fix(awooop): derive work progress from automation receipts

apps/api/src/services/ai_agent_autonomous_runtime_control.py

@@ -882,9 +882,21 @@ def _build_learning_loop_readback(
         and controlled_retry_package.get("schema_version")
         == "ai_agent_controlled_retry_package_v1"
     )
+    learned_context_ready = bool(
+        verifier_total > 0
+        and km_total > 0
+        and learning_writeback_total > 0
+        and trust_total > 0
+        and learning_source_family_count > 0
+        and repair_feedback_ready
+    )
     next_decision_ready = bool(
         agent_decision_wiring.get("status") == "completed"
-        and loop_ledger.get("closed") is True
+        and (
+            loop_ledger.get("closed") is True
+            or latest_flow_closure.get("closed") is True
+            or learned_context_ready
+        )
     )
     stages = [
         _learning_loop_stage(
@@ -1546,8 +1558,8 @@ def _build_work_item_progress(
     decision_wiring_missing = _int_value(decision_rollups.get("required_stage_missing_count"))
     p1a_completed = inactive_source_count == 0
     p1b_completed = (
-        p1a_completed
-        and agent_decision_wiring.get("schema_version") == "ai_agent_decision_wiring_readback_v1"
+        agent_decision_wiring.get("schema_version") == "ai_agent_decision_wiring_readback_v1"
+        and agent_decision_wiring.get("status") == "completed"
         and decision_wiring_missing == 0
     )
     learning_rollups = learning_loop.get("rollups")
@@ -1555,8 +1567,8 @@ def _build_work_item_progress(
         learning_rollups = {}
     learning_loop_missing = _int_value(learning_rollups.get("required_stage_missing_count"))
     p1c_completed = (
-        p1b_completed
-        and learning_loop.get("schema_version") == "ai_agent_learning_loop_readback_v1"
+        learning_loop.get("schema_version") == "ai_agent_learning_loop_readback_v1"
+        and learning_loop.get("status") == "completed"
         and learning_loop_missing == 0
     )
     alert_noise_rollups = alert_noise_reduction.get("rollups")
@@ -1564,9 +1576,9 @@ def _build_work_item_progress(
         alert_noise_rollups = {}
     alert_noise_missing = _int_value(alert_noise_rollups.get("required_stage_missing_count"))
     p1d_completed = (
-        p1c_completed
-        and alert_noise_reduction.get("schema_version")
+        alert_noise_reduction.get("schema_version")
         == "ai_agent_alert_noise_reduction_readback_v1"
+        and alert_noise_reduction.get("status") == "completed"
         and alert_noise_missing == 0
     )
     ui_rollups = ui_productization.get("rollups")
@@ -1574,9 +1586,9 @@ def _build_work_item_progress(
         ui_rollups = {}
     ui_surface_missing = _int_value(ui_rollups.get("required_surface_missing_count"))
     p2a_completed = (
-        p1d_completed
-        and ui_productization.get("schema_version")
+        ui_productization.get("schema_version")
         == "ai_agent_ui_productization_readback_v1"
+        and ui_productization.get("status") == "completed"
         and ui_surface_missing == 0
     )
     multi_product_rollups = multi_product_taxonomy.get("rollups")
@@ -1588,9 +1600,9 @@ def _build_work_item_progress(
         else []
     ) + _int_value(multi_product_rollups.get("missing_required_dimension_count"))
     p2b_completed = (
-        p2a_completed
-        and multi_product_taxonomy.get("schema_version")
+        multi_product_taxonomy.get("schema_version")
         == "ai_agent_multi_product_taxonomy_contract_v1"
+        and multi_product_taxonomy.get("status") == "completed"
         and multi_product_missing == 0
     )
     deployed_readback_complete = (

apps/api/tests/test_ai_agent_autonomous_runtime_control.py

@@ -582,6 +582,194 @@ def test_runtime_receipt_readback_summarizes_live_executor_closure_rows():
     assert progress["rollups"]["pending_count"] == 0
 
 
+def test_runtime_receipt_work_items_use_learning_receipts_without_latest_telegram_gate():
+    apply_op_id = "2f8ef5c8-fd4e-4950-99e9-dc9e61150cab"
+    incident_id = "INC-20260629-LEARNING"
+
+    readback = build_runtime_receipt_readback_from_rows(
+        project_id="awoooi",
+        db_read_status="ok",
+        operation_count_rows=[
+            {
+                "operation_type": "ansible_candidate_matched",
+                "status": "dry_run",
+                "total": 1,
+                "recent": 1,
+            },
+            {
+                "operation_type": "ansible_check_mode_executed",
+                "status": "success",
+                "total": 1,
+                "recent": 1,
+            },
+            {
+                "operation_type": "ansible_apply_executed",
+                "status": "success",
+                "total": 1,
+                "recent": 1,
+            },
+            {
+                "operation_type": "ansible_learning_writeback_recorded",
+                "status": "success",
+                "total": 1,
+                "recent": 1,
+            },
+        ],
+        operation_latest_rows=[
+            {
+                "op_id": "candidate-op-learning",
+                "parent_op_id": None,
+                "operation_type": "ansible_candidate_matched",
+                "status": "dry_run",
+                "actor": "decision_manager",
+                "incident_id": incident_id,
+                "catalog_id": "ansible:188-ai-web",
+                "playbook_path": "infra/ansible/playbooks/188-ai-web.yml",
+                "execution_mode": "check_mode",
+            },
+            {
+                "op_id": "check-mode-op-learning",
+                "parent_op_id": "candidate-op-learning",
+                "operation_type": "ansible_check_mode_executed",
+                "status": "success",
+                "actor": "ansible_check_mode_worker",
+                "incident_id": incident_id,
+                "catalog_id": "ansible:188-ai-web",
+                "playbook_path": "infra/ansible/playbooks/188-ai-web.yml",
+                "execution_mode": "check_mode",
+                "returncode": "0",
+            },
+            {
+                "op_id": apply_op_id,
+                "parent_op_id": "check-mode-op-learning",
+                "operation_type": "ansible_apply_executed",
+                "status": "success",
+                "actor": "ansible_controlled_apply_worker",
+                "incident_id": incident_id,
+                "catalog_id": "ansible:188-ai-web",
+                "playbook_path": "infra/ansible/playbooks/188-ai-web.yml",
+                "execution_mode": "controlled_apply",
+                "source_candidate_op_id": "candidate-op-learning",
+                "check_mode_op_id": "check-mode-op-learning",
+                "returncode": "0",
+            },
+            {
+                "op_id": "learning-op",
+                "parent_op_id": apply_op_id,
+                "operation_type": "ansible_learning_writeback_recorded",
+                "status": "success",
+                "actor": "ansible_controlled_apply_worker",
+                "incident_id": incident_id,
+                "catalog_id": "ansible:188-ai-web",
+                "playbook_path": "infra/ansible/playbooks/188-ai-web.yml",
+                "execution_mode": "learning_writeback",
+                "returncode": "0",
+            },
+        ],
+        auto_repair_count_rows=[
+            {"result_status": "success", "total": 1, "recent": 1},
+        ],
+        auto_repair_latest_rows=[
+            {
+                "id": "auto-repair-learning",
+                "incident_id": incident_id,
+                "catalog_id": "ansible:188-ai-web",
+                "playbook_name": "infra/ansible/playbooks/188-ai-web.yml",
+                "result_status": "success",
+                "executed_steps_text": f'["apply:{apply_op_id}"]',
+                "triggered_by": "ansible_controlled_apply",
+                "risk_level": "low",
+                "execution_time_ms": 2400,
+            },
+        ],
+        verifier_count_rows=[
+            {"verification_result": "success", "total": 1, "recent": 1},
+        ],
+        verifier_latest_rows=[
+            {
+                "id": "evidence-learning",
+                "incident_id": incident_id,
+                "verification_result": "success",
+                "apply_op_id": apply_op_id,
+                "catalog_id": "ansible:188-ai-web",
+                "playbook_path": "infra/ansible/playbooks/188-ai-web.yml",
+                "returncode": "0",
+            },
+        ],
+        km_count_rows=[
+            {"status": "review", "total": 1, "recent": 1},
+        ],
+        km_latest_rows=[
+            {
+                "id": "km-learning",
+                "title": "AI 自動修復沉澱：INC-20260629-LEARNING",
+                "related_incident_id": incident_id,
+                "related_playbook_id": "ansible:188-ai-web",
+                "path_type": "ansible_apply_receipt:2f8ef5c8",
+                "status": "review",
+                "created_by": "ai_agent_ansible_worker",
+            },
+        ],
+        telegram_count_rows=[
+            {"send_status": "sent", "total": 1, "recent": 1},
+        ],
+        telegram_latest_rows=[],
+        mcp_gateway_count_rows=[
+            {"status": "success", "total": 1, "recent": 1},
+        ],
+        legacy_mcp_count_rows=[
+            {"status": "success", "total": 1, "recent": 1},
+        ],
+        service_log_count_rows=[
+            {"status": "sanitized_recent_logs", "total": 1, "recent": 1},
+        ],
+        executor_log_count_rows=[
+            {"status": "success", "total": 1, "recent": 1},
+        ],
+        timeline_count_rows=[
+            {"status": "success", "total": 1, "recent": 1},
+        ],
+        playbook_trust_count_rows=[
+            {"status": "learning_active", "total": 1, "recent": 1},
+        ],
+        alert_operation_count_rows=[
+            {"event_type": "ALERT_RECEIVED", "total": 5, "recent": 2},
+            {"event_type": "AUTO_REPAIR_TRIGGERED", "total": 2, "recent": 1},
+            {"event_type": "EXECUTION_STARTED", "total": 1, "recent": 1},
+            {"event_type": "EXECUTION_COMPLETED", "total": 1, "recent": 1},
+        ],
+        alertmanager_event_count_rows=[
+            {"stage": "received", "total": 5, "recent": 2},
+            {"stage": "converged", "total": 3, "recent": 1},
+            {"stage": "llm_inflight_suppressed", "total": 1, "recent": 1},
+        ],
+        grouped_alert_event_count_rows=[
+            {"status": "grouped_child_alert", "total": 4, "recent": 1},
+        ],
+    )
+
+    assert readback["latest_flow_closure"]["closed"] is False
+    assert readback["latest_flow_closure"]["missing"] == ["telegram_receipt"]
+    assert readback["autonomous_execution_loop_ledger"]["closed"] is False
+    assert readback["learning_loop"]["status"] == "completed"
+    assert readback["learning_loop"]["missing_required_stage_ids"] == []
+    assert readback["learning_loop"]["rollups"]["next_decision_ready_count"] == 1
+    assert readback["alert_noise_reduction"]["status"] == "completed"
+    assert readback["alert_noise_reduction"]["missing_required_stage_ids"] == []
+    progress = readback["work_item_progress"]
+    statuses = {
+        item["work_item_id"]: item["status"]
+        for item in progress["ordered_items"]
+    }
+    assert statuses["P1-C-learning-loop"] == "completed"
+    assert statuses["P1-D-alert-noise-reduction"] == "completed"
+    assert statuses["P2-A-ui-ux-productization"] == "completed"
+    assert statuses["P2-B-multi-product-expansion"] == "completed"
+    assert {item["status"] for item in progress["source_family_items"]} == {"completed"}
+    assert progress["rollups"]["completed_count"] == 21
+    assert progress["rollups"]["pending_count"] == 0
+
+
 def test_runtime_receipt_readback_classifies_closed_failed_apply_as_ai_repair():
     apply_op_id = "94925d5e-6fdc-49c3-90e8-f0a0d57a6a58"
     incident_id = "INC-20260628-A40A9A"