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51 changes: 27 additions & 24 deletions README.ko.md
Original file line number Diff line number Diff line change
Expand Up @@ -220,30 +220,33 @@ Cross-repo evidence:

Runtime Intelligence smoke:

- Orchestrator operation feed를 supplemental context로 보존
- EdgeEnv telemetry history/regression evidence를 Lab report에 연결
- Runtime history seed `run_config` snapshot을 replay/comparability traceability로 표시
- Jetson EdgeEnv preservation smoke는 entrypoint가 device-local ONNX Runtime probe evidence, live `tegrastats`, Runtime operation summary를 EdgeEnv run evidence로 보존한 뒤 Lab deployment risk report까지 연결할 수 있음을 확인합니다.
- 사용 가능한 경우 AIGuard deterministic runtime evidence 보존
- AIGuard `runtime_history_seed_run_config_traceability` evidence를 gate에서 필수 traceability evidence로 검증
- AIGuard raw context의 device-local producer lineage를 traceability evidence로 표시
- 기존 JSON contract를 바꾸지 않고 Lab-owned Runtime Intelligence Risk Summary 생성

EdgeEnv runtime regression report에 `runtime_telemetry_context`가 포함되면 Lab은 이를 supplemental telemetry coverage / evidence-gap context로 표시하되, final deployment decision ownership은 Lab에 남깁니다.

Runtime Intelligence report에서 읽어야 할 핵심 row:

- EdgeEnv comparability / regression evidence
- telemetry replay gap
- Runtime history seed `run_config` traceability
- Orchestrator device-local producer lineage
- Lab EdgeEnv preservation context marker
- Jetson/device-local preservation row의 `identity=jetson_device_local_preservation`
및 `path=device_local_starter` 식별 label
- Jetson/device-local preservation detail row의 producer/source/stage/resource
navigation context
- AIGuard deterministic anomaly evidence
- Lab-owned deployment decision
- Orchestrator operation feed를 supplemental context로 보존합니다.
- EdgeEnv telemetry history/regression evidence를 Lab report에 연결합니다.
- AIGuard deterministic runtime evidence가 있으면 같은 Lab-owned report에 보존합니다.
- Jetson EdgeEnv preservation smoke는 device-local ONNX Runtime probe evidence, live `tegrastats`, Runtime operation summary가 EdgeEnv run evidence를 거쳐 Lab deployment risk report까지 이어지는지 확인합니다.
- 기존 JSON contract를 바꾸지 않고 Lab-owned Runtime Intelligence Risk Summary를 생성합니다.

### Runtime Intelligence Risk Summary 빠른 읽기

| 먼저 볼 항목 | Quick signal | 의미 |
|---|---|---|
| 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. |
| 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. |
| 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. |

세부 marker contract는 [docs/portfolio/edgeenv_runtime_regression_lab_handoff.md](docs/portfolio/edgeenv_runtime_regression_lab_handoff.md)에 정리되어 있습니다.

최신 Jetson EdgeEnv preservation smoke:

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56 changes: 24 additions & 32 deletions README.md
Original file line number Diff line number Diff line change
Expand Up @@ -515,46 +515,38 @@ If the EdgeEnv report includes `runtime_telemetry_context`, Lab shows supplement

When `--with-guard` is used with EdgeEnv evidence, Lab preserves deterministic
AIGuard evidence in the same Lab-owned report. The summary is a reviewer
navigation surface: it makes runtime risk evidence easy to find, while Lab
remains the final deployment decision owner.
navigation surface, not a new owner: Lab remains the final deployment decision
owner.

The report starts with a `Reviewer Focus` table using
`Focus / Quick signal / First read` columns so reviewers can quickly scan the
Decision owner, EdgeEnv regression gate, Telemetry/replay quality,
Operation context, and AIGuard warnings before reading the detailed evidence
rows.
Start with the report's `Reviewer Focus` table. It uses
`Focus / Quick signal / First read` columns so reviewers can scan the main risk
areas before opening detailed evidence rows.

| Reviewer question | Where to look | Meaning |
| First read | Quick signal | What it tells you |
|---|---|---|
| Did AIGuard preserve EdgeEnv/Orchestrator producer lineage? | `producer_lineage_evidence_type=edgeenv_orchestrator_producer_lineage` and `runtime_history_seed_run_config_traceability` | Confirms the expected deterministic AIGuard evidence reached the Lab-owned report. |
| Is there operation pressure? | `Orchestrator queue/deadline/fallback markers` | Keeps `queue_pressure_reason`, `max_total_queue_depth`, deadline misses, and fallback count together before the detailed task rollup. |
| Can queue depth be traced back to AIGuard raw context? | `AIGuard max queue raw-context traceability` | Ties visible `max_total_queue_depth` markers back to deterministic AIGuard context and Orchestrator operation evidence. |
| What replay window was used? | `Runtime replay duration scope` | Shows `duration_label`, `duration_class`, frame count, `duration_source`, and `duration_scope_label` such as `source=entrypoint_requested_frames`. |
| Was EdgeEnv preservation rendered by Lab? | `Lab EdgeEnv preservation context` | Shows `lab_report_preservation_context_present=True`, `lab_preservation=present`, and `lab_context=present` without making EdgeEnv the decision owner. |
| Is this the Jetson/device-local preservation path? | `Jetson/device-local EdgeEnv preservation run` | Starts with `identity=jetson_device_local_preservation` and `path=device_local_starter` when available. |
| Where are producer/source/resource details? | `Jetson/device-local EdgeEnv preservation details` | Keeps source, stage, device-local event, resource, and queue markers out of the short identity row. |
| Which tasks were affected? | `Orchestrator task event rollup` and `AIGuard task event rollup evidence` | Shows scheduler delay, deadline misses, fallback decisions, and queue/drop reasons as review context only. |
| Is there deterministic operation-risk evidence? | `AIGuard runtime operation anomalies` and `AIGuard Orchestrator Operation Evidence` | Preserves warning evidence without overriding EdgeEnv comparability or Lab deployment policy. |
| Is this remote dispatch starter evidence? | `AIGuard remote dispatch event summary` and `Remote fallback starter evidence` | Preserves `evidence_role=remote_dispatch_runtime_event_compact_summary`, `operation_boundary=remote dispatch starter evidence only`, and `production_remote_execution=false`. |
| 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. |
| 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. |
| 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. |

These rows do not turn Orchestrator, EdgeEnv, or AIGuard into final decision
owners. They also do not present the path as production remote execution,
long-lived worker readiness, cloud orchestration, or production readiness.

Markdown and HTML reports include a Runtime Intelligence Risk Summary that connects:

- EdgeEnv comparability and regression evidence
- telemetry replay gaps
- Runtime history seed and run_config traceability
- Orchestrator operation risk summary markers
- compact queue/deadline/fallback operation markers with `max_total_queue_depth`
- AIGuard raw-context traceability for `max_total_queue_depth`
- Lab EdgeEnv preservation context markers
- device-local producer lineage handoff
- Orchestrator-declared downstream guard alignment
- remote dispatch starter boundary evidence
- AIGuard deterministic evidence
- the Lab-owned deployment decision
For the full marker contract, see
[docs/portfolio/edgeenv_runtime_regression_lab_handoff.md](docs/portfolio/edgeenv_runtime_regression_lab_handoff.md)
([한국어: EdgeEnv 런타임 회귀 Lab handoff 문서](docs/portfolio/edgeenv_runtime_regression_lab_handoff.md)).

Latest Jetson EdgeEnv preservation smoke:

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18 changes: 7 additions & 11 deletions tests/test_runtime_intelligence_bundle_manifest.py
Original file line number Diff line number Diff line change
Expand Up @@ -172,7 +172,8 @@ def test_runtime_intelligence_docs_record_jetson_edgeenv_preservation_boundary()
def test_readme_runtime_intelligence_section_stays_scannable():
readme = (REPO_ROOT / "README.md").read_text(encoding="utf-8")

assert "| Reviewer question | Where to look | Meaning |" in readme
assert "| First read | Quick signal | What it tells you |" in readme
assert "| Marker group | Key rows / labels | Why it matters |" in readme
assert "Reviewer Focus" in readme
assert "`Focus / Quick signal / First read`" in readme
assert "Decision owner" in readme
Expand All @@ -181,16 +182,11 @@ def test_readme_runtime_intelligence_section_stays_scannable():
assert "Operation context" in readme
assert "AIGuard warnings" in readme
for row in [
"Did AIGuard preserve EdgeEnv/Orchestrator producer lineage?",
"Is there operation pressure?",
"Can queue depth be traced back to AIGuard raw context?",
"What replay window was used?",
"Was EdgeEnv preservation rendered by Lab?",
"Is this the Jetson/device-local preservation path?",
"Where are producer/source/resource details?",
"Which tasks were affected?",
"Is there deterministic operation-risk evidence?",
"Is this remote dispatch starter evidence?",
"Producer lineage",
"Queue pressure",
"Replay and preservation",
"Task and operation risk",
"Remote starter boundary",
]:
assert row in readme

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