fix(appraiser-facts): route extraction through analyst wakeup (was silent 0)

The "חלץ עובדות שמאיות" UI button hit POST /api/cases/{n}/extract-appraiser-facts
which called appraiser_facts_extractor inline — that shells out to the local
`claude` CLI, which is absent in the Coolify container, so every doc errored,
the per-doc try/except swallowed it, and the response was "completed, 0 facts".

Refactored the endpoint to wake the legal-analyst of the correct company via
Paperclip (same pattern as wake_curator_for_final), and surface
extraction_failed instead of "completed" when every doc errored.

web/paperclip_client.py

@@ -53,6 +53,15 @@ CURATOR_AGENTS = {
     COMPANIES["betterment"]: "d6f7c55d-570a-46b8-8d72-1286d07da0d8",  # CMPA curator
 }
 
+# Legal Analyst (מנתח משפטי) agent per company — woken from the chair UI
+# when the chair finishes tagging appraisals and asks for fact extraction.
+# The analyst runs `mcp__legal-ai__extract_appraiser_facts` locally (where
+# the Claude CLI is present), since the FastAPI container cannot.
+ANALYST_AGENTS = {
+    COMPANIES["licensing"]: "c26e9439-a88a-49dc-9e67-2262c95db65c",   # CMP analyst
+    COMPANIES["betterment"]: "f70fd353-6cde-46b3-8d6c-cfad12100b1b",  # CMPA analyst
+}
+
 # Fallback mapping — used only when DB lookup returns no results.
 # בל"מ (extension_request_*) variants route to the same company as their
 # parent domain — בל"מ ברישוי → CMP, בל"מ בהיטל השבחה → CMPA, וכו'.
@@ -1016,3 +1025,107 @@ async def wake_curator_for_final(
         "curator_id": curator_id,
         "main_issue_id": main_issue_id,
     }
+
+
+async def wake_analyst_for_appraiser_facts(
+    case_number: str,
+    company_id: str,
+) -> dict:
+    """Wake the legal-analyst to extract appraiser facts for this case.
+
+    Triggered by the chair clicking "חלץ עובדות שמאיות עכשיו" in the UI.
+    The FastAPI container cannot run `extract_appraiser_facts` directly —
+    the extractor calls `claude_session.query_json()`, which only works
+    where the local `claude` CLI is present (the MCP server / agent runner
+    on the host). So instead of running it inline, we create a child issue
+    under the case's main Paperclip issue, assign it to the analyst of the
+    correct company, and trigger a wakeup with `mutation: extract_appraiser_facts`.
+    The analyst's HEARTBEAT picks up the issue, runs the MCP tool locally,
+    and reports back via a comment.
+
+    Returns a dict shaped for the FastAPI endpoint to serialize as-is:
+        {"status": "queued", "sub_issue_id", "analyst_id", "main_issue_id"}
+      or {"status": "skipped", "reason": "..."} for non-fatal early outs.
+    """
+    if not PAPERCLIP_BOARD_API_KEY:
+        logger.warning(
+            "PAPERCLIP_BOARD_API_KEY not set — cannot queue analyst wakeup for %s",
+            case_number,
+        )
+        return {"status": "skipped", "reason": "no_api_key"}
+
+    analyst_id = ANALYST_AGENTS.get(company_id)
+    if not analyst_id:
+        logger.info("No analyst configured for company %s — skipping", company_id)
+        return {"status": "skipped", "reason": "no_analyst", "company_id": company_id}
+
+    issues = await get_case_issues(case_number)
+    if not issues:
+        logger.warning(
+            "No Paperclip issues found for case %s — cannot queue analyst", case_number,
+        )
+        return {"status": "skipped", "reason": "no_issue"}
+
+    main_issue = next((i for i in issues if i.get("status") == "in_progress"), None) or issues[0]
+    main_issue_id = main_issue["id"]
+
+    description = (
+        f"חיים תייג שומות בתיק {case_number} וביקש חילוץ עובדות שמאיות.\n\n"
+        f"הרץ `mcp__legal-ai__extract_appraiser_facts(case_number=\"{case_number}\")` "
+        f"וכתוב comment בעברית עם תוצאת החילוץ — מספר תכניות, מספר היתרים, "
+        f"וסתירות (אם יש) בין שמאים. אם המסמכים חסרי תיוג `appraiser_side`, "
+        f"דווח ב-comment על השומות החסרות וסגור את ה-issue כ-blocked."
+    )
+    child_resp = await pc_request(
+        "POST",
+        f"/api/issues/{main_issue_id}/children",
+        json={
+            "title": f"[ערר {case_number}] חילוץ עובדות שמאיות",
+            "description": description,
+            "status": "in_progress",
+            "priority": "normal",
+            "assigneeAgentId": analyst_id,
+        },
+        raise_on_error=True,
+    )
+    sub_issue = child_resp.json()
+    sub_issue_id = sub_issue["id"]
+
+    # Tag plugin_state so the case page surfaces this sub-issue too
+    try:
+        conn = await asyncpg.connect(PAPERCLIP_DB_URL)
+        try:
+            await _link_case_to_issue(conn, sub_issue_id, case_number)
+        finally:
+            await conn.close()
+    except Exception as e:
+        logger.warning("plugin_state link failed for sub_issue=%s: %s", sub_issue_id, e)
+
+    wake_resp = await pc_request(
+        "POST",
+        f"/api/agents/{analyst_id}/wakeup",
+        json={
+            "source": "on_demand",
+            "triggerDetail": "manual",
+            "reason": f"extract_appraiser_facts_{case_number}",
+            # Use "assignment" — the same mutation `wake_curator_for_final`
+            # sends. The HEARTBEAT recognises it; the task-specific intent
+            # is conveyed by the child-issue's description, not the payload.
+            "payload": {
+                "issueId": sub_issue_id,
+                "mutation": "assignment",
+                "caseNumber": case_number,
+            },
+        },
+        raise_on_error=True,
+    )
+    logger.info(
+        "Analyst wakeup for case %s: sub_issue=%s analyst=%s wake=%s",
+        case_number, sub_issue_id, analyst_id, wake_resp.status_code,
+    )
+    return {
+        "status": "queued",
+        "sub_issue_id": sub_issue_id,
+        "analyst_id": analyst_id,
+        "main_issue_id": main_issue_id,
+    }