Document Lab sample handoff path

README.ko.md

@@ -244,6 +244,7 @@ README에서는 빠른 검토 경로만 유지하고, 세부 marker contract는
 | 먼저 열어볼 operation risk가 있는가? | `Reviewer operation quick scan`, `raw_marker=reviewer_focus_operation_quick_scan`, `Orchestrator queue/deadline/fallback markers` | detailed row를 열기 전에 queue pressure, `max_total_queue_depth`, deadline miss, fallback count, Jetson/device-local identity를 먼저 봅니다. |
 | 어떤 preserved run/path를 보는가? | `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. |
 | optional AIGuard full-evidence source fixture는 무엇인가? | `runtime_intelligence_source_traceability_summary.md`, `source_traceability_alignment`, `aiguard_optional_present_source_artifact` | EdgeEnv mirror와 AIGuard optional-present fixture가 같은 read-only source artifact와 재생성 명령을 가리키는지 확인합니다. |
+| upstream sample handoff는 어디서 확인하는가? | Orchestrator `agent_scheduler_delay_sample.json`, `remote_fallback_recovery_sample.json` -> AIGuard `scheduler_delay_pattern`, `remote_execution_recovered_by_fallback` -> Lab report marker | curated sample을 benchmark output이나 Lab policy input으로 만들지 않고 cross-repo 검토 경로만 제공합니다. |
 | 어떤 warning이 review context로만 남는가? | `AIGuard max queue raw-context traceability`, `AIGuard operation timeline evidence`, `AIGuard runtime operation anomalies`, `AIGuard remote dispatch event summary`, `Remote fallback starter evidence`, `production_remote_execution=false` | AIGuard/Orchestrator가 policy owner가 되지 않도록 deterministic warning과 remote starter evidence를 보존합니다. |
 
 세부 marker contract는 [docs/portfolio/edgeenv_runtime_regression_lab_handoff.md](docs/portfolio/edgeenv_runtime_regression_lab_handoff.md)에 정리되어 있습니다.

README.md

@@ -538,6 +538,7 @@ in the handoff document linked below.
 | Is there an operation risk worth opening first? | `Reviewer operation quick scan`, `raw_marker=reviewer_focus_operation_quick_scan`, `Orchestrator queue/deadline/fallback markers` | Surfaces queue pressure, `max_total_queue_depth`, deadline misses, fallback count, and Jetson/device-local identity before the detailed rows. |
 | Which preserved run/path is being reviewed? | `Runtime replay duration scope`, `Lab EdgeEnv preservation context`, `Jetson/device-local EdgeEnv preservation run`, `Jetson/device-local EdgeEnv preservation details` | Keeps replay duration, `identity=jetson_device_local_preservation`, and `path=device_local_starter` easy to find. |
 | Which optional AIGuard source fixture backs the full-evidence path? | `runtime_intelligence_source_traceability_summary.md`, `source_traceability_alignment`, `aiguard_optional_present_source_artifact` | Lets reviewers confirm the EdgeEnv mirror and AIGuard optional-present fixture point to the same read-only source artifact and reproduction command. |
+| Which upstream samples explain the handoff? | Orchestrator `agent_scheduler_delay_sample.json`, `remote_fallback_recovery_sample.json` -> AIGuard `scheduler_delay_pattern`, `remote_execution_recovered_by_fallback` -> Lab report markers | Gives reviewers a cross-repo navigation path without making curated samples benchmark outputs or Lab policy inputs. |
 | Which warnings remain review context only? | `AIGuard max queue raw-context traceability`, `AIGuard operation timeline evidence`, `AIGuard runtime operation anomalies`, `AIGuard remote dispatch event summary`, `Remote fallback starter evidence`, `production_remote_execution=false` | Preserves deterministic warning and remote starter evidence without making AIGuard/Orchestrator the policy owner. |
 
 These rows do not turn Orchestrator, EdgeEnv, or AIGuard into final decision

docs/portfolio/edgeenv_runtime_regression_lab_handoff.md

@@ -193,6 +193,7 @@ Expected Lab behavior:
 - When EdgeEnv preservation context is present, Lab renders `Lab EdgeEnv preservation context` with `lab_report_preservation_context_present=True`, `lab_preservation=present`, and `lab_context=present` so the Runtime Intelligence report gate and entrypoint evidence index use the same Lab-owned marker vocabulary.
 - When an EdgeEnv handoff manifest is provided, the bundle gate requires EdgeEnv-produced file keys, external AIGuard file keys, source repository mapping, artifact roles, producer contracts, and boundary flags to match Lab's Runtime Intelligence bundle contract.
 - The same manifest gate requires `expected_report_markers` to preserve these exact Lab-owned report markers: `Runtime Intelligence Risk Summary`, `Runtime replay duration scope`, `Orchestrator operation feed context`, `EdgeEnv fixture matrix coverage`, `Reviewer operation quick scan`, `Orchestrator task event rollup`, `Lab EdgeEnv preservation context`, `AIGuard operation risk rollup evidence`, `AIGuard task event rollup evidence`, `AIGuard operation timeline evidence`, `AIGuard runtime operation anomalies`, `AIGuard remote dispatch event summary`, `AIGuard remote event summary consistency`, `Remote fallback starter evidence`, `lab=Remote fallback starter evidence; evidence=remote_execution_recovered_by_fallback`, `AIGuard producer-lineage guard alignment`, and `Lab remains the final deployment decision owner.`.
+- Reviewer navigation can trace Orchestrator curated samples through AIGuard evidence into Lab report rows: `agent_scheduler_delay_sample.json` -> `scheduler_delay_pattern` -> `Reviewer operation quick scan` / `Orchestrator queue/deadline/fallback markers`, and `remote_fallback_recovery_sample.json` -> `remote_execution_recovered_by_fallback` -> `Remote fallback starter evidence`. Lab does not treat those curated samples as benchmark outputs, production retry proof, or deployment policy inputs.
 - The external AIGuard artifact gate also requires `runtime_queue_overload`
   raw context to preserve
   `orchestrator_candidate_operation_max_total_queue_depth=7`, keeping the

tests/test_runtime_intelligence_bundle_manifest.py

@@ -218,13 +218,15 @@ def test_readme_runtime_intelligence_section_stays_scannable():
     assert "Is telemetry/replay evidence complete enough?" in readme
     assert "Is there an operation risk worth opening first?" in readme
     assert "Which preserved run/path is being reviewed?" in readme
+    assert "Which upstream samples explain the handoff?" in readme
     assert "Which warnings remain review context only?" in readme
     for row in [
         "최종 판단 owner는 누구인가?",
         "runtime regression을 비교해도 되는가?",
         "telemetry/replay evidence가 충분한가?",
         "먼저 열어볼 operation risk가 있는가?",
         "어떤 preserved run/path를 보는가?",
+        "upstream sample handoff는 어디서 확인하는가?",
         "어떤 warning이 review context로만 남는가?",
     ]:
         assert row in readme_ko
@@ -247,10 +249,32 @@ def test_readme_runtime_intelligence_section_stays_scannable():
         "Remote fallback starter evidence",
         "Lab remains the final deployment decision owner",
         "production_remote_execution=false",
+        "agent_scheduler_delay_sample.json",
+        "remote_fallback_recovery_sample.json",
+        "scheduler_delay_pattern",
+        "remote_execution_recovered_by_fallback",
     ]:
         assert marker in readme
         assert marker in readme_ko
 
+    handoff = (
+        REPO_ROOT
+        / "docs"
+        / "portfolio"
+        / "edgeenv_runtime_regression_lab_handoff.md"
+    ).read_text(encoding="utf-8")
+    for marker in [
+        "agent_scheduler_delay_sample.json",
+        "remote_fallback_recovery_sample.json",
+        "scheduler_delay_pattern",
+        "remote_execution_recovered_by_fallback",
+        "Reviewer operation quick scan",
+        "Remote fallback starter evidence",
+        "benchmark outputs",
+        "deployment policy inputs",
+    ]:
+        assert marker in handoff
+
 
 def test_readme_internal_links_include_matching_korean_labels():
     readme = (REPO_ROOT / "README.md").read_text(encoding="utf-8")