full_text and asks Claude to
+fill in the metadata fields that an upload form usually leaves empty:
+short case_name, summary, headnote, key_quote, subject_tags,
+appeal_subtype.
+
+Caller policy: only empty user-supplied fields are filled. Anything the
+chair already typed in the upload form is preserved. This is enforced
+in ``apply_to_record``.
+"""
+
+from __future__ import annotations
+
+import logging
+from uuid import UUID
+
+from legal_mcp.config import parse_llm_json
+from legal_mcp.services import claude_session, db
+
+logger = logging.getLogger(__name__)
+
+
+# The prompt is short — we only need the first 12K chars of the ruling
+# (header + opening of discussion is enough for naming + summary). For
+# subject tags we sample the discussion section too.
+_HEAD_CHARS = 12_000
+_TAIL_CHARS = 6_000
+
+
+METADATA_EXTRACTION_PROMPT = """אתה מסייע משפטי בכיר. קרא את פסק הדין/ההחלטה הבא וחלץ ממנו מטא-דאטה לקטלוג הקורפוס.
+
+המטרה: למלא שדות בטופס העלאה שהמשתמש הזין באופן חלקי. **אל תמציא** — אם המידע לא מופיע בטקסט, השאר ריק (מחרוזת ריקה / מערך ריק).
+
+## פלט נדרש
+החזר JSON אחד (object — לא array) בפורמט הבא, ללא markdown וללא הסברים:
+
+{
+  "case_name_short": "שם קצר ל-3-6 מילים (למשל 'אהרון ברק' או 'ב. קרן-נכסים'). אל תכלול מספר תיק. שם המבקש/העורר העיקרי. אם זו החלטה מאוחדת — שם הצד המוביל.",
+  "appeal_subtype": "תת-סוג ספציפי בתוך תחום המשפט (למשל 'תכנית רחביה', 'מימוש במכר', 'תמ\\"א 38', 'שימוש חורג', 'סופיות ההחלטה'). מילה אחת או צירוף קצר.",
+  "summary": "תקציר עניני 2-3 משפטים: מה הייתה השאלה, מה הוכרע. בלי שיפוט.",
+  "headnote": "headnote בסגנון נבו: 1-2 משפטים שמסכמים את העיקרון שנקבע/יושם בפסק. למשל 'תכנית רחביה — היטל השבחה במימוש במכר — אין לחייב כשהזכויות צפות'.",
+  "key_quote": "ציטוט מילולי בודד, 30-100 מילים, שמייצג את לב הפסק. חייב להופיע מילה במילה בטקסט. אם אין ציטוט מתאים — מחרוזת ריקה.",
+  "subject_tags": ["תגיות", "נושא", "בעברית"]
+}
+
+## כללי איכות
+1. **case_name_short** — שם בולט וקצר. בלי 'נ\\'' / 'נגד' / מספרי תיק.
+2. **appeal_subtype** — אופציונלי. אם הסוגיה רחבה ולא מסווגת — השאר ריק.
+3. **summary** — תיאור ניטרלי, גוף שלישי.
+4. **headnote** — לא מצטטים, מסכמים. סגנון נבו: ביטוי קצר אחד.
+5. **key_quote** — חייב להיות הדבקה מילולית מהקלט. אם אין ציטוט בולט — השאר ריק.
+6. **subject_tags** — 3-7 תגיות בעברית, snake_case (חניה, קווי_בניין, שיקול_דעת, פגם_פרוצדורלי, סמכות, מועדים, פגיעה_במקרקעין, ירידת_ערך, תכנית_רחביה, מימוש_במכר, וכד'). שייך לתחום של ועדת ערר תכנון ובניה.
+
+## הקלט
+{context}
+
+--- תחילת הטקסט ---
+{text_window}
+--- סוף הטקסט ---
+"""
+
+
+def _build_text_window(full_text: str) -> str:
+    """Return the head + tail of the ruling, with a marker if truncated.
+
+    Most rulings have the parties/subject in the head and the conclusion
+    in the tail; the middle is the discussion which is captured via the
+    halacha extractor independently. Sending head+tail keeps the prompt
+    cheap while preserving naming and conclusion context.
+    """
+    if len(full_text) <= _HEAD_CHARS + _TAIL_CHARS:
+        return full_text
+    return (
+        full_text[:_HEAD_CHARS]
+        + "\n\n[... חלק האמצע הושמט עקב אורך — ראה את החלק האחרון של הפסק להלן ...]\n\n"
+        + full_text[-_TAIL_CHARS:]
+    )
+
+
+async def extract_metadata(case_law_id: UUID | str) -> dict:
+    """Run metadata extraction. Returns a dict with the suggested values.
+
+    Does NOT write to the DB — caller decides what to merge.
+    """
+    if isinstance(case_law_id, str):
+        case_law_id = UUID(case_law_id)
+
+    record = await db.get_case_law(case_law_id)
+    if not record:
+        return {}
+    full_text = (record.get("full_text") or "").strip()
+    if not full_text:
+        return {}
+
+    citation = record.get("case_number") or ""
+    court = record.get("court") or ""
+    date_str = str(record.get("date") or "")
+    practice_area = record.get("practice_area") or ""
+
+    context = (
+        f"מראה מקום: {citation}\n"
+        f"ערכאה: {court}\n"
+        f"תאריך: {date_str}\n"
+        f"תחום: {practice_area}"
+    )
+    prompt = METADATA_EXTRACTION_PROMPT.format(
+        context=context, text_window=_build_text_window(full_text),
+    )
+
+    try:
+        result = await claude_session.query_json(prompt)
+    except Exception as e:
+        logger.warning("precedent_metadata_extractor: query failed: %s", e)
+        return {}
+
+    if not isinstance(result, dict):
+        logger.warning(
+            "precedent_metadata_extractor: expected dict, got %s",
+            type(result).__name__,
+        )
+        return {}
+
+    # Normalize keys / types
+    out: dict = {}
+    if isinstance(result.get("case_name_short"), str):
+        out["case_name_short"] = result["case_name_short"].strip()
+    if isinstance(result.get("appeal_subtype"), str):
+        out["appeal_subtype"] = result["appeal_subtype"].strip()
+    if isinstance(result.get("summary"), str):
+        out["summary"] = result["summary"].strip()
+    if isinstance(result.get("headnote"), str):
+        out["headnote"] = result["headnote"].strip()
+    if isinstance(result.get("key_quote"), str):
+        out["key_quote"] = result["key_quote"].strip()
+    tags = result.get("subject_tags") or []
+    if isinstance(tags, list):
+        out["subject_tags"] = [str(t).strip() for t in tags if str(t).strip()]
+    return out
+
+
+async def apply_to_record(
+    case_law_id: UUID | str,
+    suggested: dict,
+) -> dict:
+    """Merge suggested metadata into the case_law row, filling ONLY empty fields.
+
+    Empty rules:
+      - string field == "" → fill from suggested
+      - list field == [] → fill from suggested
+      - if suggested key is missing or empty, skip
+
+    case_name has special handling: if the current case_name equals the
+    case_number (a tell-tale sign of the upload form sending the long
+    citation into both fields), treat it as empty and overwrite.
+    """
+    if isinstance(case_law_id, str):
+        case_law_id = UUID(case_law_id)
+    record = await db.get_case_law(case_law_id)
+    if not record:
+        return {"updated": False, "fields": []}
+
+    fields_to_update: dict = {}
+
+    cur_case_name = (record.get("case_name") or "").strip()
+    cur_case_number = (record.get("case_number") or "").strip()
+    suggested_case_name = (suggested.get("case_name_short") or "").strip()
+    if suggested_case_name and (
+        not cur_case_name or cur_case_name == cur_case_number
+    ):
+        fields_to_update["case_name"] = suggested_case_name
+
+    if not (record.get("appeal_subtype") or "").strip():
+        s = (suggested.get("appeal_subtype") or "").strip()
+        if s:
+            fields_to_update["appeal_subtype"] = s
+
+    if not (record.get("summary") or "").strip():
+        s = (suggested.get("summary") or "").strip()
+        if s:
+            fields_to_update["summary"] = s
+
+    if not (record.get("headnote") or "").strip():
+        s = (suggested.get("headnote") or "").strip()
+        if s:
+            fields_to_update["headnote"] = s
+
+    if not (record.get("key_quote") or "").strip():
+        s = (suggested.get("key_quote") or "").strip()
+        if s:
+            fields_to_update["key_quote"] = s
+
+    cur_tags = record.get("subject_tags") or []
+    if not cur_tags:
+        sug_tags = suggested.get("subject_tags") or []
+        if sug_tags:
+            fields_to_update["subject_tags"] = sug_tags
+
+    if not fields_to_update:
+        return {"updated": False, "fields": []}
+
+    await db.update_case_law(case_law_id, **fields_to_update)
+    return {"updated": True, "fields": list(fields_to_update.keys())}
+
+
+async def extract_and_apply(case_law_id: UUID | str) -> dict:
+    """Convenience wrapper: extract → merge into row → return summary."""
+    suggested = await extract_metadata(case_law_id)
+    if not suggested:
+        return {"status": "no_metadata", "fields": []}
+    result = await apply_to_record(case_law_id, suggested)
+    return {
+        "status": "completed" if result["updated"] else "no_changes",
+        "fields": result["fields"],
+        "suggested": suggested,
+    }

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

@@ -139,6 +139,19 @@ async def precedent_extract_halachot(case_law_id: str) -> str:
     return _ok(result)
 
 
+async def precedent_extract_metadata(case_law_id: str) -> str:
+    """חילוץ מטא-דאטה (case_name קצר, summary, headnote, key_quote, subject_tags, appeal_subtype) מהטקסט. ממלא רק שדות ריקים — לא דורס מה שכבר הוזן."""
+    try:
+        cid = UUID(case_law_id)
+    except ValueError:
+        return _err("case_law_id לא תקין")
+    try:
+        result = await precedent_library.reextract_metadata(cid)
+    except Exception as e:
+        return _err(str(e))
+    return _ok(result)
+
+
 async def search_precedent_library(
     query: str,
     practice_area: str = "",

web-ui/src/components/precedents/library-list-panel.tsx

@@ -1,7 +1,7 @@
 "use client";
 
 import { useState } from "react";
-import { Trash2, Plus, RefreshCw } from "lucide-react";
+import { Trash2, Plus, RefreshCw, Pencil } from "lucide-react";
 import { toast } from "sonner";
 import {
   Table, TableBody, TableCell, TableHead, TableHeader, TableRow,
@@ -22,6 +22,7 @@ import {
 } from "@/lib/api/precedent-library";
 import { PRACTICE_AREAS, PRECEDENT_LEVELS, practiceAreaShort } from "./practice-area";
 import { PrecedentUploadSheet } from "./precedent-upload-sheet";
+import { PrecedentEditSheet } from "./precedent-edit-sheet";
 
 function formatDate(iso: string | null) {
   if (!iso) return "—";
@@ -55,7 +56,12 @@ function StatusPill({ p }: { p: Precedent }) {
   );
 }
 
-function PrecedentRow({ p }: { p: Precedent }) {
+function PrecedentRow({
+  p, onEdit,
+}: {
+  p: Precedent;
+  onEdit: (id: string) => void;
+}) {
   const del = useDeletePrecedent();
   const reExtract = useReExtractHalachot();
 
@@ -105,6 +111,14 @@ function PrecedentRow({ p }: { p: Precedent }) {
       </TableCell>
       <TableCell className="text-end">
         <div className="flex items-center gap-1 justify-end">
+          <Button
+            variant="ghost" size="sm" onClick={() => onEdit(p.id)}
+            aria-label={`ערוך את ${p.case_number}`}
+            title="ערוך פרטים"
+            className="text-ink-muted hover:text-navy"
+          >
+            <Pencil className="w-4 h-4" />
+          </Button>
           <Button
             variant="ghost" size="sm" onClick={onReExtract}
             disabled={reExtract.isPending}
@@ -133,6 +147,7 @@ export function LibraryListPanel() {
   const [precedentLevel, setPrecedentLevel] = useState("");
   const [search, setSearch] = useState("");
   const [uploadOpen, setUploadOpen] = useState(false);
+  const [editingId, setEditingId] = useState<string | null>(null);
 
   const { data, isPending, error } = usePrecedents({
     practiceArea: practiceArea || undefined,
@@ -222,7 +237,9 @@ export function LibraryListPanel() {
                   </TableCell>
                 </TableRow>
               ) : (
-                data.items.map((p) => <PrecedentRow key={p.id} p={p} />)
+                data.items.map((p) => (
+                  <PrecedentRow key={p.id} p={p} onEdit={setEditingId} />
+                ))
               )}
             </TableBody>
           </Table>
@@ -230,6 +247,10 @@ export function LibraryListPanel() {
       )}
 
       <PrecedentUploadSheet open={uploadOpen} onOpenChange={setUploadOpen} />
+      <PrecedentEditSheet
+        caseLawId={editingId}
+        onOpenChange={(open) => { if (!open) setEditingId(null); }}
+      />
     </div>
   );
 }

web-ui/src/components/precedents/precedent-edit-sheet.tsx

@@ -0,0 +1,309 @@
+"use client";
+
+import { useEffect, useState } from "react";
+import { Save, Sparkles, Loader2 } from "lucide-react";
+import { toast } from "sonner";
+import {
+  Sheet, SheetContent, SheetHeader, SheetTitle, SheetDescription,
+} from "@/components/ui/sheet";
+import { Button } from "@/components/ui/button";
+import { Input } from "@/components/ui/input";
+import { Label } from "@/components/ui/label";
+import { Textarea } from "@/components/ui/textarea";
+import { Skeleton } from "@/components/ui/skeleton";
+import {
+  Select, SelectContent, SelectItem, SelectTrigger, SelectValue,
+} from "@/components/ui/select";
+import {
+  usePrecedent,
+  useUpdatePrecedent,
+  useReExtractMetadata,
+  type PracticeArea,
+  type SourceType,
+} from "@/lib/api/precedent-library";
+import { useProgress } from "@/lib/api/documents";
+import {
+  PRACTICE_AREAS, PRECEDENT_LEVELS, SOURCE_TYPES,
+} from "./practice-area";
+
+type Props = {
+  caseLawId: string | null;
+  onOpenChange: (open: boolean) => void;
+};
+
+/* All editable fields. Pulled fresh from /api/precedent-library/{id}
+ * each time the sheet opens so the form reflects any auto-fill that
+ * happened in the background. */
+type FormState = {
+  citation: string;
+  case_name: string;
+  court: string;
+  decision_date: string;
+  practice_area: PracticeArea;
+  appeal_subtype: string;
+  source_type: SourceType;
+  precedent_level: string;
+  is_binding: boolean;
+  subject_tags: string;
+  summary: string;
+  headnote: string;
+  key_quote: string;
+};
+
+const EMPTY: FormState = {
+  citation: "", case_name: "", court: "", decision_date: "",
+  practice_area: "", appeal_subtype: "", source_type: "",
+  precedent_level: "", is_binding: true, subject_tags: "",
+  summary: "", headnote: "", key_quote: "",
+};
+
+export function PrecedentEditSheet({ caseLawId, onOpenChange }: Props) {
+  const open = caseLawId !== null;
+  const { data: record, isPending } = usePrecedent(caseLawId);
+  const update = useUpdatePrecedent();
+  const reextractMeta = useReExtractMetadata();
+
+  const [form, setForm] = useState<FormState>(EMPTY);
+  const [metadataTaskId, setMetadataTaskId] = useState<string | null>(null);
+  const metadataProgress = useProgress(metadataTaskId);
+
+  // Hydrate form when the record loads.
+  useEffect(() => {
+    if (!record) return;
+    // eslint-disable-next-line react-hooks/set-state-in-effect
+    setForm({
+      citation: record.case_number || "",
+      case_name: record.case_name || "",
+      court: record.court || "",
+      decision_date: record.date ? record.date.slice(0, 10) : "",
+      practice_area: (record.practice_area || "") as PracticeArea,
+      appeal_subtype: record.appeal_subtype || "",
+      source_type: (record.source_type || "") as SourceType,
+      precedent_level: record.precedent_level || "",
+      is_binding: record.is_binding ?? true,
+      subject_tags: (record.subject_tags || []).join(", "),
+      summary: record.summary || "",
+      headnote: record.headnote || "",
+      key_quote: (record as { key_quote?: string }).key_quote || "",
+    });
+  }, [record]);
+
+  // Auto-close metadata progress on completion + refresh form
+  useEffect(() => {
+    if (metadataProgress?.status === "completed") {
+      toast.success("חילוץ מטא-דאטה הסתיים — השדות עודכנו");
+      setMetadataTaskId(null);
+    } else if (metadataProgress?.status === "failed") {
+      toast.error(`חילוץ מטא-דאטה נכשל: ${metadataProgress.error || ""}`);
+      setMetadataTaskId(null);
+    }
+  }, [metadataProgress]);
+
+  const onSubmit = async (e: React.FormEvent) => {
+    e.preventDefault();
+    if (!caseLawId) return;
+    try {
+      const patch: Record<string, unknown> = {
+        case_name: form.case_name.trim(),
+        court: form.court.trim(),
+        practice_area: form.practice_area || undefined,
+        appeal_subtype: form.appeal_subtype.trim(),
+        source_type: form.source_type || undefined,
+        precedent_level: form.precedent_level || undefined,
+        is_binding: form.is_binding,
+        subject_tags: form.subject_tags
+          .split(",").map((t) => t.trim()).filter(Boolean),
+        summary: form.summary.trim(),
+        headnote: form.headnote.trim(),
+        key_quote: form.key_quote.trim(),
+      };
+      if (form.decision_date) patch.decision_date = form.decision_date;
+      // citation (case_number) is the unique key; we don't allow editing it
+      // here to avoid orphaning halachot. To rename, delete + re-upload.
+      await update.mutateAsync({ id: caseLawId, patch });
+      toast.success("נשמר");
+      onOpenChange(false);
+    } catch (err) {
+      toast.error(err instanceof Error ? err.message : "שגיאה");
+    }
+  };
+
+  const onTriggerMetadata = async () => {
+    if (!caseLawId) return;
+    try {
+      const res = await reextractMeta.mutateAsync(caseLawId);
+      setMetadataTaskId(res.task_id);
+      toast.message("מחלץ מטא-דאטה ברקע…");
+    } catch (err) {
+      toast.error(err instanceof Error ? err.message : "שגיאה");
+    }
+  };
+
+  const isMetaRunning = metadataTaskId !== null
+    && metadataProgress?.status !== "completed"
+    && metadataProgress?.status !== "failed";
+
+  return (
+    <Sheet open={open} onOpenChange={(o) => { if (!o) onOpenChange(false); }}>
+      <SheetContent side="left" className="w-full sm:max-w-2xl overflow-y-auto" dir="rtl">
+        <SheetHeader>
+          <SheetTitle className="text-navy">עריכת פרטי פסיקה</SheetTitle>
+          <SheetDescription className="text-ink-muted">
+            כל השדות ניתנים לעריכה חוץ ממראה המקום (מזהה ייחודי).
+            כפתור &quot;חלץ מטא-דאטה אוטומטית&quot; מנתח את הטקסט וממלא רק שדות ריקים.
+          </SheetDescription>
+        </SheetHeader>
+
+        {isPending || !record ? (
+          <div className="px-6 pb-6 mt-4 space-y-3">
+            {[...Array(6)].map((_, i) => <Skeleton key={i} className="h-10 w-full" />)}
+          </div>
+        ) : (
+          <form onSubmit={onSubmit} className="px-6 pb-6 space-y-4 mt-4">
+            <div className="rounded-lg border border-rule bg-rule-soft/40 p-3 flex items-start gap-3">
+              <div className="flex-1">
+                <div className="text-[0.78rem] text-ink-muted">מראה מקום (לא ניתן לעריכה)</div>
+                <div className="text-navy font-mono text-sm break-all" dir="ltr">
+                  {record.case_number}
+                </div>
+              </div>
+              <Button
+                type="button" size="sm" variant="outline"
+                onClick={onTriggerMetadata}
+                disabled={isMetaRunning || reextractMeta.isPending}
+                className="shrink-0"
+              >
+                {isMetaRunning ? (
+                  <Loader2 className="w-3.5 h-3.5 me-1 animate-spin" />
+                ) : (
+                  <Sparkles className="w-3.5 h-3.5 me-1" />
+                )}
+                חלץ מטא-דאטה אוטומטית
+              </Button>
+            </div>
+
+            {isMetaRunning && (metadataProgress as { step?: string } | null)?.step && (
+              <div className="text-[0.78rem] text-ink-muted">
+                {(metadataProgress as { step?: string }).step}
+              </div>
+            )}
+
+            <div className="grid grid-cols-2 gap-3">
+              <div className="space-y-1">
+                <Label htmlFor="case-name">שם קצר</Label>
+                <Input id="case-name" value={form.case_name}
+                  onChange={(e) => setForm({ ...form, case_name: e.target.value })}
+                  placeholder="ערר 403/17 / אהרון ברק" />
+              </div>
+              <div className="space-y-1">
+                <Label htmlFor="court">ערכאה</Label>
+                <Input id="court" value={form.court}
+                  onChange={(e) => setForm({ ...form, court: e.target.value })} />
+              </div>
+              <div className="space-y-1">
+                <Label htmlFor="date">תאריך</Label>
+                <Input id="date" type="date" value={form.decision_date}
+                  onChange={(e) => setForm({ ...form, decision_date: e.target.value })} />
+              </div>
+              <div className="space-y-1">
+                <Label htmlFor="appeal-subtype">תת-סוג</Label>
+                <Input id="appeal-subtype" value={form.appeal_subtype}
+                  onChange={(e) => setForm({ ...form, appeal_subtype: e.target.value })}
+                  placeholder="תכנית רחביה / סופיות ההחלטה" />
+              </div>
+            </div>
+
+            <div className="space-y-1">
+              <Label>תחום</Label>
+              <div className="flex gap-4 flex-wrap">
+                {PRACTICE_AREAS.map((a) => (
+                  <label key={a.value} className="flex items-center gap-2 cursor-pointer">
+                    <input type="radio" name="practice_area" value={a.value}
+                      checked={form.practice_area === a.value}
+                      onChange={() => setForm({ ...form, practice_area: a.value as PracticeArea })} />
+                    <span className="text-sm">{a.label}</span>
+                  </label>
+                ))}
+              </div>
+            </div>
+
+            <div className="grid grid-cols-2 gap-3">
+              <div className="space-y-1">
+                <Label htmlFor="source-type">סוג מקור</Label>
+                <Select value={form.source_type || "_none"}
+                  onValueChange={(v) => setForm({ ...form, source_type: v === "_none" ? "" : v as SourceType })}>
+                  <SelectTrigger><SelectValue /></SelectTrigger>
+                  <SelectContent>
+                    <SelectItem value="_none">—</SelectItem>
+                    {SOURCE_TYPES.map((s) => (
+                      <SelectItem key={s.value} value={s.value}>{s.label}</SelectItem>
+                    ))}
+                  </SelectContent>
+                </Select>
+              </div>
+              <div className="space-y-1">
+                <Label htmlFor="precedent-level">רמת תקדים</Label>
+                <Select value={form.precedent_level || "_none"}
+                  onValueChange={(v) => setForm({ ...form, precedent_level: v === "_none" ? "" : v })}>
+                  <SelectTrigger><SelectValue /></SelectTrigger>
+                  <SelectContent>
+                    <SelectItem value="_none">—</SelectItem>
+                    {PRECEDENT_LEVELS.map((l) => (
+                      <SelectItem key={l.value} value={l.value}>{l.label}</SelectItem>
+                    ))}
+                  </SelectContent>
+                </Select>
+              </div>
+            </div>
+
+            <div className="space-y-1">
+              <Label htmlFor="tags">תגיות נושא (מופרדות בפסיקים)</Label>
+              <Input id="tags" value={form.subject_tags}
+                onChange={(e) => setForm({ ...form, subject_tags: e.target.value })}
+                placeholder="חניה, קווי בניין, שיקול דעת" />
+            </div>
+
+            <div className="space-y-1">
+              <Label htmlFor="summary">תקציר (2-3 משפטים)</Label>
+              <Textarea id="summary" value={form.summary} rows={3} dir="rtl"
+                onChange={(e) => setForm({ ...form, summary: e.target.value })} />
+            </div>
+
+            <div className="space-y-1">
+              <Label htmlFor="headnote">Headnote (משפט-שניים)</Label>
+              <Textarea id="headnote" value={form.headnote} rows={2} dir="rtl"
+                onChange={(e) => setForm({ ...form, headnote: e.target.value })} />
+            </div>
+
+            <div className="space-y-1">
+              <Label htmlFor="key-quote">ציטוט מרכזי</Label>
+              <Textarea id="key-quote" value={form.key_quote} rows={3} dir="rtl"
+                onChange={(e) => setForm({ ...form, key_quote: e.target.value })} />
+            </div>
+
+            <label className="flex items-center gap-2 cursor-pointer">
+              <input type="checkbox" checked={form.is_binding}
+                onChange={(e) => setForm({ ...form, is_binding: e.target.checked })} />
+              <span className="text-sm">הלכה מחייבת (binding)</span>
+              <span className="text-[0.7rem] text-ink-muted">
+                — בדרך כלל רק עליון/מנהלי. ועדות ערר אחרות = לא מחייב.
+              </span>
+            </label>
+
+            <div className="flex gap-2 justify-end pt-2 border-t border-rule-soft">
+              <Button type="button" variant="ghost"
+                onClick={() => onOpenChange(false)} disabled={update.isPending}>
+                ביטול
+              </Button>
+              <Button type="submit" disabled={update.isPending}
+                className="bg-navy text-parchment hover:bg-navy-soft">
+                <Save className="w-4 h-4 me-1" />
+                שמור
+              </Button>
+            </div>
+          </form>
+        )}
+      </SheetContent>
+    </Sheet>
+  );
+}

web-ui/src/lib/api/precedent-library.ts

@@ -350,6 +350,21 @@ export function useReExtractHalachot() {
   });
 }
 
+export function useReExtractMetadata() {
+  const qc = useQueryClient();
+  return useMutation({
+    mutationFn: (id: string) =>
+      apiRequest<{ task_id: string }>(
+        `/api/precedent-library/${encodeURIComponent(id)}/extract-metadata`,
+        { method: "POST" },
+      ),
+    onSuccess: (_, id) => {
+      qc.invalidateQueries({ queryKey: libraryKeys.detail(id) });
+      qc.invalidateQueries({ queryKey: libraryKeys.all });
+    },
+  });
+}
+
 export function useHalachotPending(limit = 200) {
   return useQuery({
     queryKey: libraryKeys.halachotPending(),

web/app.py

@@ -3779,6 +3779,37 @@ async def precedent_library_reextract(case_law_id: str):
     return {"task_id": task_id}
 
 
+@app.post("/api/precedent-library/{case_law_id}/extract-metadata")
+async def precedent_library_extract_metadata(case_law_id: str):
+    """Re-run metadata extraction in background. Fills empty fields only."""
+    try:
+        cid = UUID(case_law_id)
+    except ValueError:
+        raise HTTPException(400, "case_law_id לא תקין")
+    record = await db.get_case_law(cid)
+    if not record:
+        raise HTTPException(404, "פסיקה לא נמצאה")
+
+    task_id = str(uuid4())
+    label = record.get("case_number") or case_law_id
+    await _progress.set(task_id, {
+        "status": "queued", "filename": label, "stage": "queued", "percent": 0,
+    })
+    publish = _make_progress_publisher(task_id, label)
+
+    async def _run():
+        try:
+            await plib_service.reextract_metadata(cid, progress=publish)
+        except Exception as e:
+            logger.exception("re-extract metadata failed")
+            await _progress.set(task_id, {
+                "status": "failed", "error": str(e), "filename": label,
+            })
+
+    asyncio.create_task(_run())
+    return {"task_id": task_id}
+
+
 @app.get("/api/halachot")
 async def halachot_list(
     case_law_id: str = "",