feat(gooddata-eval): add the agentic anomaly-detection evaluator (#1801)

* feat(gooddata-eval): add the agentic anomaly-detection evaluator

Scores the anomaly-detection skill end to end, with the granularity map aligned to what
the service actually accepts and whole-conversation latency and cost rather than the
goal turn's alone.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>

* fix(gooddata-eval): let --gate decide an anomaly item, not pass@K alone

`run_agentic_anomaly_detection` already computed `pass_power_k`; the evaluator
never read it, asking `if not summary.pass_at_k` for the verdict, so `--gate
power` on a flaky item reported a pass on the strength of one good run out of K.

Wired the same way as the other multi-run kinds: the evaluator takes `gate`, the
dispatch passes it, `gate_passed(...)` decides, the gate's note goes into the
assertion message -- which matters because the body describes the BEST run, and
under pass^K that can be one that passed -- and pass@K/pass^K/gate_passed reach
Langfuse alongside the run metadata stamp.

The default is unchanged: without --gate this is pass@K exactly as before, pinned
by a test beside the power case. The power test fails against the previous code.

Found by CodeRabbit on #1798. Forecasting is fixed there; what-if, which is
already on master, in #1831.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>

---------

Co-authored-by: Claude Opus 5 <noreply@anthropic.com>

Author: Tomkess

packages/gooddata-eval/src/gooddata_eval/cli/agentic_runner.py

@@ -12,6 +12,7 @@
 from gooddata_eval.core.agentic._langfuse import make_langfuse_client
 from gooddata_eval.core.agentic._trace_linker import BackgroundTraceLinker, SubmitTraceLink, run_trace_link_inline
 from gooddata_eval.core.agentic.alert_skill import evaluate_agentic_alert_skill
+from gooddata_eval.core.agentic.anomaly_detection import evaluate_agentic_anomaly_detection
 from gooddata_eval.core.agentic.conversation import ConversationFixture, evaluate_agentic_conversation
 from gooddata_eval.core.agentic.dashboard_skill import evaluate_agentic_dashboard_skill
 from gooddata_eval.core.agentic.general_question import evaluate_agentic_general_question
@@ -48,6 +49,7 @@ class _LfKw(TypedDict, total=False):
         "agentic_guardrail",
         "agentic_conversation",
         "agentic_kda_skill",
+        "agentic_anomaly_detection",
         "agentic_what_if",
     }
 )
@@ -278,6 +280,18 @@ def _dispatch_agentic(
             agent_id=agent_id,
             **lf_kw,
         )
+    elif kind == "agentic_anomaly_detection":
+        return evaluate_agentic_anomaly_detection(
+            host=host,
+            token=token,
+            workspace_id=workspace_id,
+            question=item.question,
+            expected_output=eo if isinstance(eo, dict) else {},
+            k=k,
+            gate=gate,
+            agent_id=agent_id,
+            **lf_kw,
+        )
     elif kind == "agentic_conversation":
         fixture_data = eo.get("fixture") or eo if isinstance(eo, dict) else {}
         return evaluate_agentic_conversation(