Improve runtime intelligence quick-scan labels

README.ko.md

@@ -233,15 +233,15 @@ Runtime Intelligence smoke:
 | Decision owner | `Lab remains the final deployment decision owner` | EdgeEnv, AIGuard, Orchestrator는 evidence provider이고 최종 판단은 Lab이 소유합니다. |
 | EdgeEnv regression gate | EdgeEnv comparability / regression evidence | runtime regression은 EdgeEnv comparability context가 있을 때만 해석합니다. |
 | Telemetry/replay quality | telemetry replay gap, `runtime_history_seed_run_config_traceability` | Runtime history seed와 `run_config` traceability가 보존됐는지 확인합니다. |
-| Operation context | `Orchestrator queue/deadline/fallback markers` | queue pressure, `max_total_queue_depth`, deadline miss, fallback count를 한눈에 묶습니다. |
+| Operation context | `Reviewer operation quick scan`, `Orchestrator queue/deadline/fallback markers` | queue pressure, `max_total_queue_depth`, deadline miss, fallback count, Jetson/device-local preservation identity를 한눈에 묶습니다. |
 | AIGuard warnings | deterministic AIGuard runtime operation evidence | AIGuard warning은 Lab policy를 덮어쓰지 않는 review evidence입니다. |
 
 Marker group:
 
 | 그룹 | 핵심 row / label | 이유 |
 |---|---|---|
 | Producer lineage | `edgeenv_orchestrator_producer_lineage`, `runtime_history_seed_run_config_traceability` | EdgeEnv/Orchestrator lineage가 AIGuard와 Lab까지 보존됐는지 확인합니다. |
-| Queue pressure | `Orchestrator queue/deadline/fallback markers`, `AIGuard max queue raw-context traceability` | `max_total_queue_depth`가 AIGuard deterministic raw context와 연결되는지 보여줍니다. |
+| Queue pressure | `Reviewer operation quick scan`, `Orchestrator queue/deadline/fallback markers`, `AIGuard max queue raw-context traceability` | `max_total_queue_depth`가 AIGuard deterministic raw context와 연결되는지 보여주고 device-local preservation label을 쉽게 찾게 합니다. |
 | Replay / preservation | `Runtime replay duration scope`, `Lab EdgeEnv preservation context`, `Jetson/device-local EdgeEnv preservation run`, `Jetson/device-local EdgeEnv preservation details` | replay duration과 `identity=jetson_device_local_preservation`, `path=device_local_starter` label을 빠르게 찾게 합니다. |
 | Task / operation risk | `Orchestrator task event rollup`, `AIGuard task event rollup evidence`, `AIGuard runtime operation anomalies` | scheduler delay, deadline miss, fallback decision, queue/drop reason을 review context로 보여줍니다. |
 | Remote starter boundary | `AIGuard remote dispatch event summary`, `Remote fallback starter evidence`, `production_remote_execution=false` | remote dispatch를 production execution이 아니라 starter evidence로 제한합니다. |

README.md

@@ -527,15 +527,15 @@ areas before opening detailed evidence rows.
 | Decision owner | `Lab remains the final deployment decision owner` | The report is Lab-owned; EdgeEnv, AIGuard, and Orchestrator provide evidence only. |
 | EdgeEnv regression gate | EdgeEnv comparability / regression evidence | Runtime regression is interpreted only after EdgeEnv comparability context is present. |
 | Telemetry/replay quality | telemetry replay gaps and `runtime_history_seed_run_config_traceability` | Shows whether Runtime history seed and `run_config` traceability are available. |
-| Operation context | `Orchestrator queue/deadline/fallback markers` | Groups queue pressure, `max_total_queue_depth`, deadline misses, and fallback count. |
+| Operation context | `Reviewer operation quick scan`, `Orchestrator queue/deadline/fallback markers` | Groups queue pressure, `max_total_queue_depth`, deadline misses, fallback count, and Jetson/device-local preservation identity. |
 | AIGuard warnings | deterministic AIGuard runtime operation evidence | Preserves warning evidence without overriding Lab deployment policy. |
 
 Reviewer marker map:
 
 | Marker group | Key rows / labels | Why it matters |
 |---|---|---|
 | Producer lineage | `edgeenv_orchestrator_producer_lineage`, `runtime_history_seed_run_config_traceability` | Confirms EdgeEnv/Orchestrator lineage reached AIGuard and Lab. |
-| Queue pressure | `Orchestrator queue/deadline/fallback markers`, `AIGuard max queue raw-context traceability` | Makes `max_total_queue_depth` traceable back to deterministic AIGuard raw context. |
+| Queue pressure | `Reviewer operation quick scan`, `Orchestrator queue/deadline/fallback markers`, `AIGuard max queue raw-context traceability` | Makes `max_total_queue_depth` traceable back to deterministic AIGuard raw context while keeping device-local preservation labels easy to spot. |
 | Replay and preservation | `Runtime replay duration scope`, `Lab EdgeEnv preservation context`, `Jetson/device-local EdgeEnv preservation run`, `Jetson/device-local EdgeEnv preservation details` | Shows replay duration, Lab preservation, and `identity=jetson_device_local_preservation` / `path=device_local_starter` labels. |
 | Task and operation risk | `Orchestrator task event rollup`, `AIGuard task event rollup evidence`, `AIGuard runtime operation anomalies` | Shows scheduler delay, deadline misses, fallback decisions, and queue/drop reasons as review context only. |
 | Remote starter boundary | `AIGuard remote dispatch event summary`, `Remote fallback starter evidence`, `production_remote_execution=false` | Keeps remote dispatch as starter evidence, not production remote execution. |

docs/portfolio/edgeenv_runtime_regression_lab_handoff.md

@@ -198,6 +198,7 @@ Expected Lab behavior:
 - Markdown/HTML reports include a `Runtime Intelligence Risk Summary` that summarizes EdgeEnv comparability/regression, telemetry replay gaps, Runtime history seed/run_config traceability, AIGuard deterministic evidence, and the Lab-owned deployment decision in one reviewer-facing table.
 - When EdgeEnv includes preserved Orchestrator feed context, the `Runtime Intelligence Risk Summary` surfaces queue, thermal, throttling, memory, fallback context, and compact `operation_risk_summary` markers as supplemental runtime evidence.
 - Lab now keeps queue pressure, `max_total_queue_depth` when available, deadline miss count, and fallback count together in an `Orchestrator queue/deadline/fallback markers` row when those compact counters are present. This is reviewer navigation context, not a production scheduler state or deployment decision override.
+- Lab also renders a `Reviewer operation quick scan` row that combines the same queue/deadline/fallback counters with Jetson/device-local preservation identity, so reviewers can identify the relevant EdgeEnv run before opening the full operation rows.
 - Lab also surfaces `AIGuard max queue raw-context traceability` when AIGuard
   preserves the same `orchestrator_candidate_operation_max_total_queue_depth`
   value, making the report row traceable back to deterministic AIGuard raw

inferedgelab/report/runtime_intelligence.py

@@ -405,6 +405,16 @@ def _append_telemetry_context_rows(
             )
         )
 
+    operation_quick_scan_labels = _operation_quick_scan_labels(telemetry_context)
+    if operation_quick_scan_labels:
+        rows.append(
+            (
+                "Reviewer operation quick scan",
+                "; ".join(operation_quick_scan_labels),
+                "One-line navigation labels combine queue/deadline/fallback and Jetson/device-local preservation context without changing Lab policy.",
+            )
+        )
+
     operation_risk_labels = _orchestrator_operation_risk_labels(telemetry_context)
     if operation_risk_labels:
         rows.append(
@@ -693,6 +703,49 @@ def _orchestrator_queue_deadline_fallback_labels(
     return labels
 
 
+def _operation_quick_scan_labels(context: dict[str, Any]) -> list[str]:
+    marker_by_run = _label_values_by_run(
+        _orchestrator_queue_deadline_fallback_labels(context)
+    )
+    risk_by_run = _label_values_by_run(_orchestrator_operation_risk_labels(context))
+    preservation_by_run = _label_values_by_run(
+        _edgeenv_preservation_run_labels(context)
+    )
+    task_by_run = _label_values_by_run(_orchestrator_task_event_rollup_labels(context))
+
+    labels: list[str] = []
+    for run_label in ("baseline", "candidate"):
+        parts: list[str] = []
+        marker_label = marker_by_run.get(run_label)
+        risk_label = risk_by_run.get(run_label)
+        if marker_label:
+            parts.append(marker_label)
+        elif risk_label:
+            parts.append(f"risk={risk_label}")
+
+        preservation_label = preservation_by_run.get(run_label)
+        if preservation_label:
+            parts.append(f"preservation={preservation_label}")
+
+        if task_by_run.get(run_label):
+            parts.append("task_rollup=present")
+
+        if parts:
+            labels.append(f"{run_label}: " + "; ".join(parts))
+    return labels
+
+
+def _label_values_by_run(labels: list[str]) -> dict[str, str]:
+    values_by_run: dict[str, str] = {}
+    for label in labels:
+        if ": " not in label:
+            continue
+        run_label, value = label.split(": ", 1)
+        if run_label and value and run_label not in values_by_run:
+            values_by_run[run_label] = value
+    return values_by_run
+
+
 def _runtime_replay_scope_labels(context: dict[str, Any]) -> list[str]:
     labels: list[str] = []
     for run_label in ("baseline", "candidate"):

tests/test_report_generators.py

@@ -867,6 +867,13 @@ def test_generate_compare_markdown_summarizes_orchestrator_context_risk():
         "queue_pressure_reason=queue_backlog_threshold_exceeded, "
         "max_total_queue_depth=7, deadline_missed_count=2, fallback_count=1 |"
     ) in text
+    assert (
+        "| Reviewer operation quick scan | candidate: "
+        "queue_pressure_reason=queue_backlog_threshold_exceeded, "
+        "max_total_queue_depth=7, deadline_missed_count=2, fallback_count=1; "
+        "preservation=identity=jetson_device_local_preservation, "
+        "run=candidate; task_rollup=present |"
+    ) in text
     assert (
         "| AIGuard max queue raw-context traceability | candidate: "
         "report=max_total_queue_depth=7, "
@@ -958,10 +965,12 @@ def test_generate_compare_html_summarizes_operation_risk_summary():
     assert "scope_label=source=entrypoint_requested_frames" in html
     assert "Orchestrator operation risk summary" in html
     assert "Orchestrator queue/deadline/fallback markers" in html
+    assert "Reviewer operation quick scan" in html
     assert (
         "queue_pressure_reason=queue_backlog_threshold_exceeded, "
         "max_total_queue_depth=7, deadline_missed_count=2, fallback_count=1"
     ) in html
+    assert "preservation=identity=jetson_device_local_preservation" in html
     assert "AIGuard max queue raw-context traceability" in html
     assert (
         "report=max_total_queue_depth=7, "

tests/test_runtime_intelligence_evidence_chain_smoke.py

@@ -539,6 +539,14 @@ def test_compare_cmd_runtime_intelligence_chain_writes_markdown_and_html(
         "identity=jetson_device_local_preservation, path=device_local_starter, "
         "run=edgeenv-smoke-candidate"
     ) in markdown
+    assert (
+        "| Reviewer operation quick scan | candidate: "
+        "queue_pressure_reason=queue_backlog_threshold_exceeded, "
+        "max_total_queue_depth=7, deadline_missed_count=2, fallback_count=1; "
+        "preservation=identity=jetson_device_local_preservation, "
+        "path=device_local_starter, run=edgeenv-smoke-candidate; "
+        "task_rollup=present |"
+    ) in markdown
     assert (
         "sources=device_local_cli_override, "
         "stages=vision_agent:device_local_starter, device_local_events=2, "
@@ -586,6 +594,7 @@ def test_compare_cmd_runtime_intelligence_chain_writes_markdown_and_html(
     assert "Jetson/device-local EdgeEnv preservation run" in html
     assert "Jetson/device-local EdgeEnv preservation details" in html
     assert "Lab EdgeEnv preservation context" in html
+    assert "Reviewer operation quick scan" in html
     assert "lab_report_preservation_context_present=True" in html
     assert "lab_preservation=present" in html
     assert "identity=jetson_device_local_preservation" in html