Planner Autonomy: вывести catalog-alignment в replay artifacts

scripts/domain_case_loop.py

@@ -1727,6 +1727,9 @@ def build_scenario_step_state(
         "selected_recipe": debug.get("selected_recipe"),
         "capability_id": debug.get("capability_id"),
         "capability_route_mode": debug.get("capability_route_mode"),
+        "mcp_discovery_catalog_chain_alignment_status": debug.get("mcp_discovery_catalog_chain_alignment_status"),
+        "mcp_discovery_catalog_chain_top_match": debug.get("mcp_discovery_catalog_chain_top_match"),
+        "mcp_discovery_catalog_chain_selected_matches_top": debug.get("mcp_discovery_catalog_chain_selected_matches_top"),
         "route_expectation_status": debug.get("route_expectation_status"),
         "result_mode": debug.get("result_mode"),
         "response_type": debug.get("response_type"),

scripts/domain_truth_harness.py

@@ -679,6 +679,9 @@ def build_truth_review_markdown(spec: dict[str, Any], scenario_state: dict[str,
                 f"intent: `{step_state.get('detected_intent') or 'n/a'}`",
                 f"recipe: `{step_state.get('selected_recipe') or 'n/a'}`",
                 f"capability: `{step_state.get('capability_id') or 'n/a'}`",
+                f"catalog_alignment_status: `{step_state.get('mcp_discovery_catalog_chain_alignment_status') or 'n/a'}`",
+                f"catalog_top_match: `{step_state.get('mcp_discovery_catalog_chain_top_match') or 'n/a'}`",
+                f"catalog_selected_matches_top: `{step_state.get('mcp_discovery_catalog_chain_selected_matches_top')}`",
                 f"limited_reason_category: `{step_state.get('limited_reason_category') or 'n/a'}`",
                 f"filters: `{dump_json(step_state.get('extracted_filters') or {})}`",
                 f"direct_answer: {step_state.get('actual_direct_answer') or 'n/a'}",

scripts/scenario_acceptance_policy.py

@@ -198,6 +198,9 @@ def build_scenario_acceptance_matrix(
                 "reply_type": step_state.get("reply_type"),
                 "detected_intent": step_state.get("detected_intent"),
                 "capability_id": step_state.get("capability_id"),
+                "mcp_discovery_catalog_chain_alignment_status": step_state.get("mcp_discovery_catalog_chain_alignment_status"),
+                "mcp_discovery_catalog_chain_top_match": step_state.get("mcp_discovery_catalog_chain_top_match"),
+                "mcp_discovery_catalog_chain_selected_matches_top": step_state.get("mcp_discovery_catalog_chain_selected_matches_top"),
                 "selected_object_step": _has_selected_object_signal(step),
                 "meta_context_step": _has_meta_context_signal(step),
                 "highest_unresolved_priority": highest_priority,
@@ -330,6 +333,9 @@ def build_scenario_acceptance_matrix_markdown(acceptance_matrix: dict[str, Any])
                 f"  review_status: `{row.get('review_status')}`",
                 f"  criticality: `{row.get('criticality')}`",
                 f"  semantic_tags: {', '.join(row.get('semantic_tags') or []) or 'none'}",
+                f"  catalog_alignment_status: `{row.get('mcp_discovery_catalog_chain_alignment_status') or 'n/a'}`",
+                f"  catalog_top_match: `{row.get('mcp_discovery_catalog_chain_top_match') or 'n/a'}`",
+                f"  catalog_selected_matches_top: `{row.get('mcp_discovery_catalog_chain_selected_matches_top')}`",
                 f"  highest_unresolved_priority: `{row.get('highest_unresolved_priority')}`",
                 f"  selected_object_step: `{row.get('selected_object_step')}`",
                 f"  meta_context_step: `{row.get('meta_context_step')}`",

scripts/test_domain_case_loop_step_state.py

@@ -0,0 +1,54 @@
+from __future__ import annotations
+
+import sys
+import unittest
+from pathlib import Path
+
+
+sys.path.insert(0, str(Path(__file__).resolve().parent))
+
+import domain_case_loop as dcl
+
+
+class DomainCaseLoopStepStateTests(unittest.TestCase):
+    def test_preserves_mcp_catalog_alignment_debug_fields(self) -> None:
+        step_state = dcl.build_scenario_step_state(
+            scenario_id="planner_alignment_demo",
+            domain="planner_autonomy",
+            step={
+                "step_id": "step_01",
+                "title": "Alignment visibility",
+                "depends_on": [],
+                "question_template": "show planner alignment",
+            },
+            step_index=1,
+            question_resolved="show planner alignment",
+            analysis_context={},
+            turn_artifact={
+                "assistant_message": {
+                    "reply_type": "factual",
+                    "text": "Confirmed answer",
+                    "message_id": "msg-1",
+                    "trace_id": "trace-1",
+                },
+                "technical_debug_payload": {
+                    "detected_mode": "address_query",
+                    "detected_intent": "counterparty_turnover",
+                    "selected_recipe": "counterparty_turnover_by_period",
+                    "capability_id": "confirmed_counterparty_turnover",
+                    "mcp_discovery_catalog_chain_alignment_status": "selected_matches_top",
+                    "mcp_discovery_catalog_chain_top_match": "value_flow",
+                    "mcp_discovery_catalog_chain_selected_matches_top": True,
+                },
+                "session_summary": {},
+            },
+            entries=[],
+        )
+
+        self.assertEqual(step_state["mcp_discovery_catalog_chain_alignment_status"], "selected_matches_top")
+        self.assertEqual(step_state["mcp_discovery_catalog_chain_top_match"], "value_flow")
+        self.assertTrue(step_state["mcp_discovery_catalog_chain_selected_matches_top"])
+
+
+if __name__ == "__main__":
+    unittest.main()

scripts/test_scenario_acceptance_policy.py

@@ -84,6 +84,9 @@ class ScenarioAcceptancePolicyTests(unittest.TestCase):
                     "reply_type": "factual",
                     "detected_intent": "inventory_on_hand_as_of_date",
                     "capability_id": "confirmed_inventory_on_hand_as_of_date",
+                    "mcp_discovery_catalog_chain_alignment_status": "selected_matches_top",
+                    "mcp_discovery_catalog_chain_top_match": "inventory_stock_snapshot",
+                    "mcp_discovery_catalog_chain_selected_matches_top": True,
                     "review_findings": [],
                 }
             },
@@ -104,6 +107,15 @@ class ScenarioAcceptancePolicyTests(unittest.TestCase):
         self.assertTrue(pack_state["acceptance_gate_passed"])
         self.assertTrue(pack_state["critical_path_green"])
         self.assertTrue(all(pack_state["invariants"].values()))
+        self.assertEqual(
+            acceptance_matrix["rows"][0]["mcp_discovery_catalog_chain_alignment_status"],
+            "selected_matches_top",
+        )
+        self.assertEqual(
+            acceptance_matrix["rows"][0]["mcp_discovery_catalog_chain_top_match"],
+            "inventory_stock_snapshot",
+        )
+        self.assertTrue(acceptance_matrix["rows"][0]["mcp_discovery_catalog_chain_selected_matches_top"])
 
     def test_flags_meta_context_integrity_when_meta_step_leaks_technical_answer_shape(self) -> None:
         spec = {