fix(telemetry): classify daemon query rejections as expected, not faults (#335)

* fix(telemetry): classify daemon query rejections as expected, not faults

Semantic-layer query rejections and warehouse-execution rejections from the
sl_query MCP tool were wrapped as generic Errors, so reportException filed them
as PostHog $exception faults indistinguishable from real ktx bugs.

The daemon already separates a caller rejection (planner ValueError -> exit 3 /
HTTP 400) from a crash. The Node runner now carries that distinction as a typed
KtxDaemonComputeError, and a shared throwClassifiedQueryError promotes daemon
input-rejections and warehouse rejections to KtxQueryError while daemon crashes
and native JS faults still reach Error Tracking. query_semantic_layer stops
report_exception-ing expected ValueErrors, and a missing 'file:' secret now
raises KtxExpectedError so absent .ktx/secrets/<conn>-password stops filing
faults.

* chore: sync uv.lock to ktx-daemon/ktx-sl 0.15.0

python/ktx-daemon/tests/test_semantic_layer.py

@@ -125,7 +125,7 @@ def test_query_semantic_layer_emits_plan_and_sql_debug_events(
     assert "public.orders" not in captured.err
 
 
-def test_query_semantic_layer_reports_exception(monkeypatch) -> None:
+def test_query_semantic_layer_reports_unexpected_fault(monkeypatch) -> None:
     from ktx_daemon import semantic_layer as semantic_layer_module
 
     reports: list[dict[str, object]] = []
@@ -133,12 +133,16 @@ def test_query_semantic_layer_reports_exception(monkeypatch) -> None:
     def fake_report(exception: BaseException, **kwargs: object) -> None:
         reports.append({"exception": exception, **kwargs})
 
-    monkeypatch.setattr(semantic_layer_module, "report_exception", fake_report)
+    def boom(*_args: object, **_kwargs: object) -> None:
+        raise RuntimeError("engine construction failed")
 
-    with pytest.raises(ValueError):
+    monkeypatch.setattr(semantic_layer_module, "report_exception", fake_report)
+    monkeypatch.setattr(semantic_layer_module.SemanticEngine, "from_sources", boom)
+
+    with pytest.raises(RuntimeError):
         query_semantic_layer(
             SemanticLayerQueryRequest(
-                sources=[ORDERS_SOURCE, ORDERS_SOURCE],
+                sources=[ORDERS_SOURCE],
                 dialect="postgres",
                 projectId="a" * 64,
                 query={"measures": ["orders.order_count"]},
@@ -152,6 +156,32 @@ def test_query_semantic_layer_reports_exception(monkeypatch) -> None:
     assert reports[0]["project_id"] == "a" * 64
 
 
+def test_query_semantic_layer_does_not_report_expected_query_rejection(
+    monkeypatch,
+) -> None:
+    from ktx_daemon import semantic_layer as semantic_layer_module
+
+    reports: list[dict[str, object]] = []
+    monkeypatch.setattr(
+        semantic_layer_module,
+        "report_exception",
+        lambda *_args, **kwargs: reports.append(kwargs),
+    )
+
+    # A planner ValueError is the engine refusing the agent's query — surfaced to
+    # the caller and re-raised, but never filed as a ktx fault.
+    with pytest.raises(ValueError, match="does not reference any source"):
+        query_semantic_layer(
+            SemanticLayerQueryRequest(
+                sources=[ORDERS_SOURCE],
+                dialect="postgres",
+                query={"measures": ["count(*)"]},
+            )
+        )
+
+    assert reports == []
+
+
 def test_semantic_layer_request_rejects_project_id_field_name() -> None:
     with pytest.raises(ValueError):
         SemanticLayerQueryRequest(