diff --git a/.gitignore b/.gitignore
index 14969b9..2b802b3 100644
--- a/.gitignore
+++ b/.gitignore
@@ -19,4 +19,7 @@ capture-android/build/
 capture-android/app/build/
 capture-android/local.properties
 infra/cdk.context.json
+infra/image_uris.json
 .worktrees/
+work_deploy*.log
+work_cdk_outputs.json
diff --git a/README.md b/README.md
new file mode 100644
index 0000000..fff439c
--- /dev/null
+++ b/README.md
@@ -0,0 +1,84 @@
+# GRIDPRINT
+
+GRIDPRINT checks whether a video is real by reading the power-grid frequency from the flicker of the lights in
+the room. Mains-powered lights flicker at twice the grid frequency. A phone's rolling shutter reads the sensor one
+row at a time, so the flicker shows up as faint horizontal bands. GRIDPRINT measures those bands with OpenCV 5,
+rebuilds the grid-frequency track (the electric network frequency, ENF), and compares it with a recorded
+reference log of the real grid. The result is one of three verdicts: `VERIFIED`, `CONTRADICTED` (only final after
+a human reviewer approves it) or `INCONCLUSIVE`. A missing signal is never evidence that a video is fake. GRIDPRINT
+is not a deepfake classifier and not cryptographic proof.
+
+Entry for the OpenCV AI Competition 2026 (OpenCV 5 + AWS). The specification is in [SPEC.md](SPEC.md); current
+status is in [docs/PROGRESS.md](docs/PROGRESS.md).
+
+- Endpoint: see [docs/JUDGE_GUIDE.md](docs/JUDGE_GUIDE.md)
+- Technical report: [docs/TECHNICAL_REPORT.md](docs/TECHNICAL_REPORT.md)
+- Architecture: [docs/ARCHITECTURE.md](docs/ARCHITECTURE.md) · diagrams in [docs/diagrams/](docs/diagrams/)
+- Responsible use: [docs/RESPONSIBLE_USE.md](docs/RESPONSIBLE_USE.md)
+- Video: (not recorded yet — human task H8)
+
+## What is in the repository
+
+| Part | Path |
+|---|---|
+| Engine (OpenCV 5 stages S1–S15) | `engine/gridprint_engine/` |
+| Agent (planner, policies, trace) and MCP tool server | `agent/`, `mcp_server/` |
+| API and job worker | `api/` |
+| Verify web app | `web/` |
+| Capture Android app | `capture-android/` |
+| Grid-frequency Node (hardware, firmware, ingest) | `node/` |
+| Camera calibration rig | `calibration_rig/` |
+| AWS infrastructure (CDK v2) | `infra/` |
+| Simulator and evaluation | `eval/` |
+| COOL benchmark | `bench/` |
+
+## Quick start (local)
+
+Requirements: Python 3.11, [uv](https://docs.astral.sh/uv/), FFmpeg on `PATH`, Node.js 24 (for the web app).
+
+```bash
+make setup
+```
+
+```bash
+make test
+```
+
+```bash
+python -m eval.make_demo_inputs
+```
+
+```bash
+make local
+```
+
+`make local` serves the API and the built web app at `http://127.0.0.1:8000` with local file storage and the
+deterministic agent planner. The reviewer token for local use is written to `work/local_reviewer_token.txt`.
+On Windows without GNU make, use `./make <target>` (Git Bash) or `make.cmd <target>`.
+
+## Deploy to AWS
+
+1. Complete human task H1 in [docs/HUMAN_TASKS.md](docs/HUMAN_TASKS.md) (CLI profile `gridprint`).
+2. Build the arm64 images (no local Docker needed): `python infra/build_images.py`.
+3. Deploy all stacks: `make deploy`. Remove everything: `make destroy`.
+
+## Evaluate and benchmark
+
+```bash
+make eval
+```
+
+```bash
+make bench
+```
+
+Synthetic results are labeled SYNTHETIC and are never presented as real-world accuracy. Every reported number
+lives under `results/` with a source tag (SPEC 14.3).
+
+## Final check
+
+```bash
+make final-check
+```
+
+It prints one line per item of the final checklist (SPEC 17.3) and `ALL CHECKS PASSED` only when all hold.
diff --git a/agent/orchestrator.py b/agent/orchestrator.py
index 8ac2408..05631ff 100644
--- a/agent/orchestrator.py
+++ b/agent/orchestrator.py
@@ -44,6 +44,36 @@ async def call(self, tool: str, args: dict[str, Any]) -> dict[str, Any]:
         return json.loads(text) if text else {}
 
 
+_PREREQ_FREE = {"probe_video", "compute_verdict", "request_user_input", "request_human_review", "render_report"}
+
+
+def _probe_ok(history: list[Step]) -> bool:
+    return any(h.tool == "probe_video" and h.error is None for h in history)
+
+
+def _needs_rule(a: Action, history: list[Step]) -> bool:
+    if a.tool not in {"render_report", "compute_verdict"} and any(h.tool == a.tool and h.args == a.args
+                                                                     for h in history):
+        return True  # identical call already made (failed or not): no new information
+    if a.tool == "extract_flicker" and (a.args.get("nominal_hz") or a.args.get("axis")) and not any(
+            h.tool == "extract_flicker" and h.result for h in history):
+        return True  # B1 allows switching frequency or axis only after a weak first extraction
+    asked = {h.args.get("kind") for h in history if h.tool == "request_user_input"}
+    if a.tool == "request_user_input" and a.args.get("kind") in asked:
+        return True
+    return a.tool not in _PREREQ_FREE and not _probe_ok(history)
+
+
+def _why(a: Action, history: list[Step]) -> str:
+    if any(h.tool == a.tool and h.args == a.args for h in history):
+        return "identical call already made"
+    if a.tool == "extract_flicker" and not any(h.tool == "extract_flicker" and h.result for h in history):
+        return "frequency or axis override before the first extraction"
+    if a.tool == "request_user_input":
+        return "same request already made"
+    return "video not probed yet"
+
+
 async def run_job(job_id: str, planner: Planner, caller: ToolCaller, max_iterations: int,
                   max_tool_calls: int, trace_path: Path | None = None) -> tuple[Trace, list[Step]]:
     trace = Trace(job_id)
@@ -56,6 +86,13 @@ async def run_job(job_id: str, planner: Planner, caller: ToolCaller, max_iterati
         except Exception as e:  # planner failure (e.g. Bedrock unavailable): fall back for this step
             proposed = FallbackPlanner().next_action(history)
             proposed.reason = f"planner error ({type(e).__name__}); fallback rule: {proposed.reason}"
+        # Guard the LLM planner: a call that repeats a failed call, or an analysis call before the video was
+        # probed successfully, is replaced by the deterministic rule for this step (recorded in the trace).
+        if planner.kind != "fallback" and proposed.tool is not None and _needs_rule(proposed, history):
+            rule = FallbackPlanner().next_action(history)
+            rule.reason = (f"guard: planner proposed {proposed.tool} {proposed.args} ({_why(proposed, history)}); "
+                           f"fallback rule: {rule.reason}")
+            proposed = rule
         action, note = policies.enforce(proposed, st)
         if action.tool is None:
             if proposed.tool is not None or note:
diff --git a/agent/planner_bedrock.py b/agent/planner_bedrock.py
index 0ce29b3..5e94bc2 100644
--- a/agent/planner_bedrock.py
+++ b/agent/planner_bedrock.py
@@ -79,7 +79,18 @@ def next_action(self, history: list[Step]) -> Action:
         return Action(None, {}, reason or "no tool chosen")
 
 
-def make_client(profile: str | None, region: str) -> Any:
+def make_client(profile: str | None, region: str, role_arn: str | None = None,
+                external_id: str | None = None) -> Any:
+    """bedrock-runtime client. With `role_arn`, the model is called through a role in the model account
+    (cross-account, D-026); the role allows only InvokeModel on the pinned model."""
     import boto3
 
-    return boto3.Session(profile_name=profile, region_name=region).client("bedrock-runtime")
+    session = boto3.Session(profile_name=profile, region_name=region)
+    if role_arn:
+        kw = {"RoleArn": role_arn, "RoleSessionName": "planner"}
+        if external_id:
+            kw["ExternalId"] = external_id
+        c = session.client("sts").assume_role(**kw)["Credentials"]
+        session = boto3.Session(aws_access_key_id=c["AccessKeyId"], aws_secret_access_key=c["SecretAccessKey"],
+                                aws_session_token=c["SessionToken"], region_name=region)
+    return session.client("bedrock-runtime")
diff --git a/agent/policies.py b/agent/policies.py
index bcf5241..48b3534 100644
--- a/agent/policies.py
+++ b/agent/policies.py
@@ -19,6 +19,40 @@
 }
 
 
+def _zones() -> set[str]:
+    try:
+        from pathlib import Path
+
+        import yaml
+
+        p = Path(__file__).resolve().parents[1] / "config" / "zones.yaml"
+        return {z["id"] for z in yaml.safe_load(p.read_text())["zones"]}
+    except Exception:  # config missing: accept no zone argument
+        return set()
+
+
+# allowed values per argument; a value outside the set is dropped (the engine default applies)
+ALLOWED_VALUES: dict[str, Any] = {
+    "method": {"auto", "sidecar", "profile", "blind"}, "strictness": {"normal", "strict"},
+    "strategy": {"all", "top", "coherent", "bright"}, "axis": {"rows+", "rows-", "cols+", "cols-"},
+    "nominal_hz": {50, 60}, "kind": {"original_file", "camera_model", "claimed_time", "longer_clip"},
+    "final": {True, False}, "zone": _zones(),
+}
+
+
+def _valid(k: str, v: Any) -> bool:
+    if k in ALLOWED_VALUES:
+        try:
+            return v in ALLOWED_VALUES[k]
+        except TypeError:
+            return False
+    if k == "patch_ids":
+        return isinstance(v, list) and all(isinstance(i, int) for i in v)
+    if k == "frame_subset":
+        return v == "low_motion" or (isinstance(v, list) and all(isinstance(i, int) for i in v))
+    return isinstance(v, str | int | float) or v is None
+
+
 @dataclass
 class Action:
     tool: str | None  # None = planner wants to stop
@@ -53,10 +87,13 @@ def enforce(a: Action, st: PolicyState) -> tuple[Action, str | None]:
                           "policy: report must be rendered"), "report required"
         return a, None
     if a.tool not in ALL_TOOLS:
-        return Action("compute_verdict" if not st.verdict_done else None, {},
-                      "policy: unknown tool rejected"), f"unknown tool {a.tool}"
+        if st.verdict_done:
+            nxt, _ = enforce(Action(None, {}, ""), st)
+            nxt.reason = f"policy: unknown tool {a.tool} rejected; " + (nxt.reason or "job complete")
+            return nxt, f"unknown tool {a.tool}"
+        return Action("compute_verdict", {}, "policy: unknown tool rejected"), f"unknown tool {a.tool}"
     note = None
-    args = {k: v for k, v in a.args.items() if k in ALLOWED_ARGS[a.tool]}
+    args = {k: v for k, v in a.args.items() if k in ALLOWED_ARGS[a.tool] and _valid(k, v)}
     if args != {k: v for k, v in a.args.items() if k != "job_id"}:
         note = "policy: disallowed arguments removed"
     a = Action(a.tool, args, a.reason)
@@ -66,11 +103,10 @@ def enforce(a: Action, st: PolicyState) -> tuple[Action, str | None]:
     if a.tool == "extract_flicker" and st.iterations >= st.max_iterations:
         st.budget_exhausted = True
         return Action("compute_verdict", {}, "policy: iteration budget exhausted (B5)"), "iteration budget"
-    if st.verdict_done and a.tool in ANALYSIS_TOOLS:
-        return Action(None, {}, "policy: compute_verdict must be the last analysis call"), \
-            f"{a.tool} after verdict blocked"
-    if st.verdict_done and a.tool == "compute_verdict":
-        return Action(None, {}, "policy: verdict already computed"), "repeat verdict blocked"
+    if st.verdict_done and a.tool in ANALYSIS_TOOLS | {"compute_verdict"}:
+        nxt, _ = enforce(Action(None, {}, ""), st)  # finish the job: review if needed, then the report
+        nxt.reason = f"policy: {a.tool} after the verdict is not allowed; " + (nxt.reason or "job complete")
+        return nxt, f"{a.tool} after verdict blocked"
     if a.tool == "render_report":
         if not st.verdict_done:
             return Action("compute_verdict", {}, "policy: verdict before report"), "report before verdict"
diff --git a/agent/tests/test_agent.py b/agent/tests/test_agent.py
index b887e61..20b73d5 100644
--- a/agent/tests/test_agent.py
+++ b/agent/tests/test_agent.py
@@ -148,7 +148,7 @@ def test_policy_blocks_final_report_for_contradicted_and_analysis_after_verdict(
     a, note = policies.enforce(Action("render_report", {"final": True}, "x"), st)
     assert a.tool == "render_report" and a.args["final"] is False and note
     a, _ = policies.enforce(Action("extract_flicker", {}, "x"), st)
-    assert a.tool is None
+    assert a.tool == "render_report" and a.args["final"] is False  # no analysis after the verdict
 
 
 def test_policy_strips_threshold_arguments():
@@ -198,3 +198,68 @@ def test_bedrock_planner_is_policed():
 def test_tool_config_lists_all_tools():
     names = {t["toolSpec"]["name"] for t in tool_config()["tools"]}
     assert policies.ALL_TOOLS <= names
+
+
+class FailingProbeTools(ScriptedTools):
+    """probe_video fails once, then succeeds."""
+
+    def __init__(self) -> None:
+        super().__init__()
+        self.probe_failed = False
+
+    async def call(self, tool: str, args: dict[str, Any]) -> dict[str, Any]:
+        if tool == "probe_video" and not self.probe_failed:
+            self.calls.append((tool, args))
+            self.probe_failed = True
+            raise RuntimeError("Unable to allocate memory")
+        return await super().call(tool, args)
+
+
+def test_llm_guard_replaces_repeated_failures_and_out_of_order_calls():
+    # an LLM that ignores errors: always asks for motion analysis
+    client = FakeBedrock([{"tool": "analyze_motion", "input": {"strictness": "normal"}}])
+    t = FailingProbeTools()
+    trace, _ = run(t, BedrockPlanner(client, "test-model"))
+    names = tools_called(t)
+    assert names[0] == "probe_video" and names[1] == "compute_verdict"  # guard: unreadable input ends the job
+    assert any("guard:" in s.decision_reason for s in trace.steps)
+    assert names.count("analyze_motion") <= 2  # the repeated call is not retried endlessly
+    assert names[-1] == "render_report"  # the job always ends with a report
+
+
+def test_llm_guard_blocks_premature_overrides_and_identical_repeats():
+    script = [{"tool": "probe_video"}, {"tool": "estimate_readout", "input": {"method": "auto"}},
+              {"tool": "analyze_motion", "input": {"strictness": "normal"}},
+              {"tool": "propose_patches", "input": {"strategy": "top"}},
+              {"tool": "extract_flicker", "input": {"nominal_hz": 60}},
+              {"tool": "propose_patches", "input": {"strategy": "top"}}]
+    client = FakeBedrock(script)
+    t = ScriptedTools()
+    trace, _ = run(t, BedrockPlanner(client, "test-model"))
+    ex = [a for n, a in t.calls if n == "extract_flicker"]
+    assert ex and "nominal_hz" not in ex[0]  # the first extraction used the zone default
+    assert sum(1 for n, a in t.calls if n == "propose_patches" and a.get("strategy") == "top") <= 1
+    assert any("frequency or axis override" in s.decision_reason for s in trace.steps)
+    assert t.calls[-1][0] == "render_report"
+
+
+def test_policy_after_verdict_finishes_with_report():
+    st = PolicyState(max_iterations=6, max_tool_calls=30, verdict_done=True, verdict="INCONCLUSIVE")
+    a, note = policies.enforce(Action("compute_verdict", {}, "again"), st)
+    assert a.tool == "render_report" and a.args["final"] is True and note
+    st2 = PolicyState(max_iterations=6, max_tool_calls=30, verdict_done=True, verdict="CONTRADICTED")
+    a, _ = policies.enforce(Action("match_reference", {}, "late"), st2)
+    assert a.tool == "request_human_review"
+
+
+def test_policy_drops_invalid_argument_values():
+    st = PolicyState(max_iterations=6, max_tool_calls=30)
+    a, note = policies.enforce(Action("match_reference", {"track_id": "t1", "zone": "global"}, "x"), st)
+    assert a.args == {"track_id": "t1"} and note
+    a, _ = policies.enforce(Action("extract_flicker", {"nominal_hz": 55, "axis": "diagonal"}, "x"), st)
+    assert a.args == {}
+    a, _ = policies.enforce(Action("match_reference", {"zone": "SIM50"}, "x"), st)
+    assert a.args == {"zone": "SIM50"}
+    st.verdict_done, st.verdict = True, "INCONCLUSIVE"
+    a, _ = policies.enforce(Action("render", {}, "x"), st)
+    assert a.tool == "render_report"
diff --git a/api/app.py b/api/app.py
index ffcea50..cf92047 100644
--- a/api/app.py
+++ b/api/app.py
@@ -195,20 +195,40 @@ def decide(review_id: str, body: DecisionBody, who: str = Depends(require_review
         ctx.store.put("Jobs", rv["job_id"], job)
         return {"review_id": review_id, "verdict": v.value, "lifecycle_state": st.value}
 
+    def demo_available(c: dict[str, Any]) -> bool:
+        if ctx.mode == "aws":  # demo inputs are seeded to the results bucket by scripts/seed_aws.py
+            return bool(c.get("seeded", True))
+        return (REPO / c["video"]).exists()
+
+    def demo_input(c: dict[str, Any], field: str, job_id: str) -> Path | None:
+        rel = c.get(field)
+        if not rel:
+            return None
+        if ctx.mode == "aws":
+            dst = ctx.workdir / job_id / Path(rel).name
+            return ctx.storage.get_file(f"demo/{Path(rel).name}", dst)
+        return REPO / rel
+
     @app.get("/v1/demo-cases")
     def demo_cases() -> list[dict[str, Any]]:
         return [{k: c[k] for k in ("id", "title", "description", "expected_verdict")} for c in load_demo_cases()
-                if (REPO / c["video"]).exists()]
+                if demo_available(c)]
 
     @app.post("/v1/demo-cases/{case_id}/run")
     def run_demo(case_id: str) -> dict[str, Any]:
         case = next((c for c in load_demo_cases() if c["id"] == case_id), None)
-        if case is None or not (REPO / case["video"]).exists():
+        if case is None or not demo_available(case):
             raise HTTPException(404, "unknown demo case")
         job_id = uuid.uuid4().hex[:12]
         key = f"uploads/{job_id}/input.mp4"
-        ctx.storage.put_file(key, REPO / case["video"])
-        sidecar = json.loads((REPO / case["sidecar"]).read_text()) if case.get("sidecar") else None
+        try:
+            video = demo_input(case, "video", job_id)
+            side_p = demo_input(case, "sidecar", job_id)
+        except Exception as e:
+            raise HTTPException(404, "demo input not available") from e
+        assert video is not None
+        ctx.storage.put_file(key, video)
+        sidecar = json.loads(side_p.read_text()) if side_p else None
         ctx.store.put("Jobs", job_id, {"job_id": job_id, "status": "queued", "upload_key": key,
                                        "claim": case.get("claim") or {}, "sidecar": sidecar, "demo_case": case_id,
                                        "created": datetime.now(tz=UTC).isoformat()})
@@ -234,6 +254,11 @@ def files(path: str) -> FileResponse:
                 raise HTTPException(404, "not found")
             return FileResponse(p)
 
+    dist = REPO / "web" / "dist"
+    if dist.exists():  # the Verify web app, served from the same origin as the API
+        from fastapi.staticfiles import StaticFiles
+
+        app.mount("/", StaticFiles(directory=dist, html=True), name="web")
     return app
 
 
diff --git a/api/local.py b/api/local.py
index f3685cf..b55f28d 100644
--- a/api/local.py
+++ b/api/local.py
@@ -10,7 +10,6 @@
 from pathlib import Path
 
 import uvicorn
-from fastapi.staticfiles import StaticFiles
 
 REPO = Path(__file__).resolve().parents[1]
 
@@ -24,10 +23,7 @@ def main() -> None:
         os.environ["GRIDPRINT_REVIEWER_TOKEN"] = tok_file.read_text().strip()
     from api.app import create_app
 
-    app = create_app()
-    dist = REPO / "web" / "dist"
-    if dist.exists():
-        app.mount("/", StaticFiles(directory=dist, html=True), name="web")
+    app = create_app()  # also serves web/dist when it has been built
     print(f"GRIDPRINT local: http://127.0.0.1:8000  (reviewer token in {tok_file})")
     uvicorn.run(app, host="127.0.0.1", port=int(os.environ.get("PORT", "8000")))
 
diff --git a/api/worker.py b/api/worker.py
index 0f68d72..07f5352 100644
--- a/api/worker.py
+++ b/api/worker.py
@@ -28,7 +28,9 @@ def make_planner(ctx: Context) -> Any:
     if cfg["agent"]["planner"] == "bedrock" and cfg["bedrock"]["enabled"]:
         from agent.planner_bedrock import BedrockPlanner, make_client
 
-        client = make_client(cfg["aws"]["profile"] if ctx.mode == "local" else None, cfg["aws"]["region"])
+        b = cfg["bedrock"]
+        profile = cfg["aws"]["profile"] if ctx.mode == "local" else None
+        client = make_client(profile, b.get("region", cfg["aws"]["region"]), b.get("role_arn"), b.get("external_id"))
         return BedrockPlanner(client, cfg["bedrock"]["model_id"], cfg["bedrock"]["max_tokens"])
     return FallbackPlanner()
 
@@ -68,13 +70,21 @@ def process_job(ctx: Context, job_id: str) -> None:
             publish_artifacts(ctx, job_id, jobdir)
         else:
             job.update({"status": "failed", "error": "no result produced; see trace"})
+            publish_artifacts(ctx, job_id, jobdir)  # the trace explains the failure
         job["user_requests"] = [r for r in ctx.store.scan("UserRequests") if r.get("job_id") == job_id]
         ctx.store.put("Jobs", job_id, job)
     except Exception as e:
         job["status"] = "failed"
         job["error"] = f"{type(e).__name__}: {e}"
         (jobdir / "error.txt").write_text(traceback.format_exc())
+        print(traceback.format_exc(), flush=True)  # also to CloudWatch
         ctx.store.put("Jobs", job_id, job)
+        try:
+            ctx.storage.put_file(f"jobs/{job_id}/error.txt", jobdir / "error.txt")
+            if (jobdir / "trace.json").exists():
+                ctx.storage.put_file(f"jobs/{job_id}/trace.json", jobdir / "trace.json")
+        except Exception:
+            pass
 
 
 def publish_artifacts(ctx: Context, job_id: str, jobdir: Path) -> None:
diff --git a/config/default.yaml b/config/default.yaml
index 44477e8..2c40160 100644
--- a/config/default.yaml
+++ b/config/default.yaml
@@ -3,11 +3,18 @@
 aws:
   profile: gridprint
   region: us-east-1            # DECISIONS D-005
+  resource_prefix: orchard     # neutral name for all AWS resources in the deployment account (D-021)
+  worker_instance_type: c8g.xlarge   # 4 vCPU Graviton4; fits the account on-demand vCPU quota (D-024)
+  worker_max_instances: 1
 bedrock:
-  enabled: false               # turned on after V6 is verified with the gridprint profile (H1)
-  # Inference-profile ID as listed by AWS (see docs/VERIFICATION.md V6). Re-check with
-  # `aws bedrock list-inference-profiles --profile gridprint` before enabling.
-  model_id: global.anthropic.claude-sonnet-4-6
+  enabled: true
+  # Amazon Nova Lite through a role in the model account (D-026). Anthropic models on Bedrock need a
+  # Marketplace payment method that neither account has yet; Nova is billed directly by AWS.
+  model_id: us.amazon.nova-lite-v1:0
+  in_account_model_id: global.anthropic.claude-sonnet-4-6   # AI stack policy; usable once Claude access is granted
+  region: us-east-1
+  role_arn: arn:aws:iam::768669378827:role/orchard-planner
+  external_id: orchard-planner
   max_tokens: 1024
 limits:
   max_file_bytes: 524288000    # 500 MiB
@@ -59,7 +66,8 @@ engine:
     segment_offset_tolerance_s: 3
     claim_min_tolerance_s: 60
   continuity:
-    smooth_window_s: 4.0
+    jump_window_s: 1.0           # frames on each side of a boundary for the two line fits (D-023)
+    min_frame_snr: 1.0            # linear; frames below 0 dB fit SNR are left out of the phase series (D-022)
   segmentation:
     model_path: models/human_segmentation_pphumanseg_2023mar.onnx
     input_size: [192, 192]
@@ -75,7 +83,7 @@ engine:
 agent:
   max_iterations: 6
   max_tool_calls: 30
-  planner: fallback             # fallback | bedrock
+  planner: bedrock              # bedrock | fallback; fallback also covers any Bedrock error per step
 evaluation:
   target_false_contradicted_rate: 0.01   # DECISIONS D-019 (written before any test data was examined)
 grid:
diff --git a/config/demo_cases.yaml b/config/demo_cases.yaml
index 0a20993..3d61cba 100644
--- a/config/demo_cases.yaml
+++ b/config/demo_cases.yaml
@@ -3,7 +3,7 @@
 # `source: human` inputs are recorded by people (H4, H5, H7) and placed at the listed path.
 cases:
   - id: capture-verified
-    title: "Capture clip with sensor sidecar (SYNTHETIC stand-in until H5)"
+    title: "Capture clip with sensor sidecar (SYNTHETIC test clip)"
     description: "Expected VERIFIED with an estimated recording time."
     expected_verdict: VERIFIED
     source: synthetic
@@ -15,12 +15,20 @@ cases:
     expected_verdict: CONTRADICTED
     source: synthetic
     video: data/demo/cut-1s.mp4
+    claim:
+      claimed_zone: SIM50
+      claimed_time_utc: "2026-01-20T10:00:00Z"
+      claimed_time_tolerance_s: 300
   - id: insertion
     title: "Insertion from another time (SYNTHETIC)"
     description: "Expected CONTRADICTED with SEGMENT_OFFSET_INCONSISTENT."
     expected_verdict: CONTRADICTED
     source: synthetic
     video: data/demo/insertion.mp4
+    claim:
+      claimed_zone: SIM50
+      claimed_time_utc: "2026-01-20T10:00:00Z"
+      claimed_time_tolerance_s: 300
   - id: dropped-frames
     title: "Dropped frames with original timestamps (SYNTHETIC)"
     description: "Expected VERIFIED with DROPPED_FRAMES_EXPLAINED."
@@ -29,13 +37,13 @@ cases:
     video: data/demo/dropped-frames.mp4
     sidecar: data/demo/dropped-frames.sidecar.json
   - id: generated-room
-    title: "Synthetic room video from a video generator (H5)"
+    title: "Synthetic room video from a video generator"
     description: "Expected INCONCLUSIVE (SIGNAL_ABSENT). A missing signal alone does not mean fake."
     expected_verdict: INCONCLUSIVE
     source: human
     video: data/demo/generated-room.mp4
   - id: daylight-only
-    title: "Daylight-only room (SYNTHETIC stand-in until H5)"
+    title: "Daylight-only room (SYNTHETIC test clip)"
     description: "Expected INCONCLUSIVE."
     expected_verdict: INCONCLUSIVE
     source: synthetic
@@ -47,7 +55,7 @@ cases:
     source: synthetic
     video: data/demo/agent-recovery.mp4
   - id: face-composite
-    title: "Face composite of a consenting team member (EXPERIMENTAL, H7)"
+    title: "Face composite of a consenting team member (EXPERIMENTAL)"
     description: "Shows the experimental face-region check. Never the only basis for CONTRADICTED."
     expected_verdict: CONTRADICTED
     source: human
diff --git a/config/zones.yaml b/config/zones.yaml
index 1ccc0bd..a76c055 100644
--- a/config/zones.yaml
+++ b/config/zones.yaml
@@ -16,6 +16,10 @@ zones:
     nominal_hz: 60
     timezone: America/New_York
     description: US Eastern Interconnection
+  - id: CN
+    nominal_hz: 50
+    timezone: Asia/Shanghai
+    description: China (State Grid) synchronous area; used for public EV-ENFD reference data
   - id: SIM50
     nominal_hz: 50
     timezone: UTC
diff --git a/docs/ARCHITECTURE.md b/docs/ARCHITECTURE.md
index 2b2be41..f38dcdc 100644
--- a/docs/ARCHITECTURE.md
+++ b/docs/ARCHITECTURE.md
@@ -8,7 +8,7 @@ Diagrams:
 
 ## 1. Build status
 
-The components below are the target design. Their build state is tracked in `docs/PROGRESS.md`. Do not read this document as a statement that a component is deployed. At the time of writing, the engine package (`engine/gridprint_engine/`) and the simulator (`eval/simulator/`) contain code. The API, agent, MCP server, web app, infrastructure, Node, and Capture app are later milestones (M4–M8, M11).
+The components below are the system design. All components have code in the repository. Build and acceptance state is tracked in `docs/PROGRESS.md`; the AWS deployment status is in `docs/TECHNICAL_REPORT.md` §6. On 2026-10-27 all stacks except Web (CloudFront, waiting for AWS account verification) are deployed in `us-east-1`. The engine runs stock OpenCV 5 on Graviton; COOL is supported by the stack but not active yet.
 
 ## 2. Components
 
@@ -18,7 +18,7 @@ The components below are the target design. Their build state is tracked in `doc
 | GRIDPRINT Verify | `web/` | Amazon S3 + Amazon CloudFront, behind AWS WAF | Upload, demo cases, live grid tile, job page with live agent trace, verdict card, overlay player, reviewer screen. |
 | API | `api/` | FastAPI on Amazon ECS Fargate, `linux/arm64` | Jobs, presigned uploads, user input, reviewer queue and decisions, demo cases, live grid samples, health. |
 | Jobs queue | CDK in `infra/` | Amazon SQS | Decouples the API from the engine workers. Worker autoscaling uses queue depth. |
-| Engine worker | `engine/`, `agent/`, `mcp_server/` | Amazon ECS on Graviton `c8g`, `linux/arm64`, OpenCV 5 + COOL | One task holds the agent orchestrator, the MCP client, and the MCP server `gridprint-engine` (stdio transport). |
+| Engine worker | `engine/`, `agent/`, `mcp_server/` | Amazon ECS on Graviton4 `c8g`, `linux/arm64`, OpenCV 5 (stock wheel); COOL AMI supported by the stack when `aws.cool_ami_id` is set | One task holds the agent orchestrator, the MCP client, and the MCP server `gridprint-engine` (stdio transport). |
 | GRIDPRINT Engine | `engine/gridprint_engine/` | inside the worker | OpenCV 5 analysis stages S1–S15 (SPEC Part 8). Python package with no AWS imports. |
 | GRIDPRINT Agent | `agent/` | inside the worker | Plans and adapts the analysis with engine tools. Planner: Claude on Amazon Bedrock, or the deterministic fallback planner. Never writes a verdict. |
 | Reference Store | DynamoDB `GridLog` | Amazon DynamoDB | Grid frequency per zone and UTC second. Key `zone#YYYYMMDD` + epoch second. |
@@ -59,11 +59,11 @@ Reference data flow: Node → MQTT/TLS → AWS IoT Core → topic rule → Lambd
 | S8 phase and frequency | `phase.py` | Per-frame least squares with `cv2.solve` (`DECOMP_SVD`, float64); DFT cross-check with `cv2.getOptimalDFTSize` and `cv2.dft` on a zero-filled, masked virtual time grid. |
 | S9 clock bias | `enf.py` | Demean both tracks. |
 | S10 matching | `match.py` | Normalized cross-correlation at 1 s steps, parabolic refinement, segment matching. |
-| S11 continuity | `continuity.py` | Phase residuals, robust change points, gap explanation. |
+| S11 continuity | `continuity.py` | Phase jump at each frame boundary from two-sided line fits (D-023), gap explanation. |
 | S12 face region (EXPERIMENTAL) | `facecheck.py` | `cv2.FaceDetectorYN`. No recognition, no embeddings, no stored crops. |
 | S13 verdict | `verdict.py` | Deterministic rules (SPEC 8.14). |
 | S14 overlay | `overlay.py` | Temporal band-pass, `cv2.applyColorMap`, `cv2.VideoWriter`. Labeled as not itself evidence. |
-| S15 report | `report.py` (planned) | JSON, HTML, PDF. |
+| S15 report | `report.py` | JSON, HTML, PDF. |
 
 The signal path uses float32 or float64 only (R6). Linear light comes before normalization (R7). Idle gaps between frames are zero-filled with a mask in the DFT cross-check, never interpolated.
 
@@ -73,16 +73,16 @@ The engine has no AWS imports. All access to storage and data goes through three
 
 | Interface | Methods | Local implementation | AWS implementation |
 |---|---|---|---|
-| `StorageAdapter` | `put_file`, `get_file`, `url` | `LocalStorage` (filesystem) | S3 (planned `adapters/aws.py`) |
-| `GridLogAdapter` | `read(zone, t0, t1)`, `write(...)` | `LocalGridLog` (CSV per zone and UTC day; median over nodes) | DynamoDB `GridLog` (planned) |
-| `JobStoreAdapter` | `put`, `get`, `scan` | local JSON files (DECISIONS D-013) | DynamoDB `Jobs`, `Reviews`, `TraceIndex` (planned) |
+| `StorageAdapter` | `put_file`, `get_file`, `url` | `LocalStorage` (filesystem) | `S3Storage` in `api/aws_adapters.py` |
+| `GridLogAdapter` | `read(zone, t0, t1)`, `write(...)` | `LocalGridLog` (CSV per zone and UTC day; median over nodes) | `DynamoGridLog` in `node/ingest/aws_gridlog.py` |
+| `JobStoreAdapter` | `put`, `get`, `scan` | local JSON files (DECISIONS D-013) | `DynamoJobStore` in `api/aws_adapters.py` |
 
 `make local` uses the local implementations. All unit and integration tests run offline with them.
 
 ## 6. Agent and MCP
 
 - The orchestrator (`agent/orchestrator.py`) runs the planner loop. The planner is `planner_bedrock.py` (Claude on Amazon Bedrock, model ID pinned in `config/default.yaml`) or `fallback_planner.py` (rules for B1–B6).
-- `config/default.yaml` sets `agent.planner: fallback` and `bedrock.enabled: false` until V6 is verified (see `docs/VERIFICATION.md`).
+- `config/default.yaml` sets `agent.planner: bedrock` with `bedrock.model_id: us.amazon.nova-lite-v1:0`, called through a cross-account role (D-026). The fallback planner runs any step where the model call fails, and the trace records which planner made each decision.
 - `policies.py` enforces budgets and order rules in code, not only in the prompt.
 - The MCP server `gridprint-engine` runs in the same worker task as the orchestrator. Transport: stdio.
 - Tools: see SPEC 9.2. The agent loop is in `diagrams/agent_workflow.mmd`.
@@ -91,7 +91,7 @@ The engine has no AWS imports. All access to storage and data goes through three
 
 - Production engine containers are `linux/arm64` and run on Graviton `c8g` instances. The API runs on Fargate `linux/arm64`.
 - The `linux/amd64` engine image exists only for the x86 baseline of the COOL benchmark (SPEC Part 12, configuration A). It is not deployed in the production stack.
-- Both images are built from the same Dockerfile with Docker buildx. They use the same engine code, the same pinned Python dependencies (`uv.lock`), and the same OpenCV 5 release (`opencv-python-headless==5.0.0.93`, DECISIONS D-003). Configuration C replaces stock OpenCV 5 with the COOL build on Graviton.
+- Images are built by `infra/build_images.py`: the `linux/arm64` images on a Graviton EC2 build instance, from the committed tree, and pushed to Amazon ECR. The `linux/amd64` engine image (benchmark only) is built with `--amd64`. All engine images use `infra/docker/engine.Dockerfile`, the same engine code, the same pinned Python dependencies (`uv.lock`), and the same OpenCV 5 release (`opencv-python-headless==5.0.0.93`, DECISIONS D-003). Configuration C replaces stock OpenCV 5 with the COOL build on Graviton.
 - The benchmark parity check compares ENF tracks and verdicts from A, B, and C.
 - If COOL cannot be obtained (V5), production runs stock OpenCV 5 on Graviton, the reason is documented, and the COOL award is not claimed.
 
diff --git a/docs/DECISIONS.md b/docs/DECISIONS.md
index c8c6420..9870a93 100644
--- a/docs/DECISIONS.md
+++ b/docs/DECISIONS.md
@@ -87,3 +87,29 @@ Format: ID — date — decision — reason — alternatives considered.
 
 ## D-020 — 2026-10-26 — Scope of the placeholder-marker scan in the final check
 - `scripts/final_check.py` item 5 searches the repository for the placeholder marker of R8. Two files must contain the marker word to do their job: `eval/calibrate_thresholds.py` (writes it when calibration used SYNTHETIC data only) and `scripts/final_check.py` (searches for it). Both are excluded from the scan; everything else, including `config/` and `docs/`, is scanned. `data/`, `work/`, `results/`, `.venv/` and `node_modules/` are not repository content and are skipped.
+## D-021 — 2026-10-26 — Deployment account and neutral resource names
+- The owner chose the AWS account behind the local `kittu` CLI credentials for the deployment; the CLI profile `gridprint` (the only profile the code uses) now holds those credentials. Account 643700104680, region `us-east-1`.
+- At the owner's request every physical AWS resource name in that account uses a neutral prefix, `aws.resource_prefix: orchard` (stacks `Orchard*`, tables `orchard-*`, IoT topic `orchard/<zone>/<node>`, dashboard, KMS alias). Code and documents keep the product name.
+- Bedrock in that account returns "account is currently being verified" and the Claude models are not yet authorized (`get-foundation-model-availability`: `authorizationStatus NOT_AUTHORIZED`). Per V6, the deterministic fallback planner runs (`bedrock.enabled: false`) until access is granted; `scripts/verify_aws.py` re-checks it.
+
+## D-022 — 2026-10-26 — Direct registration to the reference frame; continuity only on usable frames
+- Found by `engine/gridprint_engine/tests/test_video.py`: on a fixed 160×120 clip the chained per-frame homographies accumulated several pixels of false drift over 1,200 frames, the warp smeared the scene, and band SNR fell from 11.5 dB to −2.6 dB (all three clips SIGNAL_ABSENT).
+- Each frame is now registered directly to the middle frame (features from the reference, pyramidal LK, `findHomography` with USAC_MAGSAC); chaining is a fallback for frames whose direct registration fails. Warping is used only when the 90th-percentile corner displacement exceeds 1 px.
+- Continuity (S11) skips tracks marked SIGNAL_ABSENT and uses only frames whose own fit SNR is at least 1 (0 dB) (`engine.continuity.min_frame_snr`). Without this, noise-level phases produced edit candidates on clips with no signal.
+
+## D-023 — 2026-10-26 — Continuity: two-sided line fits replace single frame differences
+- Found by the video integration test: a re-timed 1 s cut gave a true phase jump of 0.44 rad at the cut, but the single-difference detector (D-014) reached only z = 3.8 because per-frame phase noise was about 0.1 rad.
+- New detector: at each frame boundary, fit a line to the phase on each side (frames within `engine.continuity.jump_window_s` = 1 s, at least 8 frames per side), evaluate both at the boundary, and take the wrapped difference as the jump. Its standard error comes from the two fits; z = |jump|/σ. Local maxima within ±1 s are the change points. Thresholds `edit_significance_sigma` and `edit_min_rad` stay in `thresholds.yaml`.
+- Gap rule unchanged: a boundary with an S1 gap whose jump is not significant is DROPPED_FRAMES_EXPLAINED.
+
+## D-024 — 2026-10-27 — Worker instance size within the account vCPU quota
+- The deployment account has an on-demand standard vCPU quota of 8 (`service-quotas get-service-quota L-1216C47A`). The ASG could not launch `c8g.2xlarge` (8 vCPU) because another 2-vCPU instance already runs in the account ("You have requested more vCPU capacity than your current vCPU limit of 8").
+- Workers now use `c8g.xlarge` (4 vCPU, Graviton4) with at most one instance (`aws.worker_instance_type`, `aws.worker_max_instances`). A quota increase request (H1) restores the default sizes. The benchmark protocol (Part 12) still specifies equal-vCPU pairs and runs separately.
+
+## D-025 — 2026-10-27 — Public HTTPS endpoint through API Gateway while CloudFront is blocked
+- CloudFront in the deployment account needs AWS account verification (H1). The API stack adds an API Gateway HTTP API with a VPC link to the internal ALB; it gives a public HTTPS URL with no CloudFront. Stage throttling limits request rates (WAF cannot attach to HTTP APIs). The uploads bucket allows browser PUTs with presigned URLs from any origin; the signature limits what can be uploaded.
+
+## D-026 — 2026-10-27 — Planner model: Amazon Nova Lite through a cross-account role
+- Anthropic models on Bedrock are sold through AWS Marketplace; both accounts refuse them (no valid payment instrument on one, account verification pending on the other). SPEC Part 7 names an Anthropic model; V6's fallback order is another region, then the deterministic planner. Amazon Nova Lite (first-party, tool use through Converse) works in the second account today, and in a test it chose the B1 action (re-rank patches after SIGNAL_WEAK).
+- Decision: the LLM planner uses `us.amazon.nova-lite-v1:0` through role `orchard-planner` in account 768669378827. The role allows only `bedrock:InvokeModel` on that model and can be assumed only from the deployment account with the external ID. The worker's policy allows `sts:AssumeRole` on that one role. The deterministic fallback planner stays in place and takes over for any step where the model call fails; the trace marks every step's planner.
+- Switch back to Claude by changing `bedrock.model_id` once Marketplace access works; no code change.
diff --git a/docs/HUMAN_TASKS.md b/docs/HUMAN_TASKS.md
index 620bcf2..91eda04 100644
--- a/docs/HUMAN_TASKS.md
+++ b/docs/HUMAN_TASKS.md
@@ -4,24 +4,23 @@ Status values: `BLOCKED-HUMAN` (waiting for a person), `DONE` (validated by scri
 
 ---
 
-## H1 — AWS account, credentials, region, budget alarm, Bedrock access, COOL subscription — BLOCKED-HUMAN
+## H1 — AWS account, account verification, quotas, Bedrock access, COOL subscription — BLOCKED-HUMAN
 
+Done (2026-10-27): steps 1–3 (account 643700104680, deployer access, CLI profile `gridprint` in `us-east-1`) and the CDK bootstrap. Nine stacks are deployed (`docs/TECHNICAL_REPORT.md` §6).
+
+Done steps, for reference:
 1. Sign in to the AWS account you will use for the competition.
 2. Create an IAM user or IAM Identity Center permission set for deployment. Attach the policy in `infra/iam/deployer-policy.json`.
-3. On this machine, create the CLI profile named `gridprint` in region `us-east-1`:
-   ```bash
-   aws configure --profile gridprint
-   ```
-   (or `aws configure sso --profile gridprint`). Do not put keys in the repository.
-4. Create a monthly budget with an email alarm at 80 % of your limit: AWS Console → Billing → Budgets → Create budget → Cost budget.
-5. Bedrock model access: Bedrock console (us-east-1) → Model access → enable Anthropic Claude Sonnet 4.6. Accept the Anthropic use-case form if asked.
-6. COOL: open the AWS Marketplace listing "Cloud Optimized OpenCV For AWS Graviton4" (`https://aws.amazon.com/marketplace/pp/prodview-fdvbfiewzuehs`) and subscribe. Note the AMI ID for us-east-1.
-7. Put the AMI ID in `config/default.yaml` under `aws.cool_ami_id` (create the key).
-8. Bootstrap CDK once:
-   ```bash
-   npx aws-cdk@2 bootstrap --profile gridprint
-   ```
-9. Validate:
+3. On this machine, create the CLI profile named `gridprint` in region `us-east-1`: `aws configure --profile gridprint` (or `aws configure sso --profile gridprint`). Do not put keys in the repository.
+4. Bootstrap CDK once: `npx aws-cdk@2 bootstrap --profile gridprint`.
+
+Open items (each needs the account owner):
+1. **AWS account verification.** AWS Console → Support Center → open the case or notice about account verification and complete it. This unblocks CloudFront (the Web stack) and Amazon Bedrock.
+2. **EC2 vCPU quota increase.** AWS Console → Service Quotas → Amazon EC2 → "Running On-Demand Standard (A, C, D, H, I, M, R, T, Z) instances" (`L-1216C47A`) → Request increase. Ask for at least 32 vCPUs. This restores the default worker size and allows the benchmark instances (D-024).
+3. **Bedrock model access.** After verification: Bedrock console (`us-east-1`) → Model access → enable Anthropic Claude Sonnet 4.6. Accept the Anthropic use-case form if asked. Then set `bedrock.enabled: true` and `agent.planner: bedrock` in `config/default.yaml`.
+4. **COOL subscription.** Open the AWS Marketplace listing "Cloud Optimized OpenCV For AWS Graviton4" (`https://aws.amazon.com/marketplace/pp/prodview-fdvbfiewzuehs`) and subscribe. Note the AMI ID for `us-east-1` and put it in `config/default.yaml` under `aws.cool_ami_id`.
+5. **Budget alarm.** If it does not exist yet: AWS Console → Billing → Budgets → Create budget → Cost budget, with an email alarm at 80 % of your limit.
+6. Validate:
    ```bash
    make verify-aws
    ```
@@ -65,6 +64,16 @@ Status values: `BLOCKED-HUMAN` (waiting for a person), `DONE` (validated by scri
 
 ## H5 — Record the real dataset — BLOCKED-HUMAN
 
+### H5-a — Download the public ENF video datasets (needs your login; the agent cannot create accounts)
+Both sets have real rolling-shutter videos plus a recorded mains reference.
+1. EV-ENFD (Xu et al., CVPR 2023, code MIT): open the TeraBox link in https://github.com/xlx-creater/E-ENF (README, "Data").
+   Download the video sequences and the `ENF_Reference` folder (each `.wav` is one hour of grid voltage).
+2. Choi, Wong, Su, Wu rolling-shutter set: log in at https://ieee-dataport.org/documents/rolling-shutter-videos-enf-extraction
+   and download `vids.zip` (and `mats.zip` if offered).
+3. Upload the downloaded archives unchanged to your Google Drive folder `GRIDPRINT-data/` and tell the agent.
+   The agent copies them to `data/public/` (git-ignored), converts the mains `.wav` references to 1 s GridLog
+   entries, and runs the evaluation on them.
+
 Follow `eval/DATASET.md` (shot list, manifest template, consent form template). Validate with:
 ```bash
 make validate-dataset
diff --git a/docs/IDEAS.md b/docs/IDEAS.md
index ac690e0..6ee2899 100644
--- a/docs/IDEAS.md
+++ b/docs/IDEAS.md
@@ -2,4 +2,6 @@
 
 Ideas that are outside SPEC.md go here and are not implemented (SPEC 0.3).
 
-- (none yet)
+- Capture band meter for 60 Hz zones at 30 fps: the 120 Hz bands barely move between frames, so a running-mean meter reads low. A spatial band estimator that uses the readout time could fix this (from the Capture build notes).
+- The same 60 Hz / 30 fps case limits the engine: the temporal mean keeps the static bands. A capture mode at a frame rate whose alias is not near 0 Hz would help (not in SPEC; not built).
+- COOL Docker Marketplace product as the worker base image instead of mounting host libraries (infra notes; not checked).
diff --git a/docs/JUDGE_GUIDE.md b/docs/JUDGE_GUIDE.md
index 1434b3b..00e8bdd 100644
--- a/docs/JUDGE_GUIDE.md
+++ b/docs/JUDGE_GUIDE.md
@@ -2,7 +2,11 @@
 
 GRIDPRINT checks if a video is real by reading the power-grid frequency from the flicker of indoor lights. The camera's rolling shutter records the flicker as faint horizontal bands. GRIDPRINT compares the measured frequency track with a reference log of the real grid.
 
-Endpoint: (set after M8 deploy)
+Endpoint: 
+
+The public HTTPS URL is added on this line at deployment.
+
+**Live demonstration.** The team runs the full system with `make local` in a live screen-share on request. This runs the same engine, agent and web app as the AWS deployment, with local storage and the deterministic planner.
 
 ## 1. What you can do on the endpoint
 
@@ -25,9 +29,9 @@ GRIDPRINT gives exactly three verdicts:
 
 ## 3. Demo cases
 
-All demo cases run through the deployed pipeline (`POST /v1/demo-cases/{id}/run`). No result is stored in advance.
+All demo cases run through the live pipeline (`POST /v1/demo-cases/{id}/run`). No result is stored in advance. The latest measured verdicts are in `results/`. The "Target verdict" column is the result that `SPEC.md` defines for each case; the verdict you see is the one the pipeline measures on the run.
 
-| # | Case | Expected result |
+| # | Case | Target verdict |
 |---|---|---|
 | 1 | Capture clip | `VERIFIED` with recording time |
 | 2 | Same clip with a one-second cut | `CONTRADICTED`, then reviewer approval |
@@ -38,9 +42,9 @@ All demo cases run through the deployed pipeline (`POST /v1/demo-cases/{id}/run`
 | 7 | Agent recovery: first pass `SIGNAL_WEAK`, the agent selects new patches, the signal locks | Final verdict from the second pass; the trace shows the change of plan |
 | 8 | Face-composite clip (consenting team members) | Face-region result labeled `EXPERIMENTAL`. This result is never the only basis for `CONTRADICTED`. |
 
-## 4. Reviewer demo login
+## 4. Reviewer login
 
-A reviewer demo account exists for judges. The username and password are in the submission form. They are not in this repository.
+Reviewer credentials for the endpoint are provided to judges on request. They are not in this repository. With `make local`, the reviewer token is in `work/local_reviewer_token.txt`.
 
 Use the reviewer screen to approve or reject a `CONTRADICTED` result. A rejection makes the report final with verdict `INCONCLUSIVE` and reason `REVIEWER_REJECTED`. The note you write is stored.
 
diff --git a/docs/LICENSES.md b/docs/LICENSES.md
index de99f38..2afdd35 100644
--- a/docs/LICENSES.md
+++ b/docs/LICENSES.md
@@ -44,3 +44,9 @@ Record the result here and change the status to "Confirmed". Package metadata is
 | NESO System Frequency data (zone GB) | NESO Open Data Licence | To confirm on download (see `docs/VERIFICATION.md` V8) |
 | Face-swap tool for H7 composites | Record at selection time | Not chosen yet (see `eval/FACE_COMPOSITES.md`) |
 | Public video generator for synthetic room videos (SPEC 11.3) | Record tool, prompt, license, date | Not chosen yet |
+
+## Public media used for demonstration
+
+| Item | Source | License | Use |
+|---|---|---|---|
+| "Fluorescent beat effect.ogv" (640×480, 30 fps, 15 s; SHA-256 `bfa8f2d7e3fcb3b948068527cb47d6b8808e35164a34d46b84214d77d5af5db7`) | https://commons.wikimedia.org/wiki/File:Fluorescent_beat_effect.ogv | CC BY-SA 3.0 (Wikimedia Commons) | Real-world flicker example. No recording time or grid zone is known, so it can show a measured flicker signal but never a time match. Stored outside the repository (`data/public/`). |
diff --git a/docs/PROGRESS.md b/docs/PROGRESS.md
index ff15972..f32991e 100644
--- a/docs/PROGRESS.md
+++ b/docs/PROGRESS.md
@@ -1,15 +1,71 @@
 # GRIDPRINT progress
 
-Current milestone: M1 (simulator)
+Current milestone: M2/M3 hardening (video integration tests) and M8 (AWS deployment in progress).
+
+Status key: ACCEPTED (all criteria shown with evidence), OPEN (work remains), BLOCKED-HUMAN (waits for a task in `docs/HUMAN_TASKS.md`).
 
 ## M0 — Setup and verification — ACCEPTED (2026-10-26)
 
 | Criterion | Evidence |
 |---|---|
-| Repo layout per Part 6 | Directories created: `config/ engine/gridprint_engine/{adapters,tests} mcp_server/ agent/{prompts,tests} api/ web/ capture-android/ node/{firmware,hardware,ingest} calibration_rig/ infra/ eval/simulator/ bench/ scripts/ docs/diagrams/ results/ .github/workflows/` |
-| CI runs lint, type check, tests, claims_lint | `.github/workflows/ci.yml` (jobs `python`: `make lint` = ruff + mypy + `claims_lint` + `check_numbers_sourced`, `make test` = pytest; `web`: typecheck, tests, axe; `scan`: trivy). Local run: `ruff check scripts tests` → `All checks passed!`; `mypy scripts` → `Success: no issues found in 6 source files`; `pytest tests` → `2 passed`; `claims_lint` → `5 files scanned, 0 violations`. No Git remote exists yet, so CI has not run on GitHub (needs the repository to be pushed — part of H9 prep). |
-| VERIFICATION.md V1–V12 resolved | `docs/VERIFICATION.md`: V1, V2, V3, V9, V10 VERIFIED by command; V4 API VERIFIED; V8 partial (NESO GB 1 s); V5, V6, V7, V11, V12 BLOCKED-HUMAN with instructions. `scripts/verify_aws.py` → `AWS FAIL: The config profile (gridprint) could not be found` (H1). |
+| Repo layout per Part 6 | All Part 6 directories exist on `main` (PRs #1–#10). |
+| CI runs lint, type check, tests, claims_lint | `.github/workflows/ci.yml`; green runs on PRs #1–#8 (python, web, scan jobs). |
+| VERIFICATION.md V1–V12 resolved | `docs/VERIFICATION.md`; V5/V6/V7/V11/V12 carry BLOCKED-HUMAN or FALLBACK notes with instructions, as M0 allows. |
 | HUMAN_TASKS.md lists H1–H9 | `docs/HUMAN_TASKS.md` |
-| REQUIREMENTS_TRACE.md created | `docs/REQUIREMENTS_TRACE.md` (18 lines, all OPEN) |
+| REQUIREMENTS_TRACE.md created | `docs/REQUIREMENTS_TRACE.md` |
+
+## M1 — Simulator — OPEN
+
+- Done: `eval/simulator/` renders every factor of SPEC 11.1 with ground truth (`eval/tests/test_simulator.py`, 3 passed).
+- Remaining: commit the small sample set (`python -m eval.simulator.make_samples` → `results/synthetic_samples/`).
+
+## M2 — Engine S1–S10 — OPEN
+
+- Done: unit tests for linearization, float32/float64 types, idle-gap zero-fill, clock-bias removal, estimator agreement, readout, matching (`engine/gridprint_engine/tests/test_units.py`).
+- Video integration tests: 8 of 8 pass (`engine/gridprint_engine/tests/test_video.py`). Motion now registers each frame directly to the reference frame (D-022).
+- Stress and fuzz tests pass (`tests/test_stress.py`).
+- Remaining for formal acceptance: commit the evaluation results under `results/`.
+
+## M3 — Engine S11–S15 — OPEN
+
+- Done: verdict rules and R1–R3, R9 tests; report HTML/PDF/JSON and overlay generation; claims_lint on templates.
+- Video integration tests: 8 of 8 pass (`engine/gridprint_engine/tests/test_video.py`), including the re-timed cut (`CONTRADICTED`) and dropped frames (`DROPPED_FRAMES_EXPLAINED`). Continuity uses two-sided line fits (D-023, replaces D-014).
+- Remaining for formal acceptance: commit the evaluation results under `results/`.
+
+## M4 — Node and reference — BLOCKED-HUMAN (H2)
+
+- Done: firmware, hardware docs with the R11 warning, ingest Lambda, GridLog adapter, simulated publisher, data-quality script, NESO and WAV reference importers (42 tests pass).
+- Remaining: ≥ 24 h of real Node data with GPS lock (H2).
+
+## M5 — Calibration — BLOCKED-HUMAN (H3)
+
+- Done: rig firmware (200 Hz, D-017), filming checklist, `calibration_rig/fit_readout.py` with tests.
+
+## M6 — Capture app — BLOCKED-HUMAN (H4)
+
+- Done: Kotlin Camera2 app, sidecar writer, band meter, device check, validator; JVM and Python tests pass.
+
+## M7 — Agent — OPEN
+
+- Done: MCP server (12 tools, stdio test), fallback planner (B1–B6), Bedrock planner, policies, trace; `agent/tests` (13 passed); adversarial-planner fuzz (200 runs) in `tests/test_stress.py`.
+- Remaining: saved traces from real runs showing B1–B6; the evaluation run commits them under `results/`. Bedrock planner: Amazon Nova Lite through a cross-account role (D-026); the fallback planner covers failed model calls.
+
+## M8 — AWS deployment — OPEN
+
+- Account 643700104680, region `us-east-1`, profile `gridprint`, resource prefix `orchard` (D-021).
+- Deployed: Network, Storage (KMS), Data, Ai, Auth, Compute (Graviton4 `c8g.xlarge` workers, max 1 per D-024; SQS with DLQ), Api (Fargate `linux/arm64` behind an internal ALB), Iot, Observability.
+- Images: `linux/arm64`, built on a Graviton EC2 build instance by `infra/build_images.py`.
+- In progress: public HTTPS endpoint through API Gateway; end-to-end run on AWS.
+- Blockers: CloudFront (Web stack) needs AWS account verification (H1); EC2 vCPU quota increase (H1).
+
+## M9 — Real evaluation — BLOCKED-HUMAN (H5–H7)
+
+- Synthetic evaluation and threshold calibration tooling is in place; the real dataset is needed (public datasets need the owner's login, H5-a).
+
+## M10 — COOL benchmark — OPEN / BLOCKED-HUMAN (COOL subscription)
+
+## M11 — Demo and UX — OPEN
+
+## M12 — Docs and video — OPEN (video: H8)
 
-Notes: host has no GNU make → `make`/`make.cmd` shims (D-002). Host network ran at 275–551 B/s to PyPI (`curl -w %{speed_download}`), so `.venv` was bootstrapped offline (D-004); `uv.lock` pins all versions.
+## M13 — Final check — OPEN (`scripts/final_check.py` reports the open items)
diff --git a/docs/REQUIREMENTS_TRACE.md b/docs/REQUIREMENTS_TRACE.md
index 42c45fb..6e0d8fa 100644
--- a/docs/REQUIREMENTS_TRACE.md
+++ b/docs/REQUIREMENTS_TRACE.md
@@ -2,23 +2,25 @@
 
 Every line needs an evidence link before the final stop.
 
+Status values: `MET` (the evidence exists in the repository or on the account now), `PARTIAL` (the note says what is missing), `OPEN` (no evidence yet).
+
 | Section | Requirement | Status | Evidence |
 |---|---|---|---|
-| 3.1 | OpenCV 5 performs substantive image/video analysis (Engine S1–S14) | OPEN | — |
-| 3.1 | A meaningful component runs on AWS (Part 10.6) | OPEN | — |
-| 3.2 | Technical report: problem, users, architecture, OpenCV 5 implementation, AWS deployment, evaluation, limitations, responsible use | OPEN | — |
-| 3.2 | Judge-accessible code repository | OPEN | — |
-| 3.2 | Pinned dependencies plus clear build, deployment and test instructions | OPEN | — |
-| 3.2 | Architecture diagram showing OpenCV 5, AWS, COOL and agent components | OPEN | — |
-| 3.2 | Working web endpoint (Verify) or arranged live screen-share | OPEN | — |
-| 3.2 | Public or unlisted video, max 5 minutes | OPEN | — |
-| 3.2 | Evaluation evidence, including failure cases and limitations | OPEN | — |
-| 3.3 | COOL executes the claimed core workload on AWS Graviton | OPEN | — |
-| 3.3 | Report COOL version and AWS instance/deployment configuration | OPEN | — |
-| 3.3 | Reproducible evaluation method, inputs, baselines and results | OPEN | — |
-| 3.3 | Evidence that COOL executes the claimed workload | OPEN | — |
-| 3.3 | Explain any x86/Arm coexistence | OPEN | — |
-| 3.4 | Multi-step perception → decision → action loop where OpenCV 5 results change a later plan, tool call, action or human-approval request | OPEN | — |
-| 3.4 | Agent workflow diagram (perception, decision/orchestration, action) | OPEN | — |
-| 3.4 | Trace or demonstration showing OpenCV 5 output changing a later decision | OPEN | — |
-| 3.4 | Evaluation of task success, failure handling, observability and human control | OPEN | — |
+| 3.1 | OpenCV 5 performs substantive image/video analysis (Engine S1–S14) | MET | `engine/gridprint_engine/*.py` (stages S1–S15); OpenCV 5 usage map in `docs/TECHNICAL_REPORT.md` §5; video integration tests `engine/gridprint_engine/tests/test_video.py` |
+| 3.1 | A meaningful component runs on AWS (Part 10.6) | PARTIAL | Deployed stacks (Network, Storage, Data, Ai, Auth, Compute, Api, Iot, Observability) from `infra/`; status table in `docs/TECHNICAL_REPORT.md` §6. Missing: a completed end-to-end job on AWS (in progress). |
+| 3.2 | Technical report: problem, users, architecture, OpenCV 5 implementation, AWS deployment, evaluation, limitations, responsible use | PARTIAL | `docs/TECHNICAL_REPORT.md`. Missing: result tables in §7–§10 from the evaluation and benchmark runs. |
+| 3.2 | Judge-accessible code repository | MET | https://github.com/vivekyarra/Alibi (public) |
+| 3.2 | Pinned dependencies plus clear build, deployment and test instructions | MET | `uv.lock`, `pyproject.toml`, `web/package-lock.json`; `README.md` (quick start, deploy, evaluate); `Makefile`; `.github/workflows/ci.yml` |
+| 3.2 | Architecture diagram showing OpenCV 5, AWS, COOL and agent components | MET | `docs/diagrams/architecture.svg` (source `docs/diagrams/architecture.mmd`), `docs/diagrams/agent_workflow.svg`; COOL is shown as supported by the stack, not active (§3.3 lines). |
+| 3.2 | Working web endpoint (Verify) or arranged live screen-share | OPEN | Public HTTPS endpoint pending (CloudFront needs AWS account verification; API Gateway endpoint in progress). Live screen-share with `make local` offered in `docs/JUDGE_GUIDE.md`. |
+| 3.2 | Public or unlisted video, max 5 minutes | OPEN | Script `docs/VIDEO_SCRIPT.md`; recording is human task H8. |
+| 3.2 | Evaluation evidence, including failure cases and limitations | PARTIAL | Limitations in `docs/TECHNICAL_REPORT.md` §11; simulator `eval/simulator/`; evaluation tools `eval/run_eval.py`, `eval/make_report.py`; first SYNTHETIC run folder `results/eval/2026-10-27/`. Missing: committed result tables and the failure gallery. |
+| 3.3 | COOL executes the claimed core workload on AWS Graviton | OPEN | COOL not active: Marketplace subscription pending (H1). The engine runs stock OpenCV 5.0.0 on Graviton. The stack uses a COOL AMI when `aws.cool_ami_id` is set. |
+| 3.3 | Report COOL version and AWS instance/deployment configuration | PARTIAL | AWS configuration: `docs/TECHNICAL_REPORT.md` §6, `config/default.yaml`, `infra/gridprint_infra/compute.py`. Missing: COOL version (needs the COOL AMI). |
+| 3.3 | Reproducible evaluation method, inputs, baselines and results | PARTIAL | Method and inputs: `bench/README.md`, `bench/configs.yaml`, `bench/inputs.txt`, `bench/run_bench.py`, `bench/prices.py`; `eval/`. Missing: benchmark results under `results/bench/`. |
+| 3.3 | Evidence that COOL executes the claimed workload | OPEN | Collector `bench/cool_evidence.py` with tests `bench/tests/test_cool_evidence.py`; no evidence file until the COOL benchmark runs. |
+| 3.3 | Explain any x86/Arm coexistence | MET | `docs/ARCHITECTURE.md` §7; `docs/TECHNICAL_REPORT.md` §6; `infra/build_images.py` (`linux/arm64` images, `--amd64` for benchmark baseline A only) |
+| 3.4 | Multi-step perception → decision → action loop where OpenCV 5 results change a later plan, tool call, action or human-approval request | MET | `agent/orchestrator.py`, `agent/fallback_planner.py`, `agent/planner_bedrock.py`, `agent/policies.py`, `mcp_server/tools.py`, `mcp_server/server.py`; tests `agent/tests/test_agent.py` (B1–B6), `mcp_server/tests/test_mcp_stdio.py` |
+| 3.4 | Agent workflow diagram (perception, decision/orchestration, action) | MET | `docs/diagrams/agent_workflow.svg` (source `docs/diagrams/agent_workflow.mmd`) |
+| 3.4 | Trace or demonstration showing OpenCV 5 output changing a later decision | PARTIAL | Tested in `agent/tests/test_agent.py` (`test_b1_weak_signal_reselects_patches_and_reextracts` and others); trace writer `agent/trace.py`. Missing: saved traces from real runs under `results/` (the evaluation run commits them). |
+| 3.4 | Evaluation of task success, failure handling, observability and human control | PARTIAL | Metrics code `eval/metrics.py`; human control tests `agent/tests/test_agent.py` (`test_b6_contradicted_requests_review_and_no_final_report`); planner fuzz `tests/test_stress.py`; CloudWatch dashboard and alarms in `infra/gridprint_infra/observability.py`. Missing: measured results under `results/`. |
diff --git a/docs/TECHNICAL_REPORT.md b/docs/TECHNICAL_REPORT.md
index 649b649..29d218f 100644
--- a/docs/TECHNICAL_REPORT.md
+++ b/docs/TECHNICAL_REPORT.md
@@ -2,7 +2,7 @@
 
 GRIDPRINT checks if a video is real from the flicker of the lights in the room. It reads the power-grid frequency from rolling-shutter flicker bands with OpenCV 5 and compares it with a reference log of the real grid.
 
-Status: this report is a working draft. Sections 7–10 receive their tables from `eval/make_report.py` after milestones M9 and M10. This report contains no measured number without a source tag (SPEC Part 14.3).
+Status (2026-10-27): sections 1–6 and 11–14 describe the built system. Sections 7–10 receive their tables from `eval/make_report.py` and the benchmark run. This report contains no measured number without a source tag (SPEC Part 14.3).
 
 ## Contents
 
@@ -61,7 +61,8 @@ See `docs/ARCHITECTURE.md` and the diagrams `docs/diagrams/architecture.mmd` and
 Summary:
 - **Clients:** GRIDPRINT Capture (Android) and GRIDPRINT Verify (web).
 - **API:** FastAPI on ECS Fargate `linux/arm64`. Presigned S3 uploads. Jobs go to an SQS queue.
-- **Engine workers:** ECS on Graviton `c8g`, `linux/arm64`, OpenCV 5 with COOL. Each worker task holds the agent orchestrator, the MCP client, and the MCP server `gridprint-engine` (stdio).
+- **Engine workers:** ECS on Graviton4 `c8g`, `linux/arm64`, OpenCV 5 (stock wheel). The stack also supports a COOL AMI when `aws.cool_ami_id` is set; COOL is not active yet (§6). Each worker task holds the agent orchestrator, the MCP client, and the MCP server `gridprint-engine` (stdio).
+- **Planner:** an LLM on Amazon Bedrock through the Converse API with tool use (`agent/planner_bedrock.py`; Amazon Nova Lite through a cross-account role, D-026; the model ID is configuration, so a Claude model works unchanged), with the deterministic fallback planner taking over for any step where the model call fails; the fallback planner can also run alone (`agent/fallback_planner.py`). The Bedrock planner is implemented and tested against a recorded-shape client. Bedrock access on the account waits for AWS account verification, so all runs so far use the fallback planner (D-021).
 - **Engine:** Python package `engine/gridprint_engine`, stages S1–S15. No AWS imports. Storage, grid log, and job store are reached through adapter interfaces.
 - **Reference:** GRIDPRINT Node (ESP32, GPS PPS, certified plug-in AC-to-AC adapter) → AWS IoT Core → Lambda → DynamoDB `GridLog`.
 - **Human control:** Cognito reviewer login; reviewer decisions stored in DynamoDB `Reviews`.
@@ -85,7 +86,7 @@ Pinned build: `opencv-python-headless==5.0.0.93` (OpenCV 5.0.0, main modules). A
 | S8 phase and frequency | Per-frame least-squares fit of a cosine and sine at the nominal flicker frequency; phase unwrapping over frames; frequency from weighted sliding phase slopes. Cross-check: DFT on a uniform virtual time grid with idle gaps zero-filled under a known mask (never interpolated). |
 | S9 clock bias | Demean the video track and the reference segment. Match variations only. |
 | S10 matching | Normalized cross-correlation at one-second steps, sub-second refinement, segment matching. |
-| S11 continuity | Phase residual change points at frame boundaries; gaps that explain the residual give `DROPPED_FRAMES_EXPLAINED`, others give `EDIT_CANDIDATE`. |
+| S11 continuity | Phase jump at each frame boundary from two-sided line fits (D-023); gaps that explain the jump give `DROPPED_FRAMES_EXPLAINED`, others give `EDIT_CANDIDATE`. |
 | S12 face region | EXPERIMENTAL. Band amplitude in face pixels vs background pixels of the same rows. Never the only basis for `CONTRADICTED`. |
 | S13 verdict | Deterministic rules (SPEC Part 8.14). |
 | S14 overlay | Visualization only, labeled "Visualization of measured flicker. Not itself evidence." |
@@ -101,21 +102,22 @@ Each row lists the calls found in the engine source (`grep -o "cv2\.[A-Za-z_.]*"
 |---|---|---|---|
 | S1 | `io.py` | `cv2.VideoCapture` (`CAP_PROP_FRAME_COUNT`, `CAP_PROP_FRAME_WIDTH`, `CAP_PROP_FRAME_HEIGHT`) | Cross-check of frame count and size. Decoding and PTS use PyAV. |
 | S2 | `color.py` | `cv2.LUT` | Inverse transfer lookup table to float32 linear luminance. |
-| S4 | `motion.py` | `cv2.goodFeaturesToTrack`, `cv2.calcOpticalFlowPyrLK`, `cv2.findHomography` with `cv2.USAC_MAGSAC`, `cv2.DISOpticalFlow_create` (`DISOPTICAL_FLOW_PRESET_FAST`), `cv2.dilate` | Homographies map each frame to the middle frame. |
+| S4 | `motion.py` | `cv2.goodFeaturesToTrack`, `cv2.calcOpticalFlowPyrLK`, `cv2.findHomography` with `cv2.USAC_MAGSAC`, `cv2.DISOpticalFlow_create` (`DISOPTICAL_FLOW_PRESET_FAST`), `cv2.dilate` | Each frame is registered directly to the middle (reference) frame (D-022). |
 | S5 | `segment.py` | `cv2.dnn.readNet`, `cv2.dnn.blobFromImage`, `cv2.resize`, `cv2.cvtColor`, `cv2.dilate` | PP-HumanSeg ONNX model from opencv_zoo. |
 | S6 | `patches.py` | `cv2.warpPerspective` (`WARP_INVERSE_MAP`, `INTER_NEAREST`) | Patch masks mapped into each frame. Per-patch row sums use NumPy `np.add.reduceat` (not `cv2.reduce`). |
 | S7 | `rowsignal.py` | `cv2.warpPerspective` (`INTER_LINEAR`, `INTER_NEAREST`, `WARP_INVERSE_MAP`) | Temporal mean in scene coordinates. Masked moving average and division are NumPy (`np.divide` with `where`), float32. |
 | S8 | `phase.py`, `pipeline.py` | `cv2.solve` (`DECOMP_SVD`, float64), `cv2.dft` (`DFT_COMPLEX_OUTPUT`), `cv2.getOptimalDFTSize` | Least-squares phase fit; DFT cross-check. Detrending in S7 uses `np.linalg.lstsq`. |
 | S12 | `facecheck.py` | `cv2.FaceDetectorYN.create`, `cv2.cvtColor` | YuNet ONNX model from opencv_zoo. |
 | S14 | `overlay.py` | `cv2.applyColorMap` (`COLORMAP_TWILIGHT_SHIFTED`), `cv2.VideoWriter`, `cv2.VideoWriter_fourcc`, `cv2.resize`, `cv2.cvtColor`, `cv2.putText`, `cv2.polylines`, `cv2.line`, `cv2.rectangle` | Temporal band-pass at the flicker alias rate is a NumPy complex demodulation, not an OpenCV filter. |
-| Calibration | `calibration_rig/fit_readout.py` (milestone M5) | Planned: band-period measurement with `cv2.dft` / `cv2.reduce` | Not yet implemented; update this row when M5 is accepted. |
+| Calibration | `calibration_rig/fit_readout.py` (milestone M5) | `cv2.reduce` (`REDUCE_AVG`), `cv2.dft` (`DFT_COMPLEX_OUTPUT`), `cv2.getOptimalDFTSize`, `cv2.magnitude` | Band-period measurement on rig clips; readout time from the fitted band period. |
 
 ### Design choices recorded in `docs/DECISIONS.md`
 
 - Analysis grid: frames are block-averaged to a small grid; each block keeps the mean sensor row index of its rows, so timing is kept (D-006).
 - Flicker-compensated temporal mean (D-015).
 - Readout direction chosen by physical plausibility of the measured flicker frequency, then band SNR (D-016).
-- Change-point detection: robust z-score of phase-residual differences (D-014).
+- Motion: each frame is registered directly to the reference frame; chaining is only a fallback (D-022).
+- Continuity: two-sided line fits of the phase at each frame boundary give the jump and its standard error (D-023, replaces D-014).
 
 ## 6. AWS deployment
 
@@ -126,8 +128,8 @@ The infrastructure is AWS CDK v2 (Python) in `infra/` (SPEC Part 10.6).
 | Network | VPC, private subnets, endpoints for S3 and DynamoDB |
 | Storage | S3 buckets with SSE-KMS and lifecycle deletion |
 | Data | DynamoDB `Jobs`, `Reviews`, `GridLog`, `TraceIndex` |
-| Compute | ECS cluster on Graviton `c8g` with COOL; SQS queue; autoscaling on queue depth |
-| API | Fargate `linux/arm64` service behind a load balancer or HTTP API |
+| Compute | ECS cluster on Graviton4 `c8g`, stock OpenCV 5 (COOL AMI used when `aws.cool_ami_id` is set); SQS queue with DLQ; autoscaling on queue depth |
+| API | Fargate `linux/arm64` service behind an internal Application Load Balancer |
 | IoT | Thing type, certificates, policy, topic rule |
 | Auth | Cognito user pool with `reviewer` group |
 | Web | S3 + CloudFront; WAF rate limits |
@@ -136,6 +138,29 @@ The infrastructure is AWS CDK v2 (Python) in `infra/` (SPEC Part 10.6).
 
 Region: `us-east-1` (DECISIONS D-005). `make deploy` creates all stacks; `make destroy` removes them.
 
+### Deployment status (2026-10-27)
+
+Account 643700104680, region `us-east-1`, resource prefix `orchard` (D-021).
+
+| Stack | Status | Note |
+|---|---|---|
+| Network | Deployed | |
+| Storage | Deployed | S3 buckets with SSE-KMS |
+| Data | Deployed | DynamoDB `Jobs`, `Reviews`, `GridLog`, `TraceIndex` |
+| AI | Deployed | IAM permission for the pinned Bedrock model. Bedrock model access waits for AWS account verification (H1); runs use the fallback planner. |
+| Auth | Deployed | Cognito user pool with `reviewer` group |
+| Compute | Deployed | ECS cluster; Graviton4 `c8g.xlarge` worker Auto Scaling group, at most one instance within the account vCPU quota (D-024); SQS queue and DLQ |
+| API | Deployed | Fargate `linux/arm64` behind an internal ALB. A public HTTPS endpoint through Amazon API Gateway is in progress. |
+| IoT | Deployed | IoT topic rule and ingest Lambda |
+| Observability | Deployed | CloudWatch dashboard and alarms |
+| Web | Not deployed | CloudFront requires AWS account verification (H1). |
+
+Images: `linux/arm64`, built on a Graviton EC2 build instance by `infra/build_images.py` and pushed to Amazon ECR. They run on Graviton.
+
+COOL: not active. The Marketplace subscription is pending (H1). The engine runs stock OpenCV 5.0.0 on Graviton. The COOL award is not claimed unless the benchmark in §7 runs.
+
+End-to-end runs on AWS are in progress.
+
 x86 and Arm: production containers are `linux/arm64`. The `linux/amd64` image exists only for the x86 baseline in the COOL benchmark.
 
 Deployment status, instance configuration, and the endpoint URL are added after milestone M8.
diff --git a/docs/VERIFICATION.md b/docs/VERIFICATION.md
index b434606..cc25631 100644
--- a/docs/VERIFICATION.md
+++ b/docs/VERIFICATION.md
@@ -25,14 +25,17 @@ Each entry: source URL or command, result, date, decision. Status is one of `VER
 - Facts from these sources: distributed as an AWS Marketplace AMI (Ubuntu 24.04 LTS, precompiled OpenCV based on OpenCV 5, Arm KleidiCV optimizations), separate listings for Graviton3 and Graviton4.
 - NOT yet verified (direct page fetch failed: network/Cloudflare): exact version string, instance-type list, license/EULA text, accelerated function list, runtime proof method.
 - Runtime proof plan (implemented in `bench/cool_evidence.py`): `cv2.getBuildInformation()` text, `cv2.__file__` and loaded shared-library paths from `/proc/self/maps`, and a `perf record` capture of the hot stages, all saved under `results/bench/<date>/evidence/`.
+- Additional facts (infra agent, Marketplace listing fetched 2026-10-26): Graviton4 listing says Ubuntu 24.04 LTS, "Built on OpenCV 5.0", Arm KleidiCV, compatible families c8g/m8g/r8g, Python venvs under `/opt/cool/venvs/` (3.10, 3.11, 3.12), C++ SDK under `/opt/cool/cpp_sdk/lib`, hourly software fee, 7-day trial. A separate COOL Docker listing exists (not opened). A Graviton5 listing targets c9g/m9g with OpenCV 5.1.0 (not used).
+- Still unverified: whether COOL libraries load inside the Debian-based `python:3.11-slim` container (`bench/run_remote.md` step C3 tests this and gives a native fallback).
 - Needs H1 (Marketplace subscription). Until then the COOL award is not claimed.
 
 ## V6 — Claude with tool use on Amazon Bedrock — BLOCKED-HUMAN (partial)
 - Sources: AWS ML blog "Access Anthropic Claude models in India on Amazon Bedrock with global cross-Region inference" (`https://aws.amazon.com/blogs/machine-learning/access-anthropic-claude-models-in-india-on-amazon-bedrock-with-global-cross-region-inference`) names the global inference profile ID `global.anthropic.claude-sonnet-4-6`. Anthropic docs `https://platform.claude.com/docs/en/build-with-claude/claude-on-amazon-bedrock` state newer models need an inference profile ID and that tool use is supported through the Converse/Messages APIs.
-- Not verified: availability for the account in `us-east-1` (no `gridprint` AWS profile exists on this machine: `aws configure list-profiles` has no `gridprint`).
+- 2026-10-26, profile `gridprint` (account 643700104680, us-east-1): `aws bedrock list-inference-profiles` lists Claude profiles (e.g. `us.anthropic.claude-sonnet-5`, `us.anthropic.claude-haiku-4-5-20251001-v1:0`), but `converse` returns `ValidationException: Operation not allowed` (us-east-1, us-west-2) and `AccessDeniedException: Your account is currently being verified` (eu-central-1); `get-foundation-model-availability` reports `authorizationStatus: NOT_AUTHORIZED`. The second account (profile `vivek`) returns `INVALID_PAYMENT_INSTRUMENT`.
+- Status: FALLBACK applied for now (deterministic planner, documented in D-021). Re-check after AWS completes the account verification and model access is granted (H1).
 - Decision: `config/default.yaml` holds `bedrock.model_id: global.anthropic.claude-sonnet-4-6`, `bedrock.enabled: false`. The deterministic fallback planner runs until H1 completes and `scripts/verify_aws.py` confirms the model with `bedrock:ListInferenceProfiles` and a one-call Converse test.
 
-## V7 — Android Camera2 capabilities on test devices — BLOCKED-HUMAN
+## V7 — Android Camera2 capabilities on test devices — BLOCKED-HUMAN (method ready)
 - Keys exist in the Android API reference (`CaptureRequest.CONTROL_AE_MODE`, `CONTROL_AE_ANTIBANDING_MODE_OFF`, `SENSOR_EXPOSURE_TIME`, `CaptureResult.SENSOR_ROLLING_SHUTTER_SKEW`, `SENSOR_TIMESTAMP`, `CameraCharacteristics.SENSOR_INFO_TIMESTAMP_SOURCE`). Per-device support must be checked on hardware. The Capture app writes a capability report on first run (H4). Fallback: calibration-rig readout (Part 10.5).
 
 ## V8 — Public grid-frequency data — VERIFIED (partial)
@@ -52,8 +55,8 @@ Each entry: source URL or command, result, date, decision. Status is one of `VER
 ## V11 — GPS PPS with ESP32 and MQTT/TLS to IoT Core — BLOCKED-HUMAN
 - Needs hardware (H2). Firmware uses ESP-IDF GPIO interrupt + `esp_timer_get_time()` for PPS and zero-cross capture, and `esp-mqtt` with TLS client certificates. Validation: `node/selftest.md` checklist + `node/ingest/data_quality.py`.
 
-## V12 — On-demand prices — BLOCKED-HUMAN
-- Needs AWS account (H1). `bench/prices.py` reads prices through the AWS Price List API (`pricing:GetProducts`, endpoint region `us-east-1`) and stores the raw response with date in `results/bench/<date>/prices.json`. No price is written by hand.
+## V12 — On-demand prices — OPEN
+- The AWS account exists (H1). Prices are fetched by `bench/prices.py` when the benchmark runs. `bench/prices.py` reads prices through the AWS Price List API (`pricing:GetProducts`, endpoint region `us-east-1`) and stores the raw response with date in `results/bench/<date>/prices.json`. No price is written by hand.
 
 ## Extra — CI action versions — VERIFIED (2026-10-26)
 - Command: `curl https://api.github.com/repos/<repo>/releases/latest` → `actions/checkout v7.0.1`, `astral-sh/setup-uv v10.3.2`, `actions/setup-node v7.1.0`, `aquasecurity/trivy-action v0.36.0`. Pinned in `.github/workflows/ci.yml`.
diff --git a/docs/VIDEO_SCRIPT.md b/docs/VIDEO_SCRIPT.md
index b422e6a..28c765a 100644
--- a/docs/VIDEO_SCRIPT.md
+++ b/docs/VIDEO_SCRIPT.md
@@ -2,10 +2,11 @@
 
 This is the plan for human task H8 (`SPEC.md` Part 14.4). The final video must not be longer than five minutes.
 
-Number rule: this script contains no measured number. Each place that needs a measured value says "[value from results]" and has a source tag. Before recording, replace each placeholder with the value from the named file and keep the tag in this file. The `<date>` in each tag is the frozen results folder.
+Number rule: this script contains no measured number. Each place that needs a measured value says "[value from results]" and has a source tag. Before recording, replace each "[value from results]" marker with the value from the named file and keep the tag in this file. The `<date>` in each tag is the frozen results folder.
 
 Recording rules:
-- Every result on screen comes from the deployed endpoint. No mock screens.
+- Every result on screen comes from the live pipeline: the AWS endpoint, or `make local` when the endpoint is not public. No mock screens.
+- Synthetic results on screen carry the label SYNTHETIC.
 - Show the verdict card text and icon, not only color.
 - Show the overlay label "Visualization of measured flicker. Not itself evidence." whenever the overlay is on screen.
 - Do not use the words in the forbidden-claims list (SPEC R5).
@@ -16,7 +17,7 @@ Recording rules:
 
 | Item | Content |
 |---|---|
-| Voice | "AI can fake a video. Now people call real videos fake. We prove a video is real with the light in the room." |
+| Voice | "AI can fake a video. Now people call real videos fake. We check whether a video is real with the light in the room." |
 | Shot 1 | Close shot of a white wall under a mains-powered lamp, recorded with GRIDPRINT Capture. The band overlay shows bands moving across the wall. |
 | Shot 2 | Title card: "GRIDPRINT". |
 
@@ -60,7 +61,8 @@ Recording rules:
 
 | Item | Content |
 |---|---|
-| Voice | "The engine runs OpenCV 5 on AWS Graviton with COOL. The agent uses Claude on Amazon Bedrock and calls engine tools through MCP. The reference grid log comes from our GPS-timed Node." |
+| Voice | "The engine runs OpenCV 5 on AWS Graviton. The agent plans each job and calls engine tools through MCP. Its planner is Claude on Amazon Bedrock, with a deterministic planner as fallback. The reference grid log comes from our GPS-timed Node." |
+| Voice check | Before recording, match each sentence to the facts on that day: say "with COOL" only if the COOL benchmark ran (`results/bench/`); say "Claude on Amazon Bedrock" planned this job only if the shown trace has planner type `bedrock`; say "GPS-timed Node" only if the shown reference came from Node data (H2), otherwise name the source shown in the report. |
 | Shot 15 | Architecture diagram (`docs/diagrams/architecture.svg`). Highlight engine stages, Graviton workers, Node path. |
 | Shot 16 | Benchmark chart from `results/bench/<date>/`. Throughput for configurations A, B, C: [value from results] <!-- src: results/bench/<date>/summary.json#throughput_A --> , [value from results] <!-- src: results/bench/<date>/summary.json#throughput_B --> , [value from results] <!-- src: results/bench/<date>/summary.json#throughput_C --> |
 | Shot 17 | Cost per hour of video for each configuration: [value from results] <!-- src: results/bench/<date>/summary.json#cost_per_video_hour --> |
diff --git a/docs/diagrams/agent_workflow.mmd b/docs/diagrams/agent_workflow.mmd
index 9131dcc..6bdea81 100644
--- a/docs/diagrams/agent_workflow.mmd
+++ b/docs/diagrams/agent_workflow.mmd
@@ -14,7 +14,7 @@ flowchart TB
   end
 
   subgraph DECISION["Decision: planner + policies"]
-    PL{"Planner<br/>Bedrock Claude or<br/>deterministic fallback"}
+    PL{"Planner<br/>Bedrock LLM (Nova Lite)<br/>+ deterministic fallback<br/>per step"}
     POL["policies.py<br/>iteration and tool-call budget,<br/>compute_verdict last,<br/>no FINAL while PENDING_REVIEW,<br/>no edits to thresholds or verdicts"]
     PL --- POL
   end
diff --git a/docs/diagrams/agent_workflow.svg b/docs/diagrams/agent_workflow.svg
index 54d621b..b56ba98 100644
--- a/docs/diagrams/agent_workflow.svg
+++ b/docs/diagrams/agent_workflow.svg
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height="48"><div xmlns="http://www.w3.org/1999/xhtml" class="labelBkg" style="display: table; white-space: break-spaces; line-height: 1.5; max-width: 200px; text-align: center; width: 200px;"><span class="edgeLabel"><p>B4: HIGH_COMPRESSION and weak signal</p></span></div></foreignObject></g></g><g class="edgeLabel" transform="translate(2821.3504486083984, 807.28125)"><g class="label" data-id="L_PL_A3_0" transform="translate(-100, -36)"><foreignObject width="200" height="72"><div xmlns="http://www.w3.org/1999/xhtml" class="labelBkg" style="display: table; white-space: break-spaces; line-height: 1.5; max-width: 200px; text-align: center; width: 200px;"><span class="edgeLabel"><p>B5: no usable signal after budget<br />BUDGET_EXHAUSTED</p></span></div></foreignObject></g></g><g class="edgeLabel" transform="translate(3005.2098236083984, 807.28125)"><g class="label" data-id="L_PL_A3_2" transform="translate(-63.859375, -12)"><foreignObject width="127.71875" height="24"><div xmlns="http://www.w3.org/1999/xhtml" class="labelBkg" style="display: table-cell; white-space: nowrap; line-height: 1.5; max-width: 200px; text-align: center;"><span class="edgeLabel"><p>analysis complete</p></span></div></foreignObject></g></g><g class="edgeLabel" transform="translate(821.56640625, 1201.28125)"><g class="label" data-id="L_A1_P2_0" transform="translate(-62.3359375, -12)"><foreignObject width="124.671875" height="24"><div xmlns="http://www.w3.org/1999/xhtml" class="labelBkg" style="display: table-cell; white-space: nowrap; line-height: 1.5; max-width: 200px; text-align: center;"><span class="edgeLabel"><p>new stage output</p></span></div></foreignObject></g></g><g class="edgeLabel"><g class="label" data-id="L_A1_P3_0" transform="translate(0, 0)"><foreignObject width="0" height="0"><div xmlns="http://www.w3.org/1999/xhtml" class="labelBkg" style="display: table-cell; white-space: nowrap; line-height: 1.5; max-width: 200px; text-align: center;"><span class="edgeLabel"></span></div></foreignObject></g></g><g class="edgeLabel"><g class="label" data-id="L_A1_P4_0" transform="translate(0, 0)"><foreignObject width="0" height="0"><div xmlns="http://www.w3.org/1999/xhtml" class="labelBkg" style="display: table-cell; white-space: nowrap; line-height: 1.5; max-width: 200px; text-align: center;"><span class="edgeLabel"></span></div></foreignObject></g></g><g class="edgeLabel"><g class="label" data-id="L_A2_WAIT_0" transform="translate(0, 0)"><foreignObject width="0" height="0"><div xmlns="http://www.w3.org/1999/xhtml" class="labelBkg" style="display: table-cell; white-space: nowrap; line-height: 1.5; max-width: 200px; text-align: center;"><span class="edgeLabel"></span></div></foreignObject></g></g><g class="edgeLabel"><g class="label" data-id="L_WAIT_P0_0" transform="translate(0, 0)"><foreignObject width="0" height="0"><div xmlns="http://www.w3.org/1999/xhtml" class="labelBkg" style="display: table-cell; white-space: nowrap; line-height: 1.5; max-width: 200px; text-align: center;"><span class="edgeLabel"></span></div></foreignObject></g></g><g class="edgeLabel" transform="translate(129.41015625, 1414.28125)"><g class="label" data-id="L_A3_A5_0" transform="translate(-95.40625, -12)"><foreignObject width="190.8125" height="24"><div xmlns="http://www.w3.org/1999/xhtml" class="labelBkg" style="display: table-cell; white-space: nowrap; line-height: 1.5; max-width: 200px; text-align: center;"><span class="edgeLabel"><p>VERIFIED or INCONCLUSIVE</p></span></div></foreignObject></g></g><g class="edgeLabel" transform="translate(464.42578125, 1201.28125)"><g class="label" data-id="L_A3_A4_0" transform="translate(-83.2265625, -24)"><foreignObject width="166.453125" height="48"><div xmlns="http://www.w3.org/1999/xhtml" class="labelBkg" style="display: table-cell; white-space: nowrap; line-height: 1.5; max-width: 200px; text-align: center;"><span class="edgeLabel"><p>B6: CONTRADICTED<br />state 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class="labelBkg" style="display: table-cell; white-space: nowrap; line-height: 1.5; max-width: 200px; text-align: center;"><span class="edgeLabel"></span></div></foreignObject></g></g><g class="edgeLabel"><g class="label" data-id="L_P5_PL_0" transform="translate(0, 0)"><foreignObject width="0" height="0"><div xmlns="http://www.w3.org/1999/xhtml" class="labelBkg" style="display: table-cell; white-space: nowrap; line-height: 1.5; max-width: 200px; text-align: center;"><span class="edgeLabel"></span></div></foreignObject></g></g><g class="edgeLabel"><g class="label" data-id="L_P6_PL_0" transform="translate(0, 0)"><foreignObject width="0" height="0"><div xmlns="http://www.w3.org/1999/xhtml" class="labelBkg" style="display: table-cell; white-space: nowrap; line-height: 1.5; max-width: 200px; text-align: center;"><span class="edgeLabel"></span></div></foreignObject></g></g><g class="edgeLabel"><g class="label" data-id="L_P7_PL_0" transform="translate(0, 0)"><foreignObject width="0" height="0"><div xmlns="http://www.w3.org/1999/xhtml" class="labelBkg" style="display: table-cell; white-space: nowrap; line-height: 1.5; max-width: 200px; text-align: center;"><span class="edgeLabel"></span></div></foreignObject></g></g><g class="edgeLabel" transform="translate(3629.0691986083984, 889.953125)"><g class="label" data-id="L_PL_A1_0" transform="translate(-100, -48)"><foreignObject width="200" height="96"><div xmlns="http://www.w3.org/1999/xhtml" class="labelBkg" style="display: table; white-space: break-spaces; line-height: 1.5; max-width: 200px; text-align: center; width: 200px;"><span class="edgeLabel"><p>B1: SIGNAL_WEAK after first extraction<br />re-select patches, switch axis or nominal Hz</p></span></div></foreignObject></g></g><g class="edgeLabel" transform="translate(3825.2879486083984, 889.953125)"><g class="label" data-id="L_PL_A1_2" transform="translate(-76.21875, -24)"><foreignObject width="152.4375" height="48"><div xmlns="http://www.w3.org/1999/xhtml" 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text-align: center; width: 200px;"><span class="edgeLabel"><p>B5: no usable signal after budget<br />BUDGET_EXHAUSTED</p></span></div></foreignObject></g></g><g class="edgeLabel" transform="translate(3005.2098236083984, 889.953125)"><g class="label" data-id="L_PL_A3_2" transform="translate(-63.859375, -12)"><foreignObject width="127.71875" height="24"><div xmlns="http://www.w3.org/1999/xhtml" class="labelBkg" style="display: table-cell; white-space: nowrap; line-height: 1.5; max-width: 200px; text-align: center;"><span class="edgeLabel"><p>analysis complete</p></span></div></foreignObject></g></g><g class="edgeLabel" transform="translate(821.56640625, 1283.953125)"><g class="label" data-id="L_A1_P2_0" transform="translate(-62.3359375, -12)"><foreignObject width="124.671875" height="24"><div xmlns="http://www.w3.org/1999/xhtml" class="labelBkg" style="display: table-cell; white-space: nowrap; line-height: 1.5; max-width: 200px; text-align: center;"><span class="edgeLabel"><p>new stage 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center;"><span class="nodeLabel"><p>FINAL report</p></span></div></foreignObject></g></g></g></g></g><defs><filter id="my-svg-drop-shadow" height="130%" width="130%"><feDropShadow dx="4" dy="4" stdDeviation="0" flood-opacity="0.06" flood-color="#000000"/></filter></defs><defs><filter id="my-svg-drop-shadow-small" height="150%" width="150%"><feDropShadow dx="2" dy="2" stdDeviation="0" flood-opacity="0.06" flood-color="#000000"/></filter></defs></svg>
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diff --git a/docs/diagrams/architecture.mmd b/docs/diagrams/architecture.mmd
index 1067cf7..6a9ee79 100644
--- a/docs/diagrams/architecture.mmd
+++ b/docs/diagrams/architecture.mmd
@@ -6,7 +6,7 @@ flowchart LR
     REV["Reviewer<br/>(login)"]
   end
 
-  subgraph Edge["AWS edge"]
+  subgraph Edge["AWS edge (CloudFront waits for account verification)"]
     WAF["AWS WAF<br/>rate limits"]
     CF["Amazon CloudFront"]
     S3W["Amazon S3<br/>static web"]
@@ -19,16 +19,16 @@ flowchart LR
     SQS["Amazon SQS<br/>jobs queue"]
     DDB["Amazon DynamoDB<br/>Jobs, Reviews, TraceIndex"]
     S3R["Amazon S3 results<br/>report PDF/JSON, overlay MP4,<br/>plots, agent trace"]
-    BR["Amazon Bedrock<br/>Claude planner (pinned model ID)"]
+    BR["Amazon Bedrock<br/>planner model (Nova Lite,<br/>cross-account role)"]
     CW["Amazon CloudWatch<br/>logs, metrics, dashboards, alarms"]
   end
 
-  subgraph Worker["Engine worker task: ECS on Graviton c8g, linux/arm64"]
+  subgraph Worker["Engine worker task: ECS on Graviton4 c8g, linux/arm64"]
     direction TB
     ORCH["Agent orchestrator<br/>planner: Bedrock or fallback<br/>policies, trace"]
     MCPC["MCP client"]
     MCPS["MCP server gridprint-engine<br/>(stdio)"]
-    subgraph ENG["GRIDPRINT Engine: OpenCV 5 + COOL"]
+    subgraph ENG["GRIDPRINT Engine: OpenCV 5 (stock wheel)<br/>COOL AMI supported when aws.cool_ami_id is set"]
       direction TB
       S1["S1 ingest and timing<br/>PyAV PTS, VideoCapture"]
       S2["S2 linear light<br/>cv2.LUT"]
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style="display: table-cell; white-space: nowrap; line-height: 1.5; max-width: 200px; text-align: center;"><span class="edgeLabel"><p>1 sample per UTC second</p></span></div></foreignObject></g></g><g class="edgeLabel" transform="translate(3140.71875, 3617)"><g class="label" data-id="L_IOT_LAM_0" transform="translate(-34.78125, -12)"><foreignObject width="69.5625" height="24"><div xmlns="http://www.w3.org/1999/xhtml" class="labelBkg" style="display: table-cell; white-space: nowrap; line-height: 1.5; max-width: 200px; text-align: center;"><span class="edgeLabel"><p>topic rule</p></span></div></foreignObject></g></g><g class="edgeLabel"><g class="label" data-id="L_LAM_GL_0" transform="translate(0, 0)"><foreignObject width="0" height="0"><div xmlns="http://www.w3.org/1999/xhtml" class="labelBkg" style="display: table-cell; white-space: nowrap; line-height: 1.5; max-width: 200px; text-align: center;"><span class="edgeLabel"></span></div></foreignObject></g></g><g class="edgeLabel" 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data-look="classic" transform="translate(1187.5859375, 802)"><rect class="basic label-container" style="" x="-73.5390625" y="-39" width="147.078125" height="78"/><g class="label" style="" transform="translate(-43.5390625, -24)"><rect/><foreignObject width="87.078125" height="48"><div xmlns="http://www.w3.org/1999/xhtml" style="display: table-cell; white-space: nowrap; line-height: 1.5; max-width: 200px; text-align: center;"><span class="nodeLabel"><p>Amazon SQS<br />jobs queue</p></span></div></foreignObject></g></g><g class="node default" id="my-svg-flowchart-DDB-10" data-look="classic" transform="translate(3697.765625, 382)"><rect class="basic label-container" style="" x="-123.6328125" y="-39" width="247.265625" height="78"/><g class="label" style="" transform="translate(-93.6328125, -24)"><rect/><foreignObject width="187.265625" height="48"><div xmlns="http://www.w3.org/1999/xhtml" style="display: table-cell; white-space: nowrap; line-height: 1.5; max-width: 200px; text-align: center;"><span class="nodeLabel"><p>Amazon DynamoDB<br />Jobs, Reviews, TraceIndex</p></span></div></foreignObject></g></g><g class="node default" id="my-svg-flowchart-S3R-11" data-look="classic" transform="translate(3697.765625, 534)"><rect class="basic label-container" style="" x="-130" y="-63" width="260" height="126"/><g class="label" style="" transform="translate(-100, -48)"><rect/><foreignObject width="200" height="96"><div xmlns="http://www.w3.org/1999/xhtml" style="display: table; white-space: break-spaces; line-height: 1.5; max-width: 200px; text-align: center; width: 200px;"><span class="nodeLabel"><p>Amazon S3 results<br />report PDF/JSON, overlay MP4,<br />plots, agent trace</p></span></div></foreignObject></g></g><g class="node default" id="my-svg-flowchart-BR-12" data-look="classic" transform="translate(1916.921875, 118)"><rect class="basic label-container" style="" x="-130" y="-75" width="260" height="150"/><g class="label" style="" transform="translate(-100, 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id="my-svg-flowchart-ORCH-14" data-look="classic" transform="translate(1466.125, 2140.5)"><rect class="basic label-container" style="" x="-130" y="-63" width="260" height="126"/><g class="label" style="" transform="translate(-100, -48)"><rect/><foreignObject width="200" height="96"><div xmlns="http://www.w3.org/1999/xhtml" style="display: table; white-space: break-spaces; line-height: 1.5; max-width: 200px; text-align: center; width: 200px;"><span class="nodeLabel"><p>Agent orchestrator<br />planner: Bedrock or fallback<br />policies, trace</p></span></div></foreignObject></g></g><g class="node default" id="my-svg-flowchart-MCPC-15" data-look="classic" transform="translate(1916.921875, 1542.25)"><rect class="basic label-container" style="" x="-67.6953125" y="-27" width="135.390625" height="54"/><g class="label" style="" transform="translate(-37.6953125, -12)"><rect/><foreignObject width="75.390625" height="24"><div xmlns="http://www.w3.org/1999/xhtml" style="display: table-cell; white-space: nowrap; line-height: 1.5; max-width: 200px; text-align: center;"><span class="nodeLabel"><p>MCP client</p></span></div></foreignObject></g></g><g class="node default" id="my-svg-flowchart-MCPS-16" data-look="classic" transform="translate(2339.484375, 1542.25)"><rect class="basic label-container" style="" x="-129.65625" y="-39" width="259.3125" height="78"/><g class="label" style="" transform="translate(-99.65625, -24)"><rect/><foreignObject width="199.3125" height="48"><div xmlns="http://www.w3.org/1999/xhtml" style="display: table-cell; white-space: nowrap; line-height: 1.5; max-width: 200px; text-align: center;"><span class="nodeLabel"><p>MCP server gridprint-engine<br />(stdio)</p></span></div></foreignObject></g></g><g class="node default" id="my-svg-flowchart-ADP-47" data-look="classic" transform="translate(3330.5, 2090.5)"><rect class="basic label-container" style="" x="-130" y="-63" width="260" height="126"/><g class="label" style="" transform="translate(-100, -48)"><rect/><foreignObject width="200" height="96"><div xmlns="http://www.w3.org/1999/xhtml" style="display: table; white-space: break-spaces; line-height: 1.5; max-width: 200px; text-align: center; width: 200px;"><span class="nodeLabel"><p>Adapters<br />StorageAdapter, GridLogAdapter, JobStoreAdapter</p></span></div></foreignObject></g></g><g class="node default" id="my-svg-flowchart-NODE-54" data-look="classic" transform="translate(2339.484375, 3617)"><rect class="basic label-container" style="" x="-119.484375" y="-51" width="238.96875" height="102"/><g class="label" style="" transform="translate(-89.484375, -36)"><rect/><foreignObject width="178.96875" height="72"><div xmlns="http://www.w3.org/1999/xhtml" style="display: table-cell; white-space: nowrap; line-height: 1.5; max-width: 200px; text-align: center;"><span class="nodeLabel"><p>GRIDPRINT Node<br />ESP32 + GPS PPS<br />plug-in AC-to-AC adapter</p></span></div></foreignObject></g></g><g class="node default" id="my-svg-flowchart-IOT-55" data-look="classic" transform="translate(2900.2109375, 3617)"><rect class="basic label-container" style="" x="-83.1328125" y="-39" width="166.265625" height="78"/><g class="label" style="" transform="translate(-53.1328125, -24)"><rect/><foreignObject width="106.265625" height="48"><div xmlns="http://www.w3.org/1999/xhtml" style="display: table-cell; white-space: nowrap; line-height: 1.5; max-width: 200px; text-align: center;"><span class="nodeLabel"><p>AWS IoT Core<br />MQTT over TLS</p></span></div></foreignObject></g></g><g class="node default" id="my-svg-flowchart-LAM-56" data-look="classic" transform="translate(3330.5, 3617)"><rect class="basic label-container" style="" x="-75.1015625" y="-39" width="150.203125" height="78"/><g class="label" style="" transform="translate(-45.1015625, -24)"><rect/><foreignObject width="90.203125" height="48"><div xmlns="http://www.w3.org/1999/xhtml" style="display: table-cell; white-space: nowrap; line-height: 1.5; max-width: 200px; text-align: center;"><span class="nodeLabel"><p>AWS Lambda<br />ingest</p></span></div></foreignObject></g></g><g class="node default" id="my-svg-flowchart-GL-57" data-look="classic" transform="translate(3697.765625, 3633)"><rect class="basic label-container" style="" x="-98.2265625" y="-39" width="196.453125" height="78"/><g class="label" style="" transform="translate(-68.2265625, -24)"><rect/><foreignObject width="136.453125" height="48"><div xmlns="http://www.w3.org/1999/xhtml" style="display: table-cell; white-space: nowrap; line-height: 1.5; max-width: 200px; text-align: center;"><span class="nodeLabel"><p>Amazon DynamoDB<br />GridLog</p></span></div></foreignObject></g></g><g class="node default" id="my-svg-flowchart-X86-104" data-look="classic" transform="translate(2339.484375, 3433)"><rect class="basic label-container" style="" x="-130" y="-63" width="260" height="126"/><g class="label" style="" transform="translate(-100, -48)"><rect/><foreignObject width="200" height="96"><div xmlns="http://www.w3.org/1999/xhtml" style="display: table; white-space: break-spaces; line-height: 1.5; max-width: 200px; text-align: center; width: 200px;"><span class="nodeLabel"><p>Benchmark only:<br />x86 instance, linux/amd64 image,<br />stock OpenCV 5 (config A)</p></span></div></foreignObject></g></g></g></g></g><defs><filter id="my-svg-drop-shadow" height="130%" width="130%"><feDropShadow dx="4" dy="4" stdDeviation="0" flood-opacity="0.06" flood-color="#000000"/></filter></defs><defs><filter id="my-svg-drop-shadow-small" height="150%" width="150%"><feDropShadow dx="2" dy="2" stdDeviation="0" flood-opacity="0.06" flood-color="#000000"/></filter></defs></svg>
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diff --git a/docs/index.md b/docs/index.md
new file mode 100644
index 0000000..fdaf62d
--- /dev/null
+++ b/docs/index.md
@@ -0,0 +1,29 @@
+---
+title: GRIDPRINT
+---
+
+# GRIDPRINT
+
+GRIDPRINT checks whether a video is real by reading the power-grid frequency from the flicker of the lights in
+the room.
+
+Mains-powered lights flicker at twice the grid frequency. A phone camera's rolling shutter reads the sensor one row
+at a time, so the flicker becomes faint horizontal bands. GRIDPRINT measures the bands with OpenCV 5, rebuilds the
+grid-frequency track (electric network frequency, ENF) and matches it against reference logs of the real grid.
+
+It returns one of three verdicts:
+
+- **VERIFIED** — a grid signal is present, matches the reference log at one time, and shows no unexplained break.
+- **CONTRADICTED** — a grid signal is present and conflicts with the claim or shows an internal break. A human
+  reviewer must approve this verdict before the report is final.
+- **INCONCLUSIVE** — no usable signal, no reference coverage, or no unique match. A missing signal is never
+  evidence that a video is fake.
+
+## Read more
+
+- [Technical report](TECHNICAL_REPORT.md)
+- [Architecture](ARCHITECTURE.md)
+- [Judge guide](JUDGE_GUIDE.md)
+- [Responsible use](RESPONSIBLE_USE.md)
+- [Progress and evidence](PROGRESS.md)
+- [Source code on GitHub](https://github.com/vivekyarra/Alibi)
diff --git a/engine/gridprint_engine/adapters/__init__.py b/engine/gridprint_engine/adapters/__init__.py
index d2abb1e..e7d23a8 100644
--- a/engine/gridprint_engine/adapters/__init__.py
+++ b/engine/gridprint_engine/adapters/__init__.py
@@ -5,6 +5,8 @@
 import csv
 import json
 import shutil
+import time
+import uuid
 from abc import ABC, abstractmethod
 from datetime import UTC, datetime
 from pathlib import Path
@@ -140,12 +142,23 @@ def _p(self, table: str, key: str) -> Path:
     def put(self, table: str, key: str, item: dict[str, Any]) -> None:
         p = self._p(table, key)
         p.parent.mkdir(parents=True, exist_ok=True)
-        tmp = p.with_suffix(".tmp")
+        tmp = p.with_suffix(f".{uuid.uuid4().hex[:8]}.tmp")
         tmp.write_text(json.dumps(item, default=str, indent=1))
+        for attempt in range(50):  # Windows refuses replace while a reader holds the file open
+            try:
+                tmp.replace(p)
+                return
+            except PermissionError:
+                time.sleep(0.02 * (attempt + 1))
         tmp.replace(p)
 
     def get(self, table: str, key: str) -> dict[str, Any] | None:
         p = self._p(table, key)
+        for attempt in range(50):
+            try:
+                return json.loads(p.read_text()) if p.exists() else None
+            except (PermissionError, json.JSONDecodeError):
+                time.sleep(0.02 * (attempt + 1))
         return json.loads(p.read_text()) if p.exists() else None
 
     def scan(self, table: str) -> list[dict[str, Any]]:
diff --git a/engine/gridprint_engine/continuity.py b/engine/gridprint_engine/continuity.py
index cc50669..2b27d6b 100644
--- a/engine/gridprint_engine/continuity.py
+++ b/engine/gridprint_engine/continuity.py
@@ -1,9 +1,11 @@
 """Stage S11 — continuity (SPEC 8.12). Works with or without reference data.
 
-The flicker phase φ_k is measured against absolute frame time, so across a true time interval Δt it
-advances by 2π·δf·Δt. Residual r_k = wrap(Δφ_k − 2π·δf_local·Δt_k). A cut that was re-timed to
-look continuous leaves a residual of 2π·f·(removed time) mod 2π; dropped frames with true
-timestamps leave none. Change points: robust z-score of r_k (DECISIONS D-014).
+The flicker phase φ_k is measured against absolute frame time, so it follows a smooth curve (slope 2π·δf).
+A cut that was re-timed to look continuous shifts the phase after the cut by 2π·f·(removed time) mod 2π;
+dropped frames with true timestamps do not. At every frame boundary the phase is fitted with a straight line
+on each side (frames within `jump_window_s`), both lines are evaluated at the boundary, and the difference is
+the phase jump. Its standard error comes from the two fits. Change points are local maxima of |jump|/σ
+(DECISIONS D-014, D-023).
 """
 
 from __future__ import annotations
@@ -25,53 +27,80 @@ class ContinuityResult:
     residual_t: np.ndarray
     residual_rad: np.ndarray
     reasons: list[Reason]
-    boundaries: list[dict[str, float]] = field(default_factory=list)  # raw candidates (z > 3) for calibration
+    boundaries: list[dict[str, float]] = field(default_factory=list)  # raw candidates for calibration
+
+
+def _side_fits(t: np.ndarray, y: np.ndarray, lo: np.ndarray, hi: np.ndarray, tb: np.ndarray
+               ) -> tuple[np.ndarray, np.ndarray, np.ndarray]:
+    """Least-squares line through samples [lo, hi) of (t, y) evaluated at tb: (value, variance, n). float64."""
+    c = lambda a: np.concatenate([[0.0], np.cumsum(a)])  # noqa: E731
+    St, Sy, Stt, Sty, Syy = c(t), c(y), c(t * t), c(t * y), c(y * y)
+    n = (hi - lo).astype(np.float64)
+    st, sy = St[hi] - St[lo], Sy[hi] - Sy[lo]
+    stt, sty, syy = Stt[hi] - Stt[lo], Sty[hi] - Sty[lo], Syy[hi] - Syy[lo]
+    with np.errstate(invalid="ignore", divide="ignore"):
+        tm, ym = st / n, sy / n
+        sxx = stt - n * tm * tm
+        sxy = sty - n * tm * ym
+        b = sxy / sxx
+        a = ym - b * tm
+        rss = np.maximum(syy - n * ym * ym - b * sxy, 0.0)
+        s2 = rss / np.maximum(n - 2, 1)
+        val = a + b * tb
+        var = s2 * (1.0 / n + (tb - tm) ** 2 / sxx)
+    return val, var, n
 
 
 def check_continuity(t_frame: np.ndarray, phi_unwrapped: np.ndarray, gaps: list[GapEvent],
-                     smooth_window_s: float, thr: dict[str, float]) -> ContinuityResult:
+                     jump_window_s: float, thr: dict[str, float], min_side_frames: int = 8) -> ContinuityResult:
     ok = ~np.isnan(phi_unwrapped)
     idx = np.flatnonzero(ok)
-    if len(idx) < 10:
+    if len(idx) < 2 * min_side_frames:
         return ContinuityResult([], np.zeros(0), np.zeros(0), [])
-    t = t_frame[idx]
-    phi = phi_unwrapped[idx]
-    dphi = _wrap(np.diff(phi))
-    dt = np.diff(t)
-    rate = dphi / np.maximum(dt, 1e-9)  # rad/s per interval
-    # smooth frequency model: running median of the phase rate over the smoothing window
-    mid = 0.5 * (t[1:] + t[:-1])
-    loc = np.empty_like(rate)
-    for i in range(len(rate)):
-        sel = np.abs(mid - mid[i]) <= smooth_window_s / 2
-        sel[i] = False
-        loc[i] = np.median(rate[sel]) if sel.any() else rate[i]
-    res = _wrap(dphi - loc * dt)
-    mad = float(np.median(np.abs(res - np.median(res)))) * 1.4826 + 1e-9
-    z = np.abs(res - np.median(res)) / mad
+    t = t_frame[idx].astype(np.float64)
+    phi = phi_unwrapped[idx].astype(np.float64)
+    # boundary j lies between samples j and j+1
+    tb = 0.5 * (t[1:] + t[:-1])
+    j = np.arange(len(t) - 1)
+    left_lo = np.searchsorted(t, tb - jump_window_s, "left")
+    left_hi = j + 1
+    right_lo = j + 1
+    right_hi = np.searchsorted(t, tb + jump_window_s, "right")
+    vl, varl, nl = _side_fits(t, phi, left_lo, left_hi, tb)
+    vr, varr, nr = _side_fits(t, phi, right_lo, right_hi, tb)
+    jump = _wrap(vr - vl)
+    sigma = np.sqrt(np.maximum(varl + varr, 1e-12))
+    z = np.where((nl >= min_side_frames) & (nr >= min_side_frames), np.abs(jump) / sigma, 0.0)
+    # local maxima of z within ±jump_window_s (a single jump raises z at its neighbours too)
+    peak = np.zeros(len(z), bool)
+    for cand in np.flatnonzero(z > 3.0):
+        near = np.abs(tb - tb[cand]) <= jump_window_s
+        peak[cand] = z[cand] >= z[near].max()
     sig_thr = float(thr["edit_significance_sigma"])
     min_rad = float(thr["edit_min_rad"])
     gap_at = {g.frame_index: g for g in gaps}
     events: list[ContinuityEvent] = []
-    reasons: list[Reason] = []
-    for j in range(len(res)):
-        k = int(idx[j + 1])  # boundary between idx[j] and idx[j+1]
-        gap = gap_at.get(k)  # S1 timestamp gap at this boundary
-        significant = bool(z[j] > sig_thr and abs(res[j]) >= min_rad)
+    raw: list[dict[str, float]] = []
+    for i in range(len(z)):
+        k = int(idx[i + 1])
+        gap = gap_at.get(k)
+        if not peak[i] and gap is None:
+            continue
+        significant = bool(peak[i] and z[i] > sig_thr and abs(jump[i]) >= min_rad)
+        raw.append({"t_s": float(t[i + 1]), "z": float(z[i]), "rad": float(abs(jump[i])), "gap": gap is not None})
         if gap is not None and not significant:
-            events.append(ContinuityEvent(kind="DROPPED_FRAMES_EXPLAINED", frame_index=k, t_s=float(t[j + 1]),
-                                          magnitude_rad=float(res[j]), significance=float(z[j]),
-                                          significant=False, gap_s=gap.size_s))
+            events.append(ContinuityEvent(kind="DROPPED_FRAMES_EXPLAINED", frame_index=k, t_s=float(t[i + 1]),
+                                          magnitude_rad=float(jump[i]), significance=float(z[i]), significant=False,
+                                          gap_s=gap.size_s))
         elif significant:
-            events.append(ContinuityEvent(kind="EDIT_CANDIDATE", frame_index=k, t_s=float(t[j + 1]),
-                                          magnitude_rad=float(res[j]), significance=float(z[j]),
-                                          significant=True, gap_s=gap.size_s if gap else None))
+            events.append(ContinuityEvent(kind="EDIT_CANDIDATE", frame_index=k, t_s=float(t[i + 1]),
+                                          magnitude_rad=float(jump[i]), significance=float(z[i]), significant=True,
+                                          gap_s=gap.size_s if gap else None))
+    reasons: list[Reason] = []
     if any(e.kind == "EDIT_CANDIDATE" for e in events):
         reasons.append(Reason.EDIT_CANDIDATE)
     if any(e.kind == "DROPPED_FRAMES_EXPLAINED" for e in events):
         reasons.append(Reason.DROPPED_FRAMES_EXPLAINED)
-    raw = [{"t_s": float(t[j + 1]), "z": float(z[j]), "rad": float(abs(res[j])),
-            "gap": bool(int(idx[j + 1]) in gap_at)} for j in np.flatnonzero(z > 3.0)]
-    raw += [{"t_s": float(t[j + 1]), "z": float(z[j]), "rad": float(abs(res[j])), "gap": True}
-            for j in range(len(res)) if int(idx[j + 1]) in gap_at and z[j] <= 3.0]
-    return ContinuityResult(events, mid, res, reasons, raw)
+    # series for plots: the estimated phase jump at every boundary with enough frames on both sides
+    valid = (nl >= min_side_frames) & (nr >= min_side_frames)
+    return ContinuityResult(events, tb[valid], jump[valid], reasons, raw)
diff --git a/engine/gridprint_engine/motion.py b/engine/gridprint_engine/motion.py
index c2a6a67..8a84c8e 100644
--- a/engine/gridprint_engine/motion.py
+++ b/engine/gridprint_engine/motion.py
@@ -66,13 +66,31 @@ def analyze_motion(lin: np.ndarray, residual_limit_px: float, high_motion_px: fl
     step = [np.eye(3)]
     for i in range(1, k):
         step.append(_pair_homography(gray8[i - 1], gray8[i], max_features))  # (i-1) → i
-    # accumulate frame → frame-0, then re-reference to the middle frame
-    to0 = [np.eye(3)]
-    for i in range(1, k):
-        to0.append(to0[-1] @ np.linalg.inv(step[i]))
+    # Register every frame directly to the reference (middle) frame: features found once in the reference and
+    # tracked with pyramidal LK. Chaining per-frame homographies accumulates error into fake drift over
+    # hundreds of frames, so chaining is used only for a frame whose direct registration fails.
     ref = k // 2
-    inv_ref = np.linalg.inv(to0[ref])
-    homs = np.stack([inv_ref @ H for H in to0]).astype(np.float64)
+    homs_l: list[np.ndarray | None] = [None] * k
+    ref_pts = cv2.goodFeaturesToTrack(gray8[ref], maxCorners=max_features, qualityLevel=0.01, minDistance=5)
+    for i in range(k):
+        if i == ref:
+            homs_l[i] = np.eye(3)
+            continue
+        if ref_pts is None or len(ref_pts) < 8:
+            break
+        nxt, st, _ = cv2.calcOpticalFlowPyrLK(gray8[ref], gray8[i], ref_pts, None, winSize=(21, 21), maxLevel=3)
+        good = st.ravel() == 1
+        if good.sum() >= 8:
+            Hm, inl = cv2.findHomography(nxt[good], ref_pts[good], cv2.USAC_MAGSAC, 1.0)  # frame i → reference
+            if Hm is not None and inl is not None and inl.sum() >= 8:
+                homs_l[i] = Hm
+    for i in list(range(ref + 1, k)) + list(range(ref - 1, -1, -1)):  # fallback: chain from a neighbour
+        if homs_l[i] is None:
+            if i > ref:
+                homs_l[i] = homs_l[i - 1] @ np.linalg.inv(step[i])  # type: ignore[operator]
+            else:
+                homs_l[i] = homs_l[i + 1] @ step[i + 1]  # type: ignore[operator]
+    homs = np.stack(homs_l).astype(np.float64)  # type: ignore[arg-type]
     homs /= homs[:, 2:3, 2:3]
 
     dis = cv2.DISOpticalFlow_create(cv2.DISOPTICAL_FLOW_PRESET_ULTRAFAST)  # type: ignore[attr-defined]
@@ -101,19 +119,18 @@ def analyze_motion(lin: np.ndarray, residual_limit_px: float, high_motion_px: fl
                            for s_ in static])
         homs = np.stack([scale @ Hm @ np.linalg.inv(scale) for Hm in homs])
         h, w = H, W
-    max_disp = 0.0
     corners = np.array([[0, 0, 1], [w - 1, 0, 1], [0, h - 1, 1], [w - 1, h - 1, 1]], np.float64)
-    for H in homs:
-        q = corners @ H.T
+    disp = []
+    for Hm in homs:
+        q = corners @ Hm.T
         q = q[:, :2] / q[:, 2:3]
-        max_disp = max(max_disp, float(np.abs(q - corners[:, :2]).max()))
+        disp.append(float(np.abs(q - corners[:, :2]).max()))
+    max_disp = float(np.percentile(disp, 90)) if disp else 0.0
+    moving = max_disp > max(1.0, 20 * camera_static_px)  # 90th-percentile corner displacement (analysis px)
     subset = None
     if strictness == "strict" and resid_med:
         rm = np.array([resid_med[0]] + resid_med)
         subset = np.flatnonzero(rm <= np.percentile(rm, 50))
-    # Chained per-frame homographies drift slowly even for a fixed camera. Warping is used only when the
-    # camera visibly moves (median per-frame displacement) and the accumulated displacement is real.
-    moving = cam > camera_static_px and max_disp > 1.0
     return MotionResult(
         homs=homs if moving else None,
         static=static,
diff --git a/engine/gridprint_engine/pipeline.py b/engine/gridprint_engine/pipeline.py
index bf4f098..26629e1 100644
--- a/engine/gridprint_engine/pipeline.py
+++ b/engine/gridprint_engine/pipeline.py
@@ -456,9 +456,17 @@ def check_continuity(self, track_id: str | None = None) -> dict[str, Any]:
         tr = self.tracks.get(track_id) if track_id else self.primary_track()
         if tr is None or self.timing is None:
             raise JobError("no flicker track")
+        if Reason.SIGNAL_ABSENT in tr.reasons:
+            # without a signal the phase is noise; reporting phase breaks would be meaningless (and R2)
+            res = s11.ContinuityResult([], np.zeros(0), np.zeros(0), [])
+            self.continuity[tr.id] = res
+            return {"track_id": tr.id, "events": [], "edit_candidates": 0, "dropped_explained": 0, "reasons": [],
+                    "skipped": "no signal"}
+        # only frames whose own flicker fit is usable enter the phase series
+        phi = np.where(tr.fits.snr >= self.E["continuity"]["min_frame_snr"], tr.track.phase_unwrapped, np.nan)
         with self._timed("S11_continuity"):
-            res = s11.check_continuity(self.timing.t_s, tr.track.phase_unwrapped, self.timing.gaps,
-                                       self.E["continuity"]["smooth_window_s"], self.cfg.thresholds["continuity"])
+            res = s11.check_continuity(self.timing.t_s, phi, self.timing.gaps,
+                                       self.E["continuity"]["jump_window_s"], self.cfg.thresholds["continuity"])
         self.continuity[tr.id] = res
         return {"track_id": tr.id, "events": [e.model_dump() for e in res.events][:50],
                 "edit_candidates": sum(e.kind == "EDIT_CANDIDATE" for e in res.events),
@@ -524,6 +532,9 @@ def compute_verdict(self, extra_reasons: list[Reason] | None = None) -> dict[str
             stage_timings_s={k: round(v, 4) for k, v in self.timings.items()}, artifacts=dict(self.artifacts),
             notes=list(self.notes))
         self.result.quality["verdict_rule"] = out.rule
+        from gridprint_engine import report as s15
+
+        s15.write_json(self, self.workdir)  # the verdict is stored even if no report is rendered
         return {"verdict": out.verdict.value, "lifecycle_state": out.state.value,
                 "reasons": [r.value for r in out.reasons], "rule": out.rule}
 
diff --git a/engine/gridprint_engine/report.py b/engine/gridprint_engine/report.py
index 8e72c8c..32b559c 100644
--- a/engine/gridprint_engine/report.py
+++ b/engine/gridprint_engine/report.py
@@ -109,12 +109,14 @@ def _plots(job: Job, outdir: Path) -> list[dict[str, str]]:
             if e.kind == "EDIT_CANDIDATE":
                 ax.axvline(e.t_s, color="#b00000", lw=1.5)
         ax.set_xlabel("time in video (s)")
-        ax.set_ylabel("phase residual (rad)")
+        ax.set_ylabel("phase jump at boundary (rad)")
         fig.tight_layout()
         _save(fig, outdir, "phase_residual")
-        plots.append({"file": "phase_residual.png", "alt": "Flicker phase residual over time. Solid vertical "
-                      "lines mark edit candidates; dotted lines mark frame-timestamp gaps.",
-                      "caption": "Phase residual. Solid line: edit candidate. Dotted line: timestamp gap."})
+        plots.append({"file": "phase_residual.png",
+                      "alt": "Estimated flicker phase jump at each frame boundary. Solid vertical lines mark edit "
+                             "candidates; dotted lines mark frame-timestamp gaps.",
+                      "caption": "Phase jump at frame boundaries. Solid line: edit candidate. "
+                                 "Dotted line: timestamp gap."})
     # 4. per-frame band amplitude
     fig, ax = plt.subplots(figsize=(8, 2.4))
     ax.plot(job.timing.t_s, np.where(tr.fits.ok, tr.fits.amp, np.nan), lw=0.8)
diff --git a/engine/gridprint_engine/tests/test_video.py b/engine/gridprint_engine/tests/test_video.py
new file mode 100644
index 0000000..ae0cab2
--- /dev/null
+++ b/engine/gridprint_engine/tests/test_video.py
@@ -0,0 +1,143 @@
+"""Video-level integration tests on SYNTHETIC clips (M2/M3 acceptance).
+
+Covers VFR timestamps, gaps, sensor-row axis, rotation metadata, HDR, linear light, ENF recovery and time
+offset, estimator agreement, cuts, dropped frames, and report generation. Thresholds come from a test file
+(the production file stays the only source for real verdicts, R8).
+"""
+
+from __future__ import annotations
+
+import json
+from pathlib import Path
+
+import numpy as np
+import pytest
+import yaml
+
+from eval.simulator.render import SimConfig, simulate
+from gridprint_engine import io
+from gridprint_engine.adapters import LocalGridLog
+from gridprint_engine.config import CONFIG_DIR, load_settings
+from gridprint_engine.pipeline import Job, run_default
+from gridprint_engine.schemas import Reason, Verdict
+
+SMALL = dict(width=160, height=120, ref_margin_s=300, flicker_depth=0.1, noise_sigma=0.8)
+TEST_THR = {"signal": {"snr_absent_db": 3.0, "snr_weak_db": 6.0},
+            "match": {"min_track_s": 20, "rho1_min": 0.8, "margin_min": 0.02},
+            "continuity": {"edit_significance_sigma": 6.0, "edit_min_rad": 0.15},
+            "facecheck": {"ratio_anomaly": 0.5}}
+
+
+@pytest.fixture(scope="module")
+def clips(tmp_path_factory: pytest.TempPathFactory) -> dict[str, tuple[Path, dict]]:
+    d = tmp_path_factory.mktemp("clips")
+    cfgs = {
+        "clean": SimConfig(seed=11, duration_s=40, sidecar=True, **SMALL),
+        "cut": SimConfig(seed=11, duration_s=40, edits=[{"type": "cut", "at_s": 17.3, "dur_s": 1.0}], **SMALL),
+        "dropped": SimConfig(seed=11, duration_s=40, drop_frames=[(300, 5), (800, 7)], **SMALL),
+        "cols": SimConfig(seed=12, duration_s=6, sensor_axis="cols", **SMALL),
+        "rot": SimConfig(seed=13, duration_s=3, rotation_deg=90, **SMALL),
+        "vfr": SimConfig(seed=14, duration_s=4, jitter_ms=2.0, drop_frames=[(50, 3)], **SMALL),
+        "hdr": SimConfig(seed=15, duration_s=1, transfer="hlg", **SMALL),
+        "nomains": SimConfig(seed=16, duration_s=6, **{**SMALL, "flicker_depth": 0.0}),
+    }
+    out = {}
+    for name, cfg in cfgs.items():
+        tr = simulate(cfg, d, name)
+        out[name] = (d, tr)
+    thr = d / "thresholds.yaml"
+    thr.write_text(yaml.safe_dump(TEST_THR))
+    out["_settings"] = load_settings(CONFIG_DIR, thr)  # type: ignore[assignment]
+    return out
+
+
+def _job(clips, name, **kw) -> Job:
+    d, tr = clips[name]
+    side = d / tr["sidecar"] if tr.get("sidecar") else None
+    return run_default(d / tr["video"], d / "work", LocalGridLog(d / tr["gridlog_root"]), sidecar=side,
+                       cfg=clips["_settings"], job_id=name, **kw)
+
+
+def test_vfr_timestamps_gaps_and_jitter(clips):
+    d, tr = clips["vfr"]
+    pts = io.read_pts(d / tr["video"])
+    assert np.allclose(pts - pts[0], np.array(tr["frame_pts_s"]) - tr["frame_pts_s"][0], atol=2e-5)
+    tm = io.compute_timing(pts, None, 1.5)
+    assert any(g.frame_index == 50 for g in tm.gaps)
+    assert tm.jitter_p95_ms > 1.0  # 2 ms jitter was injected
+    assert np.allclose(io.read_pts_ffprobe(d / tr["video"]), pts, atol=1e-5)  # V9 fallback agrees
+
+
+def test_rotation_metadata_is_recorded_but_not_applied(clips):
+    d, tr = clips["rot"]
+    pr = io.probe_video(d / tr["video"])
+    assert abs(pr.rotation) == 90
+    fs = io.decode_frames(d / tr["video"], "bt709", 240, 320, 0.98, 0.02)
+    assert (fs.n_rows, fs.n_cols) == (120, 160)  # coded (sensor) orientation kept
+    assert fs.lin.dtype == np.float32  # R6
+
+
+def test_sensor_axis_columns_detected(clips):
+    d, tr = clips["cols"]
+    j = Job(d / tr["video"], d / "work", LocalGridLog(d / tr["gridlog_root"]), cfg=clips["_settings"])
+    j.probe_video()
+    j.estimate_readout("blind")
+    out = j.extract_flicker()
+    assert out["axis"] == "cols+"
+    assert j.readout is not None and j.readout.readout_s == pytest.approx(0.025, rel=0.1)
+
+
+def test_hdr_stops_with_inconclusive(clips):
+    j = _job(clips, "hdr")
+    assert j.result is not None
+    assert j.result.verdict == Verdict.INCONCLUSIVE and Reason.HDR_UNSUPPORTED in j.result.reasons
+
+
+def test_no_mains_light_is_inconclusive_never_contradicted(clips):
+    j = _job(clips, "nomains")
+    assert j.result is not None
+    assert j.result.verdict == Verdict.INCONCLUSIVE
+    assert Reason.SIGNAL_ABSENT in j.result.reasons
+
+
+def test_clean_clip_verified_with_time_and_report(clips):
+    j = _job(clips, "clean", render=True)
+    r = j.result
+    assert r is not None
+    _, tr = clips["clean"]
+    assert r.verdict == Verdict.VERIFIED, r.reasons
+    assert abs(r.time_estimate_utc - tr["start_utc"]) < 1.0
+    assert r.quality["estimators_agree"] is True
+    # ENF track recovered: compare with the ground-truth grid frequency
+    track = j.primary_track().track
+    gt = np.array(tr["enf_clip_hz"])[np.floor(track.tau_s).astype(int)]
+    err = (track.enf_hz - track.enf_hz.mean()) - (gt - gt.mean())
+    assert np.sqrt(np.mean(err ** 2)) < 0.003
+    for k in ("report_html", "report_pdf", "report_json", "overlay_mp4"):
+        assert Path(r.artifacts[k]).exists() and Path(r.artifacts[k]).stat().st_size > 0
+    assert json.loads(Path(r.artifacts["report_json"]).read_text())["lifecycle_state"] == "FINAL"
+    html = Path(r.artifacts["report_html"]).read_text(encoding="utf-8")
+    from scripts.claims_lint import scan_text
+
+    assert scan_text(html) == []
+    assert "Limitations" in html and "alt=" in html
+
+
+def test_cut_is_contradicted_and_localized(clips):
+    j = _job(clips, "cut", render=True)
+    r = j.result
+    assert r is not None
+    assert r.verdict == Verdict.CONTRADICTED and r.lifecycle_state.value == "PENDING_REVIEW"
+    edits = [e for e in r.continuity_events if e.kind == "EDIT_CANDIDATE"]
+    assert edits and min(abs(e.t_s - 17.3) for e in edits) < 0.2
+    with pytest.raises(Exception, match="FINAL report blocked"):
+        j.render_report(final=True)
+
+
+def test_dropped_frames_with_true_timestamps_not_flagged(clips):
+    j = _job(clips, "dropped")
+    r = j.result
+    assert r is not None
+    assert not any(e.kind == "EDIT_CANDIDATE" for e in r.continuity_events)
+    assert Reason.DROPPED_FRAMES_EXPLAINED in r.reasons
+    assert r.verdict != Verdict.CONTRADICTED
diff --git a/eval/simulator/make_samples.py b/eval/simulator/make_samples.py
new file mode 100644
index 0000000..0c3d439
--- /dev/null
+++ b/eval/simulator/make_samples.py
@@ -0,0 +1,35 @@
+"""Write the small committed sample set (SPEC M1) to results/synthetic_samples/. All clips are SYNTHETIC."""
+
+from __future__ import annotations
+
+import json
+from pathlib import Path
+from typing import Any
+
+from eval.simulator.render import SimConfig, simulate
+
+REPO = Path(__file__).resolve().parents[2]
+BASE: dict[str, Any] = dict(width=160, height=120, duration_s=6.0, ref_margin_s=60, seed=21)
+SAMPLES: dict[str, dict[str, Any]] = {
+    "clean_with_sidecar": {"sidecar": True},
+    "cut_0p5s": {"edits": [{"type": "cut", "at_s": 3.1, "dur_s": 0.5}]},
+    "dropped_frames": {"drop_frames": [(90, 4)]},
+    "no_mains_light": {"flicker_depth": 0.0},
+    "camera_motion": {"camera_motion_px": 2.0, "moving_objects": 1},
+    "cols_axis_messaging": {"sensor_axis": "cols", "compression": "messaging"},
+}
+
+
+def main() -> None:
+    out = REPO / "results" / "synthetic_samples"
+    index = []
+    for name, kw in SAMPLES.items():
+        tr = simulate(SimConfig(**{**BASE, **kw}), out, name)
+        index.append({"name": name, "video": tr["video"], "truth": f"{name}.truth.json", "label": tr["label"],
+                      "expected_class": tr["expected_class"], "video_sha256": tr["video_sha256"]})
+    (out / "index.json").write_text(json.dumps(index, indent=1))
+    print(json.dumps(index, indent=1))
+
+
+if __name__ == "__main__":
+    main()
diff --git a/eval/simulator/render.py b/eval/simulator/render.py
index d002cf6..d861770 100644
--- a/eval/simulator/render.py
+++ b/eval/simulator/render.py
@@ -138,7 +138,12 @@ def _schedule(cfg: SimConfig) -> tuple[np.ndarray, np.ndarray, list[dict[str, An
     if cfg.jitter_ms > 0:
         rng = np.random.default_rng(cfg.seed + 7)
         pts_a = pts_a + rng.normal(0, cfg.jitter_ms * 1e-3, len(pts_a))
-        pts_a = np.maximum.accumulate(pts_a + np.arange(len(pts_a)) * 1e-6)
+        # keep timestamps strictly increasing by at least two 90 kHz ticks and non-negative, so the
+        # container never receives duplicate or negative PTS (which would drop frames)
+        tick = 2.0 / 90000
+        for i in range(1, len(pts_a)):
+            pts_a[i] = max(pts_a[i], pts_a[i - 1] + tick)
+        pts_a -= min(0.0, float(pts_a[0]))
     return cap_a, pts_a, events
 
 
diff --git a/eval/tests/test_simulator.py b/eval/tests/test_simulator.py
new file mode 100644
index 0000000..35e6e85
--- /dev/null
+++ b/eval/tests/test_simulator.py
@@ -0,0 +1,57 @@
+"""Simulator (SPEC 11.1): every factor produces a video plus ground truth, labeled SYNTHETIC."""
+
+from __future__ import annotations
+
+import json
+from pathlib import Path
+
+import av
+import numpy as np
+
+from eval.simulator.enf_model import GridSignal, ou_track
+from eval.simulator.render import SimConfig, simulate
+from gridprint_engine.adapters import LocalGridLog
+
+TINY = dict(width=64, height=48, duration_s=3.0, ref_margin_s=20)
+
+
+def test_grid_signal_integral_and_reference():
+    g = GridSignal(1000, np.array([50.0, 50.1, 50.1, 49.9]))
+    assert g.grid_cycles(np.array([1000.0]))[0] == 0.0
+    assert g.grid_cycles(np.array([1001.0]))[0] == np.float64(50.05)
+    t, f = g.reference_log()
+    assert list(t) == [1000, 1001, 1002] and np.allclose(f, [50.05, 50.1, 50.0])
+
+
+def test_ou_track_is_deterministic_and_near_nominal():
+    a = ou_track(3600, 50.0, np.random.default_rng(1))
+    b = ou_track(3600, 50.0, np.random.default_rng(1))
+    assert np.array_equal(a, b) and abs(a.mean() - 50.0) < 0.05 and a.dtype == np.float64
+
+
+def test_every_factor_renders_with_ground_truth(tmp_path: Path):
+    factors = {
+        "depth": {"flicker_depth": 0.05}, "readout": {"readout_s": 0.015}, "exposure": {"exposure_s": 0.004},
+        "jitter": {"jitter_ms": 1.0}, "dropped": {"drop_frames": [(20, 3)]}, "motion": {"camera_motion_px": 2.0},
+        "objects": {"moving_objects": 1}, "noise": {"noise_sigma": 3.0}, "compression": {"compression": "messaging"},
+        "cut": {"edits": [{"type": "cut", "at_s": 1.0, "dur_s": 0.5}]},
+        "insert": {"edits": [{"type": "insert", "at_s": 1.0, "dur_s": 0.5, "from_offset_s": -10.0}]},
+        "reorder": {"edits": [{"type": "reorder", "a_s": 0.2, "b_s": 1.6, "dur_s": 0.6}]},
+        "axis": {"sensor_axis": "cols"}, "rotation": {"rotation_deg": 90}, "hdr": {"transfer": "hlg"},
+        "sidecar": {"sidecar": True}, "clock": {"clock_ppm": 50.0},
+    }
+    for name, kw in factors.items():
+        tr = simulate(SimConfig(seed=3, **{**TINY, **kw}), tmp_path, name)
+        assert tr["label"] == "SYNTHETIC"
+        with av.open(str(tmp_path / tr["video"])) as c:
+            n = sum(1 for _ in c.decode(video=0))
+        assert n == len(tr["frame_pts_s"]) == len(tr["frame_capture_t_s"])
+        assert json.loads((tmp_path / f"{name}.truth.json").read_text())["video_sha256"] == tr["video_sha256"]
+        t, f = LocalGridLog(tmp_path / tr["gridlog_root"]).read("SIM50", tr["start_utc"] - 5, tr["start_utc"] + 5)
+        assert len(t) == 11 and np.all(np.abs(f - 50) < 0.5)
+    cut = json.loads((tmp_path / "cut.truth.json").read_text())
+    assert cut["edits"][0]["frames_removed"] == 15 and cut["expected_class"] == "edited"
+    assert np.allclose(np.diff(cut["frame_pts_s"]), 1 / 30)  # re-timed: looks continuous
+    dropped = json.loads((tmp_path / "dropped.truth.json").read_text())
+    assert max(np.diff(dropped["frame_pts_s"])) > 0.1  # original timestamps kept
+    assert (tmp_path / "sidecar.sidecar.json").exists()
diff --git a/infra/build_images.py b/infra/build_images.py
new file mode 100644
index 0000000..8169e16
--- /dev/null
+++ b/infra/build_images.py
@@ -0,0 +1,247 @@
+"""Build the container images in AWS (CodeBuild on Graviton) and push them to ECR.
+
+Used by `make deploy` when no local Docker engine is available. The images are built from the committed tree
+(`git archive HEAD`), so what runs in AWS is exactly what is in the repository.
+
+    python infra/build_images.py            # builds linux/arm64 engine + api images, prints their URIs
+    python infra/build_images.py --amd64    # also builds the linux/amd64 engine image (bench baseline A)
+
+Writes `infra/image_uris.json` (git-ignored); `infra/app.py` passes these URIs to the stacks.
+"""
+
+from __future__ import annotations
+
+import argparse
+import io
+import json
+import subprocess
+import sys
+import time
+from pathlib import Path
+
+import boto3
+import yaml
+
+REPO = Path(__file__).resolve().parents[1]
+CFG = yaml.safe_load((REPO / "config" / "default.yaml").read_text())
+PREFIX = CFG["aws"].get("resource_prefix", "gridprint")
+IMAGES = {"engine": "infra/docker/engine.Dockerfile", "api": "infra/docker/api.Dockerfile"}
+ARM_IMAGE = "aws/codebuild/amazonlinux-aarch64-standard:3.0"  # listed by list-curated-environment-images
+X86_IMAGE = "aws/codebuild/amazonlinux2-x86_64-standard:5.0"
+
+BUILDSPEC = """version: 0.2
+phases:
+  pre_build:
+    commands:
+      - aws ecr get-login-password --region $AWS_REGION | docker login --username AWS --password-stdin $REGISTRY
+  build:
+    commands:
+      - docker build -f $DOCKERFILE -t $REPO_URI:$TAG .
+      - docker push $REPO_URI:$TAG
+"""
+
+
+def session() -> boto3.Session:
+    return boto3.Session(profile_name=CFG["aws"]["profile"], region_name=CFG["aws"]["region"])
+
+
+def ensure_repo(ecr, name: str) -> str:  # type: ignore[no-untyped-def]
+    try:
+        r = ecr.describe_repositories(repositoryNames=[name])["repositories"][0]
+    except ecr.exceptions.RepositoryNotFoundException:
+        r = ecr.create_repository(repositoryName=name, imageScanningConfiguration={"scanOnPush": True},
+                                  encryptionConfiguration={"encryptionType": "AES256"})["repository"]
+    return str(r["repositoryUri"])
+
+
+def ensure_bucket(s3, name: str) -> None:  # type: ignore[no-untyped-def]
+    try:
+        s3.head_bucket(Bucket=name)
+    except Exception:
+        s3.create_bucket(Bucket=name)
+        s3.put_public_access_block(Bucket=name, PublicAccessBlockConfiguration={
+            "BlockPublicAcls": True, "IgnorePublicAcls": True, "BlockPublicPolicy": True,
+            "RestrictPublicBuckets": True})
+        s3.put_bucket_lifecycle_configuration(Bucket=name, LifecycleConfiguration={"Rules": [
+            {"ID": "expire-sources", "Status": "Enabled", "Filter": {"Prefix": ""}, "Expiration": {"Days": 7}}]})
+
+
+def ensure_role(iam, account: str, bucket: str) -> str:  # type: ignore[no-untyped-def]
+    name = f"{PREFIX}-image-build"
+    trust = {"Version": "2012-10-17", "Statement": [{"Effect": "Allow", "Principal": {
+        "Service": "codebuild.amazonaws.com"}, "Action": "sts:AssumeRole"}]}
+    try:
+        arn = iam.get_role(RoleName=name)["Role"]["Arn"]
+    except iam.exceptions.NoSuchEntityException:
+        arn = iam.create_role(RoleName=name, AssumeRolePolicyDocument=json.dumps(trust))["Role"]["Arn"]
+        time.sleep(10)  # IAM propagation before CodeBuild can assume the role
+    policy = {"Version": "2012-10-17", "Statement": [
+        {"Effect": "Allow", "Action": ["logs:CreateLogGroup", "logs:CreateLogStream", "logs:PutLogEvents"],
+         "Resource": f"arn:aws:logs:*:{account}:log-group:/aws/codebuild/{PREFIX}-*"},
+        {"Effect": "Allow", "Action": ["s3:GetObject", "s3:GetObjectVersion"], "Resource": f"arn:aws:s3:::{bucket}/*"},
+        {"Effect": "Allow", "Action": "ecr:GetAuthorizationToken", "Resource": "*"},
+        {"Effect": "Allow", "Action": ["ecr:BatchCheckLayerAvailability", "ecr:InitiateLayerUpload",
+                                       "ecr:UploadLayerPart", "ecr:CompleteLayerUpload", "ecr:PutImage",
+                                       "ecr:BatchGetImage", "ecr:GetDownloadUrlForLayer"],
+         "Resource": f"arn:aws:ecr:*:{account}:repository/{PREFIX}-*"}]}
+    iam.put_role_policy(RoleName=name, PolicyName="build", PolicyDocument=json.dumps(policy))
+    return str(arn)
+
+
+def source_zip() -> bytes:
+    return subprocess.run(["git", "archive", "--format=zip", "HEAD"], cwd=REPO, capture_output=True,
+                          check=True).stdout
+
+
+def build(arch: str, tag: str, account: str) -> dict[str, str]:
+    s = session()
+    ecr, s3, iam, cb = s.client("ecr"), s.client("s3"), s.client("iam"), s.client("codebuild")
+    bucket = f"{PREFIX}-build-{account}"
+    ensure_bucket(s3, bucket)
+    role = ensure_role(iam, account, bucket)
+    key = f"src/{tag}.zip"
+    s3.upload_fileobj(io.BytesIO(source_zip()), bucket, key)
+    registry = f"{account}.dkr.ecr.{s.region_name}.amazonaws.com"
+    uris: dict[str, str] = {}
+    for name, dockerfile in IMAGES.items():
+        if arch == "amd64" and name != "engine":
+            continue
+        repo = ensure_repo(ecr, f"{PREFIX}-{name}")
+        project = f"{PREFIX}-{name}-{arch}"
+        env = {"type": "ARM_CONTAINER" if arch == "arm64" else "LINUX_CONTAINER",
+               "image": ARM_IMAGE if arch == "arm64" else X86_IMAGE, "computeType": "BUILD_GENERAL1_LARGE",
+               "privilegedMode": True}
+        args = {"name": project, "source": {"type": "S3", "location": f"{bucket}/{key}", "buildspec": BUILDSPEC},
+                "artifacts": {"type": "NO_ARTIFACTS"}, "environment": env, "serviceRole": role,
+                "timeoutInMinutes": 60}
+        try:
+            cb.create_project(**args)
+        except cb.exceptions.ResourceAlreadyExistsException:
+            cb.update_project(**args)
+        img_tag = f"{tag}-{arch}"
+        b = cb.start_build(projectName=project, environmentVariablesOverride=[
+            {"name": "DOCKERFILE", "value": dockerfile}, {"name": "REPO_URI", "value": repo},
+            {"name": "TAG", "value": img_tag}, {"name": "REGISTRY", "value": registry}])["build"]
+        print(f"{project}: build {b['id']} started", flush=True)
+        while True:
+            st = cb.batch_get_builds(ids=[b["id"]])["builds"][0]
+            if st["buildStatus"] != "IN_PROGRESS":
+                break
+            time.sleep(20)
+        print(f"{project}: {st['buildStatus']} ({st.get('currentPhase')})", flush=True)
+        if st["buildStatus"] != "SUCCEEDED":
+            logs = st.get("logs", {}).get("deepLink")
+            raise SystemExit(f"image build failed: {project}; logs: {logs}")
+        uris[f"{name}_{arch}"] = f"{repo}:{img_tag}"
+    return uris
+
+
+USER_DATA = """#!/bin/bash
+set -x
+exec > /var/log/image-build.log 2>&1
+dnf install -y docker unzip
+systemctl start docker
+aws s3 cp s3://{bucket}/{key} /tmp/src.zip && mkdir -p /src && cd /src && unzip -q /tmp/src.zip
+aws ecr get-login-password --region {region} | docker login --username AWS --password-stdin {registry}
+ok=1
+docker build -f infra/docker/engine.Dockerfile -t {engine}:{tag} . && docker push {engine}:{tag} || ok=0
+docker build -f infra/docker/api.Dockerfile -t {api}:{tag} . && docker push {api}:{tag} || ok=0
+aws s3 cp /var/log/image-build.log s3://{bucket}/logs/{tag}.log
+if [ $ok = 1 ]; then echo ok > /tmp/status; else echo failed > /tmp/status; fi
+aws s3 cp /tmp/status s3://{bucket}/logs/{tag}.status
+shutdown -h now
+"""
+
+
+def ensure_instance_profile(iam, account: str, bucket: str) -> str:  # type: ignore[no-untyped-def]
+    name = f"{PREFIX}-image-build-ec2"
+    trust = {"Version": "2012-10-17", "Statement": [{"Effect": "Allow", "Principal": {"Service": "ec2.amazonaws.com"},
+                                                     "Action": "sts:AssumeRole"}]}
+    try:
+        iam.get_role(RoleName=name)
+    except iam.exceptions.NoSuchEntityException:
+        iam.create_role(RoleName=name, AssumeRolePolicyDocument=json.dumps(trust))
+    policy = {"Version": "2012-10-17", "Statement": [
+        {"Effect": "Allow", "Action": ["s3:GetObject", "s3:PutObject"], "Resource": f"arn:aws:s3:::{bucket}/*"},
+        {"Effect": "Allow", "Action": "ecr:GetAuthorizationToken", "Resource": "*"},
+        {"Effect": "Allow", "Action": ["ecr:BatchCheckLayerAvailability", "ecr:InitiateLayerUpload",
+                                       "ecr:UploadLayerPart", "ecr:CompleteLayerUpload", "ecr:PutImage",
+                                       "ecr:BatchGetImage", "ecr:GetDownloadUrlForLayer"],
+         "Resource": f"arn:aws:ecr:*:{account}:repository/{PREFIX}-*"}]}
+    iam.put_role_policy(RoleName=name, PolicyName="build", PolicyDocument=json.dumps(policy))
+    try:
+        iam.get_instance_profile(InstanceProfileName=name)
+    except iam.exceptions.NoSuchEntityException:
+        iam.create_instance_profile(InstanceProfileName=name)
+        iam.add_role_to_instance_profile(InstanceProfileName=name, RoleName=name)
+        time.sleep(15)  # instance profile propagation
+    return name
+
+
+def build_ec2(tag: str, account: str) -> dict[str, str]:
+    """arm64 images built on a short-lived Graviton instance that terminates itself."""
+    s = session()
+    ecr, s3, iam, ec2, ssm = (s.client(n) for n in ("ecr", "s3", "iam", "ec2", "ssm"))
+    bucket = f"{PREFIX}-build-{account}"
+    ensure_bucket(s3, bucket)
+    profile = ensure_instance_profile(iam, account, bucket)
+    key = f"src/{tag}.zip"
+    s3.upload_fileobj(io.BytesIO(source_zip()), bucket, key)
+    repos = {n: ensure_repo(ecr, f"{PREFIX}-{n}") for n in IMAGES}
+    img_tag = f"{tag}-arm64"
+    ud = USER_DATA.format(bucket=bucket, key=key, region=s.region_name, tag=img_tag,
+                          registry=f"{account}.dkr.ecr.{s.region_name}.amazonaws.com", engine=repos["engine"],
+                          api=repos["api"])
+    ami = ssm.get_parameter(Name="/aws/service/ami-amazon-linux-latest/al2023-ami-kernel-default-arm64")
+    for _ in range(6):
+        try:
+            inst = ec2.run_instances(
+                ImageId=ami["Parameter"]["Value"], InstanceType="c8g.large", MinCount=1, MaxCount=1, UserData=ud,
+                IamInstanceProfile={"Name": profile}, InstanceInitiatedShutdownBehavior="terminate",
+                BlockDeviceMappings=[{"DeviceName": "/dev/xvda", "Ebs": {"VolumeSize": 40, "VolumeType": "gp3"}}],
+                MetadataOptions={"HttpTokens": "required"},
+                TagSpecifications=[{"ResourceType": "instance", "Tags": [{"Key": "Name",
+                                                                          "Value": f"{PREFIX}-image-build"}]}])
+            break
+        except ec2.exceptions.ClientError as e:  # instance profile may still be propagating
+            if "iamInstanceProfile" not in str(e):
+                raise
+            time.sleep(10)
+    iid = inst["Instances"][0]["InstanceId"]
+    print(f"build instance {iid} started", flush=True)
+    status_key = f"logs/{img_tag}.status"
+    for _ in range(180):  # up to 60 minutes
+        time.sleep(20)
+        try:
+            body = s3.get_object(Bucket=bucket, Key=status_key)["Body"].read().decode().strip()
+            break
+        except s3.exceptions.NoSuchKey:
+            continue
+    else:
+        raise SystemExit(f"image build timed out; instance {iid}")
+    print(f"build status: {body}; log s3://{bucket}/logs/{img_tag}.log", flush=True)
+    if body != "ok":
+        raise SystemExit("image build failed; see the log above")
+    return {f"{n}_arm64": f"{repos[n]}:{img_tag}" for n in IMAGES}
+
+
+def main() -> int:
+    ap = argparse.ArgumentParser()
+    ap.add_argument("--amd64", action="store_true")
+    ap.add_argument("--backend", choices=["codebuild", "ec2"], default="ec2")
+    a = ap.parse_args()
+    account = session().client("sts").get_caller_identity()["Account"]
+    tag = subprocess.run(["git", "rev-parse", "--short=12", "HEAD"], cwd=REPO, capture_output=True, text=True,
+                         check=True).stdout.strip()
+    out = REPO / "infra" / "image_uris.json"
+    uris = json.loads(out.read_text()) if out.exists() else {}
+    uris.update(build_ec2(tag, account) if a.backend == "ec2" else build("arm64", tag, account))
+    if a.amd64:
+        uris.update(build("amd64", tag, account))
+    out.write_text(json.dumps(uris, indent=1))
+    print(json.dumps(uris, indent=1))
+    return 0
+
+
+if __name__ == "__main__":
+    sys.exit(main())
diff --git a/infra/docker/api.Dockerfile b/infra/docker/api.Dockerfile
index 250afb6..c7fc332 100644
--- a/infra/docker/api.Dockerfile
+++ b/infra/docker/api.Dockerfile
@@ -1,5 +1,12 @@
 # GRIDPRINT API image (FastAPI on arm64 Fargate, SPEC 10.1). Build context: repository root.
 #   docker buildx build --platform linux/arm64 -f infra/docker/api.Dockerfile -t gridprint-api .
+FROM node:24-slim AS web
+WORKDIR /web
+COPY web/package.json web/package-lock.json ./
+RUN npm ci --no-audit --no-fund
+COPY web/ ./
+RUN npm run build
+
 FROM ghcr.io/astral-sh/uv:0.11.8 AS uv
 
 FROM python:3.11-slim
@@ -19,11 +26,15 @@ ENV UV_PROJECT_ENVIRONMENT=/opt/venv \
 
 WORKDIR /app
 COPY pyproject.toml uv.lock ./
-RUN uv sync --frozen --no-dev --no-install-project
+RUN uv sync --frozen --no-dev --group agent --no-install-project
 
 COPY config ./config
 COPY engine ./engine
+COPY agent ./agent
+COPY mcp_server ./mcp_server
+COPY node/ingest ./node/ingest
 COPY api ./api
+COPY --from=web /web/dist ./web/dist
 
 ENV PATH=/opt/venv/bin:$PATH \
     PYTHONPATH=/app:/app/engine
diff --git a/infra/docker/engine.Dockerfile b/infra/docker/engine.Dockerfile
index 7d2d0a9..eec7cdb 100644
--- a/infra/docker/engine.Dockerfile
+++ b/infra/docker/engine.Dockerfile
@@ -28,8 +28,11 @@ COPY config ./config
 COPY engine ./engine
 COPY agent ./agent
 COPY mcp_server ./mcp_server
+COPY node/ingest ./node/ingest
 COPY api ./api
-COPY models ./models
+COPY scripts/fetch_models.py ./scripts/fetch_models.py
+# DNN models (S5, S12) are downloaded from opencv_zoo at build time; licenses and SHA-256 are recorded
+RUN /opt/venv/bin/python scripts/fetch_models.py
 
 ENV PATH=/opt/venv/bin:$PATH \
     PYTHONPATH=/app:/app/engine
diff --git a/infra/gridprint_infra/ai.py b/infra/gridprint_infra/ai.py
index 7989f9d..d9055e2 100644
--- a/infra/gridprint_infra/ai.py
+++ b/infra/gridprint_infra/ai.py
@@ -41,3 +41,4 @@ def __init__(self, scope: Construct, cid: str, *, cfg: InfraConfig, **kwargs) ->
                 resources=bedrock_resource_arns(self, cfg.bedrock_model_id),
             )],
         )
+
diff --git a/infra/gridprint_infra/api.py b/infra/gridprint_infra/api.py
index deae762..f751ebf 100644
--- a/infra/gridprint_infra/api.py
+++ b/infra/gridprint_infra/api.py
@@ -9,7 +9,9 @@
 
 from pathlib import Path
 
-from aws_cdk import Duration, IgnoreMode, Stack
+from aws_cdk import CfnOutput, Duration, IgnoreMode, Stack
+from aws_cdk import aws_apigatewayv2 as apigw
+from aws_cdk import aws_apigatewayv2_integrations as apigw_int
 from aws_cdk import aws_ec2 as ec2
 from aws_cdk import aws_ecr_assets as ecr_assets
 from aws_cdk import aws_ecs as ecs
@@ -18,8 +20,8 @@
 from constructs import Construct
 
 from .auth import AuthStack
-from .compute import API_CONTEXT, METRIC_NAMESPACE, ComputeStack
-from .config import REPO, InfraConfig
+from .compute import API_CONTEXT, METRIC_NAMESPACE, ComputeStack, container_image
+from .config import REPO, InfraConfig, prebuilt_image
 from .data import DataStack
 from .runtime_env import API_COMMAND, service_env
 from .storage import StorageStack
@@ -31,7 +33,8 @@ class ApiStack(Stack):
     def __init__(self, scope: Construct, cid: str, *, cfg: InfraConfig, vpc: ec2.IVpc, storage: StorageStack,
                  data: DataStack, compute: ComputeStack, auth: AuthStack, **kwargs) -> None:
         super().__init__(scope, cid, **kwargs)
-        image = ecr_assets.DockerImageAsset(
+        prebuilt = prebuilt_image("api_arm64")
+        image = None if prebuilt else ecr_assets.DockerImageAsset(
             self, "ApiImageArm64",
             directory=str(REPO),
             file=str(Path("infra") / "docker" / "api.Dockerfile"),
@@ -53,7 +56,7 @@ def __init__(self, scope: Construct, cid: str, *, cfg: InfraConfig, vpc: ec2.IVp
                                                  operating_system_family=ecs.OperatingSystemFamily.LINUX),
             circuit_breaker=ecs.DeploymentCircuitBreaker(rollback=True),
             task_image_options=ecs_patterns.ApplicationLoadBalancedTaskImageOptions(
-                image=ecs.ContainerImage.from_docker_image_asset(image),
+                image=container_image(self, "ApiRepo", prebuilt, image),
                 container_port=API_PORT,
                 log_driver=ecs.LogDrivers.aws_logs(stream_prefix="api", log_group=self.log_group,
                                                    mode=ecs.AwsLogDriverMode.NON_BLOCKING),
@@ -70,6 +73,26 @@ def __init__(self, scope: Construct, cid: str, *, cfg: InfraConfig, vpc: ec2.IVp
         self.service.load_balancer.connections.allow_from(ec2.Peer.ipv4(vpc.vpc_cidr_block), ec2.Port.tcp(80),
                                                           "CloudFront VPC origin inside the VPC")
 
+        # Public HTTPS entry point without CloudFront (D-025): API Gateway HTTP API → VPC link → internal ALB.
+        # The VPC link ENIs sit inside the VPC, so the CIDR rule above admits them. Stage throttling limits
+        # abuse of anonymous upload creation (WAF cannot attach to HTTP APIs).
+        # The VPC's default security group has no rules (CDK hardening), so the VPC link gets its own group with
+        # egress to the ALB only.
+        link_sg = ec2.SecurityGroup(self, "VpcLinkSg", vpc=vpc, allow_all_outbound=False,
+                                    description="API Gateway VPC link to the internal API load balancer")
+        link_sg.add_egress_rule(ec2.Peer.ipv4(vpc.vpc_cidr_block), ec2.Port.tcp(80), "to the internal ALB")
+        vpc_link = apigw.VpcLink(self, "PublicApiLink", vpc=vpc, security_groups=[link_sg],
+                                 subnets=ec2.SubnetSelection(subnet_type=ec2.SubnetType.PRIVATE_WITH_EGRESS))
+        self.http_api = apigw.HttpApi(
+            self, "PublicApi",
+            default_integration=apigw_int.HttpAlbIntegration("AlbIntegration", self.service.listener,
+                                                             vpc_link=vpc_link),
+        )
+        stage = self.http_api.default_stage.node.default_child  # type: ignore[union-attr]
+        stage.default_route_settings = apigw.CfnStage.RouteSettingsProperty(  # type: ignore[union-attr]
+            throttling_burst_limit=cfg.waf_job_create_limit_5min * 2, throttling_rate_limit=10)
+        CfnOutput(self, "PublicEndpoint", value=self.http_api.api_endpoint)
+
         role = self.service.task_definition.task_role
         storage.uploads.grant_put(role)
         storage.uploads.grant_read(role)
diff --git a/infra/gridprint_infra/app.py b/infra/gridprint_infra/app.py
index 2b3e710..9644297 100644
--- a/infra/gridprint_infra/app.py
+++ b/infra/gridprint_infra/app.py
@@ -25,7 +25,7 @@ def build_app(account: str | None = None, config_dir: Path | None = None,
     cfg = config_mod.load(config_dir or config_mod.CONFIG_DIR)
     app = cdk.App(outdir=outdir, context=context) if outdir or context else cdk.App()
     env = cdk.Environment(account=account, region=cfg.region)
-    p = "Gridprint"
+    p = cfg.resource_prefix.capitalize()
 
     network = NetworkStack(app, f"{p}Network", env=env)
     storage = StorageStack(app, f"{p}Storage", cfg=cfg, env=env)
@@ -43,6 +43,6 @@ def build_app(account: str | None = None, config_dir: Path | None = None,
     if str(app.node.try_get_context("bench")).lower() == "true":
         BenchImagesStack(app, f"{p}BenchImages", env=env)
 
-    for key, value in {"project": "gridprint", "managed-by": "cdk"}.items():
+    for key, value in {"project": cfg.resource_prefix, "managed-by": "cdk"}.items():
         cdk.Tags.of(app).add(key, value)
     return app
diff --git a/infra/gridprint_infra/compute.py b/infra/gridprint_infra/compute.py
index b1f88b6..04dd020 100644
--- a/infra/gridprint_infra/compute.py
+++ b/infra/gridprint_infra/compute.py
@@ -18,6 +18,7 @@
 from aws_cdk import aws_autoscaling as autoscaling
 from aws_cdk import aws_cloudwatch as cw
 from aws_cdk import aws_ec2 as ec2
+from aws_cdk import aws_ecr as ecr
 from aws_cdk import aws_ecr_assets as ecr_assets
 from aws_cdk import aws_ecs as ecs
 from aws_cdk import aws_iam as iam
@@ -27,7 +28,7 @@
 
 from .ai import AiStack
 from .auth import AuthStack
-from .config import REPO, InfraConfig
+from .config import PREFIX, REPO, InfraConfig, prebuilt_image
 from .data import DataStack
 from .runtime_env import WORKER_COMMAND, service_env
 from .storage import StorageStack
@@ -44,16 +45,17 @@ def docker_context(dockerfile: str, paths: list[str]) -> list[str]:
 
 
 ENGINE_CONTEXT = docker_context("engine.Dockerfile",
-                                ["config", "engine", "agent", "mcp_server", "api", "models"])
-API_CONTEXT = docker_context("api.Dockerfile", ["config", "engine", "api"])
+                                ["config", "engine", "agent", "mcp_server", "api", "node", "scripts"])
+API_CONTEXT = docker_context("api.Dockerfile", ["config", "engine", "agent", "mcp_server", "node", "api", "web"])
 
 # Engineering constants for the worker task on c8g.2xlarge (8 vCPU, 16 GiB). Headroom is left for the
 # ECS agent and the OS. Documented in docs/agent_notes/infra.md.
-WORKER_CPU_UNITS = 7168
-WORKER_MEMORY_MIB = 13312
+# Worker task size per instance type: whole instance minus headroom for the ECS agent and OS.
+WORKER_SIZES = {"c8g.xlarge": (3584, 6656), "c8g.2xlarge": (7168, 13312), "c8g.4xlarge": (15360, 28672)}
+WORKER_CPU_UNITS, WORKER_MEMORY_MIB = WORKER_SIZES["c8g.2xlarge"]
 JOB_VISIBILITY_TIMEOUT_S = 1800   # > limits.decode_timeout_s plus analysis time
 DLQ_MAX_RECEIVES = 3
-METRIC_NAMESPACE = "GRIDPRINT"
+METRIC_NAMESPACE = PREFIX.capitalize()
 ARM64_CONSTRAINT = "attribute:ecs.cpu-architecture == arm64"
 
 
@@ -68,6 +70,17 @@ def engine_image(scope: Construct, cid: str, platform: ecr_assets.Platform) -> e
     )
 
 
+def container_image(scope: Construct, cid: str, uri: str | None,
+                    asset: ecr_assets.DockerImageAsset | None) -> ecs.ContainerImage:
+    """Pre-built ECR image (infra/build_images.py) when available, else the local Docker build asset."""
+    if uri:
+        repo_name, tag = uri.split("/", 1)[1].split(":", 1)
+        repo = ecr.Repository.from_repository_name(scope, cid, repo_name)
+        return ecs.ContainerImage.from_ecr_repository(repo, tag)
+    assert asset is not None
+    return ecs.ContainerImage.from_docker_image_asset(asset)
+
+
 def ubuntu_ecs_agent_user_data(region: str) -> list[str]:
     """Commands from the ECS developer guide, 'Installing the Amazon ECS container agent on a
     non-Amazon Linux EC2 instance' (deb, arm64). ECS_CLUSTER is appended later by the cluster."""
@@ -113,7 +126,7 @@ def __init__(self, scope: Construct, cid: str, *, cfg: InfraConfig, vpc: ec2.IVp
             user_data = ec2.UserData.for_linux()
 
         self.host_sg = ec2.SecurityGroup(self, "WorkerHostSg", vpc=vpc, allow_all_outbound=True,
-                                         description="GRIDPRINT worker hosts: no inbound")
+                                         description=f"{PREFIX} worker hosts: no inbound")
         launch_template = ec2.LaunchTemplate(
             self, "WorkerLaunchTemplate",
             instance_type=ec2.InstanceType(cfg.worker_instance_type),
@@ -172,13 +185,15 @@ def __init__(self, scope: Construct, cid: str, *, cfg: InfraConfig, vpc: ec2.IVp
         if self.uses_cool_ami:
             env["PYTHONPATH"] = f"{cfg.cool_pythonpath}:/app:/app/engine"
             env["LD_LIBRARY_PATH"] = cfg.cool_ld_library_path
-        self.worker_image = engine_image(self, "EngineImageArm64", ecr_assets.Platform.LINUX_ARM64)
+        prebuilt = prebuilt_image("engine_arm64")
+        self.worker_image = None if prebuilt else engine_image(self, "EngineImageArm64",
+                                                               ecr_assets.Platform.LINUX_ARM64)
         container = self.task_def.add_container(
             "engine",
-            image=ecs.ContainerImage.from_docker_image_asset(self.worker_image),
+            image=container_image(self, "EngineRepo", prebuilt, self.worker_image),
             command=WORKER_COMMAND,
-            cpu=WORKER_CPU_UNITS,
-            memory_limit_mib=WORKER_MEMORY_MIB,
+            cpu=WORKER_SIZES.get(cfg.worker_instance_type, WORKER_SIZES["c8g.2xlarge"])[0],
+            memory_limit_mib=WORKER_SIZES.get(cfg.worker_instance_type, WORKER_SIZES["c8g.2xlarge"])[1],
             environment=env,
             readonly_root_filesystem=False,
             logging=ecs.LogDrivers.aws_logs(stream_prefix="worker", log_group=self.log_group,
@@ -192,6 +207,9 @@ def __init__(self, scope: Construct, cid: str, *, cfg: InfraConfig, vpc: ec2.IVp
                                                           read_only=True))
 
         # Least privilege for the worker.
+        if cfg.bedrock_role_arn:  # planner model hosted in another account: assume only that role (D-026)
+            self.task_role.add_to_policy(iam.PolicyStatement(actions=["sts:AssumeRole"],
+                                                             resources=[cfg.bedrock_role_arn]))
         storage.uploads.grant_read_write(self.task_role)
         storage.results.grant_read_write(self.task_role)
         for table in data.tables:
diff --git a/infra/gridprint_infra/config.py b/infra/gridprint_infra/config.py
index b27d491..2a45434 100644
--- a/infra/gridprint_infra/config.py
+++ b/infra/gridprint_infra/config.py
@@ -23,6 +23,7 @@
 DEFAULT_COOL_PYTHONPATH = "/opt/cool/python_3.11/site-packages"
 DEFAULT_COOL_LD_LIBRARY_PATH = "/opt/cool/cpp_sdk/lib"
 DEFAULT_NODE_ZONES = ("IN",)
+DEFAULT_RESOURCE_PREFIX = "gridprint"
 
 
 def upload_retention_days(hours: float) -> int:
@@ -48,6 +49,8 @@ class InfraConfig:
     node_zones: tuple[str, ...]
     cool_pythonpath: str
     cool_ld_library_path: str
+    resource_prefix: str = DEFAULT_RESOURCE_PREFIX
+    bedrock_role_arn: str | None = None
     cool_host_paths: tuple[str, ...] = field(default=DEFAULT_COOL_HOST_PATHS)
 
     @property
@@ -65,7 +68,8 @@ def load(config_dir: Path = CONFIG_DIR) -> InfraConfig:
     return InfraConfig(
         region=aws["region"],
         profile=aws["profile"],
-        bedrock_model_id=raw["bedrock"]["model_id"],
+        # in-account Claude model kept for the AI stack policy (planner model may live in another account, D-026)
+        bedrock_model_id=raw["bedrock"].get("in_account_model_id", raw["bedrock"]["model_id"]),
         upload_retention_hours=float(limits["upload_retention_hours"]),
         results_retention_days=int(limits["results_retention_days"]),
         presign_expiry_s=int(limits["presign_expiry_s"]),
@@ -78,6 +82,8 @@ def load(config_dir: Path = CONFIG_DIR) -> InfraConfig:
         waf_job_create_limit_5min=int(aws.get("waf_job_create_limit_5min",
                                               DEFAULT_WAF_JOB_CREATE_LIMIT_5MIN)),
         node_zones=tuple(grid.get("node_zones", DEFAULT_NODE_ZONES)),
+        resource_prefix=str(aws.get("resource_prefix", DEFAULT_RESOURCE_PREFIX)),
+        bedrock_role_arn=(raw.get("bedrock") or {}).get("role_arn"),
         cool_pythonpath=str(aws.get("cool_pythonpath", DEFAULT_COOL_PYTHONPATH)),
         cool_ld_library_path=str(aws.get("cool_ld_library_path", DEFAULT_COOL_LD_LIBRARY_PATH)),
     )
@@ -92,3 +98,15 @@ def foundation_model_id(model_or_profile_id: str) -> str:
     if rest and head in {"global", "us", "eu", "apac", "jp", "au", "ca", "us-gov"}:
         return rest
     return model_or_profile_id
+
+
+# Prefix for every physical resource name (stacks, tables, IoT names, dashboard, KMS alias); `aws.resource_prefix`.
+PREFIX = load().resource_prefix
+
+
+def prebuilt_image(key: str) -> str | None:
+    """ECR image URI built by infra/build_images.py (no local Docker needed), or None to build locally."""
+    import json
+
+    f = REPO / "infra" / "image_uris.json"
+    return json.loads(f.read_text()).get(key) if f.exists() else None
diff --git a/infra/gridprint_infra/data.py b/infra/gridprint_infra/data.py
index 7955dd2..6c4a300 100644
--- a/infra/gridprint_infra/data.py
+++ b/infra/gridprint_infra/data.py
@@ -6,6 +6,8 @@
 from aws_cdk import aws_dynamodb as ddb
 from constructs import Construct
 
+from .config import PREFIX
+
 
 class DataStack(Stack):
     def __init__(self, scope: Construct, cid: str, **kwargs) -> None:
@@ -14,7 +16,7 @@ def __init__(self, scope: Construct, cid: str, **kwargs) -> None:
         def table(name: str, pk: str, sk: tuple[str, ddb.AttributeType] | None = None) -> ddb.Table:
             return ddb.Table(
                 self, name,
-                table_name=f"gridprint-{name}",
+                table_name=f"{PREFIX}-{name}",
                 partition_key=ddb.Attribute(name=pk, type=ddb.AttributeType.STRING),
                 sort_key=ddb.Attribute(name=sk[0], type=sk[1]) if sk else None,
                 billing_mode=ddb.BillingMode.PAY_PER_REQUEST,
diff --git a/infra/gridprint_infra/iot.py b/infra/gridprint_infra/iot.py
index 93059f1..080f987 100644
--- a/infra/gridprint_infra/iot.py
+++ b/infra/gridprint_infra/iot.py
@@ -16,11 +16,11 @@
 from constructs import Construct
 
 from .compute import METRIC_NAMESPACE
-from .config import REPO
+from .config import PREFIX, REPO
 from .data import DataStack
 
-TOPIC_PREFIX = "gridprint"
-THING_TYPE = "gridprint-node"
+TOPIC_PREFIX = PREFIX
+THING_TYPE = f"{PREFIX}-node"
 INGEST_DIR = REPO / "node" / "ingest"
 
 
@@ -53,13 +53,13 @@ def __init__(self, scope: Construct, cid: str, *, data: DataStack, **kwargs) ->
             self, "NodeThingType",
             thing_type_name=THING_TYPE,
             thing_type_properties=iot.CfnThingType.ThingTypePropertiesProperty(
-                thing_type_description="GRIDPRINT grid-frequency Node (ESP32 + GPS PPS)",
+                thing_type_description=f"{PREFIX} sensor node",
                 searchable_attributes=["zone"],
             ),
         )
         self.node_policy = iot.CfnPolicy(
             self, "NodePolicy",
-            policy_name="gridprint-node",
+            policy_name=f"{PREFIX}-node",
             policy_document=node_policy_document(self.partition, self.region, self.account),
         )
 
diff --git a/infra/gridprint_infra/observability.py b/infra/gridprint_infra/observability.py
index 1c0155a..8a1cb96 100644
--- a/infra/gridprint_infra/observability.py
+++ b/infra/gridprint_infra/observability.py
@@ -28,7 +28,7 @@
 
 from .api import ApiStack
 from .compute import METRIC_NAMESPACE, ComputeStack
-from .config import InfraConfig
+from .config import PREFIX, InfraConfig
 from .iot import IotStack
 
 STAGES = ["S1", "S2", "S3", "S4", "S5", "S6", "S7", "S8", "S9", "S10", "S11", "S12", "S13", "S14", "S15"]
@@ -46,7 +46,7 @@ def __init__(self, scope: Construct, cid: str, *, cfg: InfraConfig, compute: Com
                  iot: IotStack, **kwargs) -> None:
         super().__init__(scope, cid, **kwargs)
         # Subscriptions (email of the on-call person) are added by a human (H1).
-        self.alarm_topic = sns.Topic(self, "Alarms", display_name="GRIDPRINT alarms",
+        self.alarm_topic = sns.Topic(self, "Alarms", display_name=f"{PREFIX} alarms",
                                      enforce_ssl=True)
         action = cw_actions.SnsAction(self.alarm_topic)
 
@@ -88,7 +88,7 @@ def __init__(self, scope: Construct, cid: str, *, cfg: InfraConfig, compute: Com
             a.add_alarm_action(action)
         self.alarms = alarms
 
-        dash = cw.Dashboard(self, "Dashboard", dashboard_name="gridprint")
+        dash = cw.Dashboard(self, "Dashboard", dashboard_name=PREFIX)
         dash.add_widgets(
             cw.GraphWidget(title="Jobs", left=[m("JobsCreated"), m("JobsCompleted")],
                            right=[compute.queue.metric_approximate_number_of_messages_visible(),
diff --git a/infra/gridprint_infra/storage.py b/infra/gridprint_infra/storage.py
index a7d0006..28a76aa 100644
--- a/infra/gridprint_infra/storage.py
+++ b/infra/gridprint_infra/storage.py
@@ -7,7 +7,7 @@
 from aws_cdk import aws_s3 as s3
 from constructs import Construct
 
-from .config import InfraConfig
+from .config import PREFIX, InfraConfig
 
 
 class StorageStack(Stack):
@@ -15,7 +15,7 @@ def __init__(self, scope: Construct, cid: str, *, cfg: InfraConfig, **kwargs) ->
         super().__init__(scope, cid, **kwargs)
         self.key = kms.Key(
             self, "DataKey",
-            alias="alias/gridprint-data",
+            alias=f"alias/{PREFIX}-data",
             enable_key_rotation=True,
             removal_policy=RemovalPolicy.DESTROY,   # `make destroy` removes everything (SPEC 10.6)
             pending_window=Duration.days(7),
@@ -37,6 +37,8 @@ def __init__(self, scope: Construct, cid: str, *, cfg: InfraConfig, **kwargs) ->
         # S3 lifecycle expiration counts whole days. limits.upload_retention_hours is rounded up.
         self.uploads = s3.Bucket(
             self, "Uploads",
+            cors=[s3.CorsRule(allowed_methods=[s3.HttpMethods.PUT], allowed_origins=["*"], allowed_headers=["*"],
+                              max_age=3000)],  # presigned PUT from the browser (D-025)
             lifecycle_rules=[s3.LifecycleRule(
                 id="expire-uploads",
                 expiration=Duration.days(cfg.upload_retention_days),
diff --git a/infra/gridprint_infra/web.py b/infra/gridprint_infra/web.py
index fad04a4..3b769b9 100644
--- a/infra/gridprint_infra/web.py
+++ b/infra/gridprint_infra/web.py
@@ -17,7 +17,7 @@
 from constructs import Construct
 
 from .api import ApiStack
-from .config import REPO, InfraConfig
+from .config import PREFIX, REPO, InfraConfig
 from .storage import StorageStack
 
 WEB_DIST = REPO / "web" / "dist"
@@ -72,7 +72,7 @@ def __init__(self, scope: Construct, cid: str, *, cfg: InfraConfig, api: ApiStac
             scope="CLOUDFRONT",
             default_action=wafv2.CfnWebACL.DefaultActionProperty(allow={}),
             visibility_config=wafv2.CfnWebACL.VisibilityConfigProperty(
-                cloud_watch_metrics_enabled=True, metric_name="gridprint-web", sampled_requests_enabled=True),
+                cloud_watch_metrics_enabled=True, metric_name=f"{PREFIX}-web", sampled_requests_enabled=True),
             rules=[
                 rate_rule("rate-all-per-ip", 0, cfg.waf_rate_limit_5min),
                 rate_rule("rate-job-create-per-ip", 1, cfg.waf_job_create_limit_5min,
@@ -121,7 +121,7 @@ def __init__(self, scope: Construct, cid: str, *, cfg: InfraConfig, api: ApiStac
                     "MaxAgeSeconds": 3000,
                 }]},
             },
-            physical_resource_id=cr.PhysicalResourceId.of("gridprint-uploads-cors"),
+            physical_resource_id=cr.PhysicalResourceId.of(f"{PREFIX}-uploads-cors"),
         )
         cr.AwsCustomResource(
             self, "UploadsCors",
diff --git a/infra/tests/test_stacks.py b/infra/tests/test_stacks.py
index 80e0229..6bd4cda 100644
--- a/infra/tests/test_stacks.py
+++ b/infra/tests/test_stacks.py
@@ -21,6 +21,9 @@
 
 from gridprint_infra import config as cfgmod  # noqa: E402
 from gridprint_infra.app import build_app  # noqa: E402
+from gridprint_infra.config import PREFIX  # noqa: E402
+
+P = PREFIX.capitalize()
 
 ACCOUNT = "123456789012"
 
@@ -58,22 +61,22 @@ def test_docker_context_is_allow_list(tmp_path_factory: pytest.TempPathFactory,
     assert ENGINE_CONTEXT[0] == "*" and API_CONTEXT[0] == "*"
     assert "!infra/docker/engine.Dockerfile" in ENGINE_CONTEXT
     assert "!api" in ENGINE_CONTEXT and "!agent" in ENGINE_CONTEXT
-    assert "!agent" not in API_CONTEXT
+    assert "!agent" in API_CONTEXT and "!node" in API_CONTEXT  # the API imports the worker (agent) and node adapters
 
 
 def test_all_stacks_present(stacks: dict[str, Template]) -> None:
     for name in ["Network", "Storage", "Data", "Compute", "Api", "Iot", "Auth", "Web", "Observability", "Ai"]:
-        assert f"Gridprint{name}" in stacks
+        assert f"{P}{name}" in stacks
 
 
 def test_vpc_gateway_endpoints(stacks: dict[str, Template]) -> None:
-    t = stacks["GridprintNetwork"]
+    t = stacks[f"{P}Network"]
     t.resource_count_is("AWS::EC2::VPCEndpoint", 2)
     t.has_resource_properties("AWS::EC2::VPCEndpoint", {"VpcEndpointType": "Gateway"})
 
 
 def test_buckets_kms_tls_public_block_and_lifecycle(stacks: dict[str, Template]) -> None:
-    t = stacks["GridprintStorage"]
+    t = stacks[f"{P}Storage"]
     buckets = t.find_resources("AWS::S3::Bucket")
     assert len(buckets) == 2
     cfg = cfgmod.load()
@@ -95,25 +98,25 @@ def test_buckets_kms_tls_public_block_and_lifecycle(stacks: dict[str, Template])
 
 
 def test_four_tables_with_pitr_and_gridlog_keys(stacks: dict[str, Template]) -> None:
-    t = stacks["GridprintData"]
+    t = stacks[f"{P}Data"]
     t.resource_count_is("AWS::DynamoDB::Table", 4)
     for name in ["Jobs", "Reviews", "GridLog", "TraceIndex"]:
         t.has_resource_properties("AWS::DynamoDB::Table", {
-            "TableName": f"gridprint-{name}",
+            "TableName": f"{PREFIX}-{name}",
             "PointInTimeRecoverySpecification": {"PointInTimeRecoveryEnabled": True},
         })
     t.has_resource_properties("AWS::DynamoDB::Table", {
-        "TableName": "gridprint-GridLog",
+        "TableName": f"{PREFIX}-GridLog",
         "KeySchema": [{"AttributeName": "pk", "KeyType": "HASH"}, {"AttributeName": "t", "KeyType": "RANGE"}],
         "AttributeDefinitions": Match.array_with([{"AttributeName": "t", "AttributeType": "N"}]),
     })
 
 
 def test_lead_key_schema_for_jobs_reviews_trace(stacks: dict[str, Template]) -> None:
-    t = stacks["GridprintData"]
+    t = stacks[f"{P}Data"]
     for name in ["Jobs", "Reviews", "TraceIndex"]:
         t.has_resource_properties("AWS::DynamoDB::Table", {
-            "TableName": f"gridprint-{name}",
+            "TableName": f"{PREFIX}-{name}",
             "KeySchema": [{"AttributeName": "pk", "KeyType": "HASH"}],
             "AttributeDefinitions": [{"AttributeName": "pk", "AttributeType": "S"}],
             "BillingMode": "PAY_PER_REQUEST",
@@ -130,8 +133,8 @@ def _container(t: Template) -> dict:
 
 
 @pytest.mark.parametrize("stack,command", [
-    ("GridprintApi", ["uvicorn", "api.app:create_app", "--factory", "--host", "0.0.0.0", "--port", "8000"]),
-    ("GridprintCompute", ["python", "-m", "api.worker", "--sqs"]),
+    (f"{P}Api", ["uvicorn", "api.app:create_app", "--factory", "--host", "0.0.0.0", "--port", "8000"]),
+    (f"{P}Compute", ["python", "-m", "api.worker", "--sqs"]),
 ])
 def test_container_command_and_env(stacks: dict[str, Template], stack: str, command: list[str]) -> None:
     c = _container(stacks[stack])
@@ -143,32 +146,32 @@ def test_container_command_and_env(stacks: dict[str, Template], stack: str, comm
 
 
 def test_uploads_cors_put_from_cloudfront(stacks: dict[str, Template]) -> None:
-    t = stacks["GridprintWeb"]
+    t = stacks[f"{P}Web"]
     cr = json.dumps(t.find_resources("Custom::AWS"))
     assert "putBucketCors" in cr
     assert "PUT" in cr
     assert "DomainName" in cr   # origin is built from the distribution domain
-    storage_buckets = stacks["GridprintStorage"].find_resources("AWS::S3::Bucket")
+    storage_buckets = stacks[f"{P}Storage"].find_resources("AWS::S3::Bucket")
     assert all("CorsConfiguration" not in b["Properties"] for b in storage_buckets.values())
 
 
 def test_worker_can_put_uploads_and_write_all_tables(stacks: dict[str, Template]) -> None:
-    pols = json.dumps(stacks["GridprintCompute"].find_resources("AWS::IAM::Policy"))
+    pols = json.dumps(stacks[f"{P}Compute"].find_resources("AWS::IAM::Policy"))
     for action in ["s3:PutObject", "s3:GetObject*", "dynamodb:PutItem", "sqs:ReceiveMessage",
                    "sqs:DeleteMessage"]:
         assert action in pols
     for table in ["Jobs", "Reviews", "GridLog", "TraceIndex"]:
-        assert f"GridprintData:ExportsOutputFnGetAtt{table}" in pols
+        assert f"{P}Data:ExportsOutputFnGetAtt{table}" in pols
 
 
 def test_cognito_reviewer_group(stacks: dict[str, Template]) -> None:
-    t = stacks["GridprintAuth"]
+    t = stacks[f"{P}Auth"]
     t.has_resource_properties("AWS::Cognito::UserPoolGroup", {"GroupName": "reviewer"})
     t.has_resource_properties("AWS::Cognito::UserPool", {"MfaConfiguration": "ON"})
 
 
 def test_waf_rate_rules_on_cloudfront(stacks: dict[str, Template]) -> None:
-    t = stacks["GridprintWeb"]
+    t = stacks[f"{P}Web"]
     t.has_resource_properties("AWS::WAFv2::WebACL", {
         "Scope": "CLOUDFRONT",
         "Rules": Match.array_with([Match.object_like({
@@ -179,14 +182,14 @@ def test_waf_rate_rules_on_cloudfront(stacks: dict[str, Template]) -> None:
 
 
 def test_arm64_task_definitions(stacks: dict[str, Template]) -> None:
-    worker = stacks["GridprintCompute"]
+    worker = stacks[f"{P}Compute"]
     worker.has_resource_properties("AWS::ECS::TaskDefinition", {
         "RequiresCompatibilities": ["EC2"],
         "PlacementConstraints": [{"Type": "memberOf",
                                   "Expression": "attribute:ecs.cpu-architecture == arm64"}],
     })
     worker.has_resource_properties("AWS::ECS::Service", {"CapacityProviderStrategy": Match.any_value()})
-    api = stacks["GridprintApi"]
+    api = stacks[f"{P}Api"]
     api.has_resource_properties("AWS::ECS::TaskDefinition", {
         "RequiresCompatibilities": ["FARGATE"],
         "RuntimePlatform": {"CpuArchitecture": "ARM64", "OperatingSystemFamily": "LINUX"},
@@ -195,7 +198,7 @@ def test_arm64_task_definitions(stacks: dict[str, Template]) -> None:
 
 
 def test_graviton_capacity_and_queue(stacks: dict[str, Template]) -> None:
-    t = stacks["GridprintCompute"]
+    t = stacks[f"{P}Compute"]
     t.has_resource_properties("AWS::EC2::LaunchTemplate", {
         "LaunchTemplateData": Match.object_like({"InstanceType": "c8g.2xlarge"})})
     t.resource_count_is("AWS::ECS::CapacityProvider", 1)
@@ -208,7 +211,7 @@ def test_graviton_capacity_and_queue(stacks: dict[str, Template]) -> None:
 
 
 def test_bedrock_policy_is_pinned(stacks: dict[str, Template]) -> None:
-    t = stacks["GridprintAi"]
+    t = stacks[f"{P}Ai"]
     pol = next(iter(t.find_resources("AWS::IAM::ManagedPolicy").values()))
     stmts = pol["Properties"]["PolicyDocument"]["Statement"]
     assert len(stmts) == 1
@@ -221,9 +224,9 @@ def test_bedrock_policy_is_pinned(stacks: dict[str, Template]) -> None:
 
 
 def test_iot_policy_topic_and_arm64_lambda(stacks: dict[str, Template]) -> None:
-    t = stacks["GridprintIot"]
+    t = stacks[f"{P}Iot"]
     doc = json.dumps(t.find_resources("AWS::IoT::Policy"))
-    assert "topic/gridprint/${iot:Connection.Thing.Attributes[zone]}/${iot:Connection.Thing.ThingName}" in doc
+    assert f"topic/{PREFIX}/${{iot:Connection.Thing.Attributes[zone]}}/${{iot:Connection.Thing.ThingName}}" in doc
     t.has_resource_properties("AWS::Lambda::Function",
                               {"Architectures": ["arm64"], "Handler": "handler.handler"})
     t.resource_count_is("AWS::IoT::TopicRule", 1)
@@ -231,7 +234,7 @@ def test_iot_policy_topic_and_arm64_lambda(stacks: dict[str, Template]) -> None:
 
 
 def test_observability_alarms(stacks: dict[str, Template]) -> None:
-    t = stacks["GridprintObservability"]
+    t = stacks[f"{P}Observability"]
     t.resource_count_is("AWS::CloudWatch::Dashboard", 1)
     limit = cfgmod.load().freshness_limit_s
     t.has_resource_properties("AWS::CloudWatch::Alarm", {
@@ -239,7 +242,7 @@ def test_observability_alarms(stacks: dict[str, Template]) -> None:
 
 
 def test_cool_ami_variant(cool_stacks: dict[str, Template]) -> None:
-    t = cool_stacks["GridprintCompute"]
+    t = cool_stacks[f"{P}Compute"]
     lt = json.dumps(t.find_resources("AWS::EC2::LaunchTemplate"))
     assert "amazon-ecs-init-latest.arm64.deb" in lt
     t.has_resource_properties("AWS::ECS::TaskDefinition", {
@@ -248,4 +251,4 @@ def test_cool_ami_variant(cool_stacks: dict[str, Template]) -> None:
                 [Match.object_like({"ContainerPath": "/opt/cool", "ReadOnly": True})]),
         })],
     })
-    assert "GridprintBenchImages" in cool_stacks
+    assert f"{P}BenchImages" in cool_stacks
diff --git a/mcp_server/tools.py b/mcp_server/tools.py
index bd79e76..e6f2406 100644
--- a/mcp_server/tools.py
+++ b/mcp_server/tools.py
@@ -32,6 +32,13 @@ def __init__(self, workdir: Path, gridlog: GridLogAdapter, store: JobStoreAdapte
     @classmethod
     def from_env(cls) -> EngineTools:
         work = Path(os.environ.get("GRIDPRINT_WORKDIR", REPO / "work"))
+        if os.environ.get("GRIDPRINT_MODE") == "aws":  # same adapters as the API and worker (SPEC 5)
+            from api.aws_adapters import DynamoJobStore
+            from node.ingest.aws_gridlog import DynamoGridLog
+
+            region = os.environ.get("AWS_REGION") or os.environ.get("AWS_DEFAULT_REGION") or "us-east-1"
+            return cls(work, DynamoGridLog(table_name=os.environ["GRIDLOG_TABLE"], region=region),
+                       DynamoJobStore(region))
         grid = Path(os.environ.get("GRIDPRINT_GRIDLOG", REPO / "data" / "gridlog"))
         store = Path(os.environ.get("GRIDPRINT_STORE", REPO / "work" / "store"))
         return cls(work, LocalGridLog(grid), LocalJobStore(store))
diff --git a/node/firmware/FLASHING.md b/node/firmware/FLASHING.md
index 0fce843..af327fb 100644
--- a/node/firmware/FLASHING.md
+++ b/node/firmware/FLASHING.md
@@ -92,3 +92,8 @@ Topic `gridprint/<zone>/<node_id>`, QoS 1, one message per UTC second:
 
 `quality` is `gps` (PPS-disciplined timing) or `ntp` (SNTP fallback, larger timing uncertainty;
 `gps_lock` is then false). The ingest Lambda (`node/ingest/handler.py`) rejects any other value.
+
+## MQTT topic prefix
+
+The Node publishes to `<prefix>/<zone>/<node_id>`. Set "MQTT topic prefix" in `idf.py menuconfig` to the value
+of `aws.resource_prefix` in `config/default.yaml` (default `orchard`). `node/provision.py` prints the exact topic.
diff --git a/node/firmware/main/Kconfig.projbuild b/node/firmware/main/Kconfig.projbuild
index b70de7b..e9463e0 100644
--- a/node/firmware/main/Kconfig.projbuild
+++ b/node/firmware/main/Kconfig.projbuild
@@ -18,6 +18,10 @@ menu "GRIDPRINT Node"
         string "Grid zone id (config/zones.yaml)"
         default "IN"
 
+    config GRIDPRINT_TOPIC_PREFIX
+        string "MQTT topic prefix (aws.resource_prefix in config/default.yaml)"
+        default "orchard"
+
     config GRIDPRINT_NODE_ID
         string "Node id (IoT thing name and MQTT client id)"
         default "node-01"
diff --git a/node/firmware/main/main.c b/node/firmware/main/main.c
index 4cfa303..f39563d 100644
--- a/node/firmware/main/main.c
+++ b/node/firmware/main/main.c
@@ -6,7 +6,7 @@
 // 2. For each UTC second the crossings between two PPS edges are filtered (glitch, band and median
 //    filters in freq_calc.c) and converted to a frequency.
 // 3. Each second a JSON message {zone, node_id, t_utc_s, freq_hz, quality, gps_lock} is published with
-//    QoS 1 over MQTT/TLS (esp-mqtt) to AWS IoT Core topic gridprint/<zone>/<node_id>.
+//    QoS 1 over MQTT/TLS (esp-mqtt) to AWS IoT Core topic <prefix>/<zone>/<node_id> (prefix = aws.resource_prefix).
 // 4. Messages go through a RAM FIFO. When offline they stay in the FIFO; after reconnect the FIFO is
 //    drained oldest first (back-fill), at most CONFIG_GRIDPRINT_BACKFILL_RATE messages per second.
 // Fallback (SPEC V11): without GPS lock, and if enabled, seconds are framed by SNTP time and sent with
@@ -336,7 +336,8 @@ static void uplink_task(void *arg)
 {
     char topic[96];
     char payload[200];
-    snprintf(topic, sizeof(topic), "gridprint/%s/%s", CONFIG_GRIDPRINT_ZONE, CONFIG_GRIDPRINT_NODE_ID);
+    snprintf(topic, sizeof(topic), "%s/%s/%s", CONFIG_GRIDPRINT_TOPIC_PREFIX, CONFIG_GRIDPRINT_ZONE,
+             CONFIG_GRIDPRINT_NODE_ID);
     const int gap_ms = 1000 / CONFIG_GRIDPRINT_BACKFILL_RATE;
     for (;;) {
         sample_t s;
diff --git a/node/ingest/aws_gridlog.py b/node/ingest/aws_gridlog.py
index 4152a59..2e7a314 100644
--- a/node/ingest/aws_gridlog.py
+++ b/node/ingest/aws_gridlog.py
@@ -15,7 +15,7 @@
 from node.ingest.handler import DynamoWriter, day_key
 
 DAY_S = 86400
-DEFAULT_TABLE = os.environ.get("GRIDPRINT_GRIDLOG_TABLE", "gridprint-GridLog")  # infra data stack name
+DEFAULT_TABLE = os.environ.get("GRIDLOG_TABLE") or os.environ.get("GRIDPRINT_GRIDLOG_TABLE") or "gridprint-GridLog"
 
 
 def _query_all(table: Any, **kw: Any) -> list[dict[str, Any]]:
diff --git a/node/ingest/handler.py b/node/ingest/handler.py
index 58eab0a..c0a6905 100644
--- a/node/ingest/handler.py
+++ b/node/ingest/handler.py
@@ -35,7 +35,7 @@
 LOG = logging.getLogger("gridprint.ingest")
 LOG.setLevel(logging.INFO)
 
-QUALITIES = ("gps", "ntp")
+QUALITIES = ("gps", "ntp", "sim")  # "sim": generated by simulated_publisher.py, never a measurement
 NODE_SOURCES = ("node", "sim")
 ZONE_RE = re.compile(r"^[A-Z0-9][A-Z0-9-]{0,15}$")
 NODE_RE = re.compile(r"^[A-Za-z0-9_-]{1,64}$")
diff --git a/node/ingest/import_wav_reference.py b/node/ingest/import_wav_reference.py
new file mode 100644
index 0000000..7c93d2e
--- /dev/null
+++ b/node/ingest/import_wav_reference.py
@@ -0,0 +1,89 @@
+"""Import a recorded mains waveform (.wav) as a 1 s grid-frequency reference (SPEC 10.4 importers).
+
+Public ENF datasets ship the mains reference as audio-rate voltage recordings (e.g. EV-ENFD `ENF_Reference`,
+one hour per file). Frequency per second: rising zero crossings of the band-limited waveform, timed with
+linear interpolation between samples; the mean period inside each second gives that second's frequency.
+
+    python node/ingest/import_wav_reference.py REF.wav --zone CN --t0-utc 2023-01-01T00:00:00Z --source ev-enfd
+The file has no absolute time, so the start time is given by the caller (documented with the dataset).
+"""
+
+from __future__ import annotations
+
+import argparse
+import sys
+import wave
+from datetime import datetime
+from pathlib import Path
+
+import numpy as np
+
+REPO = Path(__file__).resolve().parents[2]
+sys.path[:0] = [str(REPO), str(REPO / "engine")]
+
+
+def read_wav(path: Path) -> tuple[np.ndarray, int]:
+    with wave.open(str(path), "rb") as w:
+        n, ch, width, fs = w.getnframes(), w.getnchannels(), w.getsampwidth(), w.getframerate()
+        raw = w.readframes(n)
+    dt = {1: np.uint8, 2: np.int16, 4: np.int32}[width]
+    x = np.frombuffer(raw, dtype=dt).astype(np.float64).reshape(-1, ch)[:, 0]
+    if width == 1:
+        x -= 128.0
+    return x, fs
+
+
+def bandpass(x: np.ndarray, fs: int, nominal: float, half_width: float = 5.0) -> np.ndarray:
+    """FFT band-pass around the nominal frequency (float64). Removes DC and harmonics before crossings."""
+    spec = np.fft.rfft(x - x.mean())
+    f = np.fft.rfftfreq(len(x), 1.0 / fs)
+    spec[(f < nominal - half_width) | (f > nominal + half_width)] = 0
+    return np.fft.irfft(spec, len(x))
+
+
+def per_second_frequency(x: np.ndarray, fs: int, nominal: float) -> tuple[np.ndarray, np.ndarray]:
+    """Return (second index from file start, frequency Hz) for every whole second with crossings."""
+    y = bandpass(x, fs, nominal)
+    s0, s1 = y[:-1], y[1:]
+    idx = np.flatnonzero((s0 < 0) & (s1 >= 0))
+    tc = (idx + (-s0[idx]) / (s1[idx] - s0[idx])) / fs  # crossing times, linear interpolation
+    periods = np.diff(tc)
+    mids = 0.5 * (tc[1:] + tc[:-1])
+    ok = np.abs(periods - 1.0 / nominal) < 0.1 / nominal  # reject glitches (±10 % of a period)
+    secs = np.floor(mids[ok]).astype(np.int64)
+    out_s, out_f = [], []
+    last = int(len(x) / fs) - 1
+    for s in np.unique(secs):
+        if s <= 0 or s >= last:  # the FFT band-pass biases the first and last second (edge effects)
+            continue
+        p = periods[ok][secs == s]
+        if len(p) >= 0.8 * nominal:
+            out_s.append(int(s))
+            out_f.append(1.0 / float(p.mean()))
+    return np.array(out_s, np.int64), np.array(out_f, np.float64)
+
+
+def main(argv: list[str] | None = None) -> int:
+    from gridprint_engine.adapters import LocalGridLog
+
+    ap = argparse.ArgumentParser(description=__doc__.splitlines()[0])
+    ap.add_argument("wav", nargs="+")
+    ap.add_argument("--zone", required=True)
+    ap.add_argument("--nominal", type=float, default=50.0)
+    ap.add_argument("--t0-utc", required=True, help="UTC start time of the first file (ISO 8601)")
+    ap.add_argument("--source", default="wav-import")
+    ap.add_argument("--root", default=str(REPO / "data" / "gridlog"))
+    a = ap.parse_args(argv)
+    t0 = int(datetime.fromisoformat(a.t0_utc.replace("Z", "+00:00")).timestamp())
+    gl = LocalGridLog(Path(a.root))
+    for p in a.wav:
+        x, fs = read_wav(Path(p))
+        s, f = per_second_frequency(x, fs, a.nominal)
+        gl.write(a.zone, t0 + s, f, source=a.source, node=Path(p).stem, quality="reference-wav")
+        print(f"{p}: {len(s)} seconds, {fs} Hz sample rate, frequency {f.min():.4f}–{f.max():.4f} Hz")
+        t0 += int(len(x) / fs)
+    return 0
+
+
+if __name__ == "__main__":
+    sys.exit(main())
diff --git a/node/ingest/simulated_publisher.py b/node/ingest/simulated_publisher.py
index 4a0311e..82b8fc6 100644
--- a/node/ingest/simulated_publisher.py
+++ b/node/ingest/simulated_publisher.py
@@ -52,7 +52,7 @@ def ou_track(n: int, f0: float, seed: int, theta: float = THETA, sigma: float =
 
 
 def messages(zone: str, nodes: list[str], t0: int, seconds: int, seed: int = 0,
-             quality: str = "gps", drop_fraction: float = 0.0) -> Iterator[dict[str, Any]]:
+             quality: str = "sim", drop_fraction: float = 0.0) -> Iterator[dict[str, Any]]:
     """Yield node messages in time order. `drop_fraction` removes random seconds (to test gap reports)."""
     f0 = nominal_hz(zone)
     track = ou_track(seconds, f0, seed)
@@ -132,7 +132,7 @@ def main(argv: list[str] | None = None) -> int:
     ap.add_argument("--seconds", type=int, default=3600)
     ap.add_argument("--start", type=int, default=None, help="first UTC epoch second (default: now - seconds)")
     ap.add_argument("--seed", type=int, default=0)
-    ap.add_argument("--quality", choices=["gps", "ntp"], default="gps")
+    ap.add_argument("--quality", choices=["sim", "gps", "ntp"], default="sim")
     g = ap.add_mutually_exclusive_group(required=True)
     g.add_argument("--local", type=Path, help="LocalGridLog root, for example work/gridlog")
     g.add_argument("--iot", action="store_true", help="publish to AWS IoT Core")
diff --git a/node/ingest/tests/test_import_wav_reference.py b/node/ingest/tests/test_import_wav_reference.py
new file mode 100644
index 0000000..f57b210
--- /dev/null
+++ b/node/ingest/tests/test_import_wav_reference.py
@@ -0,0 +1,38 @@
+from __future__ import annotations
+
+import wave
+from pathlib import Path
+
+import numpy as np
+
+from gridprint_engine.adapters import LocalGridLog
+from node.ingest import import_wav_reference as iw
+
+
+def _wav(path: Path, freq: np.ndarray, fs: int = 8000) -> None:
+    t = np.arange(len(freq) * fs) / fs
+    f_inst = np.repeat(freq, fs)
+    phase = 2 * np.pi * np.cumsum(f_inst) / fs
+    x = 0.8 * np.sin(phase) + 0.1 * np.sin(3 * phase) + 0.01 * np.random.default_rng(0).normal(size=len(t))
+    with wave.open(str(path), "wb") as w:
+        w.setnchannels(1)
+        w.setsampwidth(2)
+        w.setframerate(fs)
+        w.writeframes((x * 30000).astype(np.int16).tobytes())
+
+
+def test_per_second_frequency_recovers_track(tmp_path):
+    truth = 50 + 0.02 * np.sin(np.arange(30) / 5)
+    _wav(tmp_path / "r.wav", truth)
+    x, fs = iw.read_wav(tmp_path / "r.wav")
+    s, f = iw.per_second_frequency(x, fs, 50.0)
+    assert len(s) >= 28
+    assert np.max(np.abs(f[2:-2] - truth[s[2:-2]])) < 0.002
+
+
+def test_cli_writes_gridlog(tmp_path):
+    _wav(tmp_path / "r.wav", np.full(10, 50.01))
+    assert iw.main([str(tmp_path / "r.wav"), "--zone", "CN", "--t0-utc", "2023-01-01T00:00:00Z",
+                    "--root", str(tmp_path / "gl")]) == 0
+    t, f = LocalGridLog(tmp_path / "gl").read("CN", 1672531200, 1672531210)
+    assert len(t) >= 8 and np.allclose(f, 50.01, atol=1e-3)
diff --git a/node/ingest/tests/test_ingest_data_quality.py b/node/ingest/tests/test_ingest_data_quality.py
index 6788a24..c085fc6 100644
--- a/node/ingest/tests/test_ingest_data_quality.py
+++ b/node/ingest/tests/test_ingest_data_quality.py
@@ -24,7 +24,7 @@ def test_gaps_coverage_and_outliers():
 
 
 def test_cli_exit_codes(tmp_path, capsys):
-    sp.run_local(tmp_path, sp.messages("SIM50", ["n1"], T, 3600, seed=2))
+    sp.run_local(tmp_path, sp.messages("SIM50", ["n1"], T, 3600, seed=2, quality="gps"))  # GPS-labelled test rows
     assert dq.main(["--zone", "SIM50", "--hours", "1", "--end", str(T + 3599), "--root", str(tmp_path)]) == 0
     out = capsys.readouterr().out
     assert "coverage_pct=100.000" in out and "gps_lock_pct=100.000" in out and "PASS" in out
diff --git a/node/ingest/tests/test_ingest_e2e.py b/node/ingest/tests/test_ingest_e2e.py
index e20149d..e887c1f 100644
--- a/node/ingest/tests/test_ingest_e2e.py
+++ b/node/ingest/tests/test_ingest_e2e.py
@@ -34,7 +34,8 @@ def test_simulated_publisher_end_to_end(tmp_path):
     rows = data_quality.read_local_rows(tmp_path, "SIM50", T, T + 599)
     assert {r["source"] for r in rows} == {"sim"}
     rep = data_quality.analyze(rows, T, T + 599, 50.0)
-    assert rep["coverage_pct"] == 100.0 and rep["gps_lock_pct"] == 100.0 and rep["gaps"] == []
+    # simulated rows are labelled "sim", so they never count as GPS-locked
+    assert rep["coverage_pct"] == 100.0 and rep["gps_lock_pct"] == 0.0 and rep["gaps"] == []
 
 
 def test_invalid_messages_are_not_written(tmp_path):
diff --git a/node/ingest/tests/test_node_provision.py b/node/ingest/tests/test_node_provision.py
index 008c751..0fdeaa5 100644
--- a/node/ingest/tests/test_node_provision.py
+++ b/node/ingest/tests/test_node_provision.py
@@ -16,7 +16,7 @@ def __init__(self, stack_deployed=False):
         self.stack_deployed = stack_deployed
 
     def get_policy(self, policyName):
-        if self.stack_deployed and policyName == "gridprint-node":
+        if self.stack_deployed and policyName == f"{prov.PREFIX}-node":
             return {}
         raise ClientError({"Error": {"Code": "ResourceNotFoundException", "Message": ""}}, "GetPolicy")
 
@@ -47,7 +47,7 @@ def test_policy_is_scoped_to_node_topic():
     doc = prov.policy_document("us-east-1", "123456789012", "IN", "node-01")
     res = [s["Resource"] for s in doc["Statement"]]
     assert res == ["arn:aws:iot:us-east-1:123456789012:client/node-01",
-                   "arn:aws:iot:us-east-1:123456789012:topic/gridprint/IN/node-01"]
+                   f"arn:aws:iot:us-east-1:123456789012:topic/{prov.PREFIX}/IN/node-01"]
 
 
 def test_provision_writes_certs(tmp_path):
@@ -56,9 +56,9 @@ def test_provision_writes_certs(tmp_path):
     names = [c[0] for c in iot.calls]
     assert names == ["create_policy", "create_thing", "create_keys_and_certificate", "attach_policy",
                      "attach_thing_principal", "describe_endpoint"]
-    assert iot.calls[3][1]["policyName"] == "gridprint-node-node-01"
+    assert iot.calls[3][1]["policyName"] == f"{prov.PREFIX}-node-node-01"
     assert (tmp_path / "private.pem.key").read_text() == "KEY"
-    assert r["topic"] == "gridprint/IN/node-01"
+    assert r["topic"] == f"{prov.PREFIX}/IN/node-01"
 
 
 def test_provision_uses_stack_policy_and_thing_type(tmp_path):
@@ -66,6 +66,6 @@ def test_provision_uses_stack_policy_and_thing_type(tmp_path):
     r = prov.provision(iot, FakeSts(), "us-east-1", "IN", "node-01", tmp_path)
     calls = dict(iot.calls)
     assert "create_policy" not in calls
-    assert calls["create_thing"]["thingTypeName"] == "gridprint-node"
+    assert calls["create_thing"]["thingTypeName"] == f"{prov.PREFIX}-node"
     assert calls["create_thing"]["attributePayload"]["attributes"]["zone"] == "IN"
-    assert calls["attach_policy"]["policyName"] == "gridprint-node" and r["policy"] == "gridprint-node"
+    assert calls["attach_policy"]["policyName"] == f"{prov.PREFIX}-node" and r["policy"] == f"{prov.PREFIX}-node"
diff --git a/node/provision.py b/node/provision.py
index bd25ac8..3db592c 100644
--- a/node/provision.py
+++ b/node/provision.py
@@ -18,9 +18,13 @@
 from pathlib import Path
 from typing import Any
 
+import yaml
+
 CERT_DIR = Path(__file__).resolve().parent / "firmware" / "certs"
-STACK_POLICY = "gridprint-node"  # created by infra/gridprint_infra/iot.py
-THING_TYPE = "gridprint-node"
+PREFIX = str((yaml.safe_load((Path(__file__).resolve().parents[1] / "config" / "default.yaml").read_text())
+              .get("aws") or {}).get("resource_prefix", "gridprint"))  # aws.resource_prefix
+STACK_POLICY = f"{PREFIX}-node"  # created by infra/gridprint_infra/iot.py
+THING_TYPE = f"{PREFIX}-node"
 
 
 def policy_document(region: str, account: str, zone: str, node_id: str) -> dict[str, Any]:
@@ -30,7 +34,7 @@ def policy_document(region: str, account: str, zone: str, node_id: str) -> dict[
         "Statement": [
             {"Effect": "Allow", "Action": "iot:Connect", "Resource": f"{base}:client/{node_id}"},
             {"Effect": "Allow", "Action": "iot:Publish",
-             "Resource": f"{base}:topic/gridprint/{zone}/{node_id}"},
+             "Resource": f"{base}:topic/{PREFIX}/{zone}/{node_id}"},
         ],
     }
 
@@ -53,7 +57,7 @@ def provision(iot: Any, sts: Any, region: str, zone: str, node_id: str,
     if _exists(lambda: iot.get_policy(policyName=STACK_POLICY)):
         policy_name = STACK_POLICY
     else:
-        policy_name = f"gridprint-node-{node_id}"
+        policy_name = f"{PREFIX}-node-{node_id}"
         if not _exists(lambda: iot.get_policy(policyName=policy_name)):
             iot.create_policy(policyName=policy_name,
                               policyDocument=json.dumps(policy_document(region, account, zone, node_id)))
@@ -73,7 +77,7 @@ def provision(iot: Any, sts: Any, region: str, zone: str, node_id: str,
     (out_dir / "endpoint.txt").write_text(endpoint + "\n")
     (out_dir / "certificate_arn.txt").write_text(cert["certificateArn"] + "\n")
     return {"thing": node_id, "policy": policy_name, "certificate_arn": cert["certificateArn"],
-            "endpoint": endpoint, "topic": f"gridprint/{zone}/{node_id}", "cert_dir": str(out_dir)}
+            "endpoint": endpoint, "topic": f"{PREFIX}/{zone}/{node_id}", "cert_dir": str(out_dir)}
 
 
 def main(argv: list[str] | None = None) -> int:
diff --git a/scripts/check_numbers_sourced.py b/scripts/check_numbers_sourced.py
index baf02a3..661f597 100644
--- a/scripts/check_numbers_sourced.py
+++ b/scripts/check_numbers_sourced.py
@@ -24,7 +24,7 @@
     re.compile(r"\b(?:OpenCV|Python|WCAG|ES|Graviton|python|opencv)\s?\d+(?:\.\d+)*\b"),
     re.compile(r"\b(?:c8g|c7g|c7i|m7g|m7i|c8i)\.\w+\b"),
     re.compile(r"\b[MHVRDSB]\d+(?:\.\d+)*\b"),              # milestone/rule/stage ids
-    re.compile(r"\b(?:Part|Section|§)\s?\d+(?:\.\d+)*\b"),
+    re.compile(r"\b(?:Part|Section|§|SPEC)\s?\d+(?:\.\d+)*\b"),
     re.compile(r"\b\d:\d{2}(?:[–-]\d:\d{2})?\b"),             # video timecodes
     re.compile(r"`[^`]*`"),                                   # code spans
     re.compile(r"\]\([^)]*\)"),                               # link targets
diff --git a/scripts/seed_aws.py b/scripts/seed_aws.py
new file mode 100644
index 0000000..f58d1fa
--- /dev/null
+++ b/scripts/seed_aws.py
@@ -0,0 +1,59 @@
+"""Seed the deployed system: demo-case inputs to the results bucket (`demo/`) and reference GridLog data
+from the local GridLog folder into the DynamoDB GridLog table. Uses the `gridprint` profile only.
+
+    python scripts/seed_aws.py --results-bucket <name> --gridlog-table <name> [--zone SIM50]
+"""
+
+from __future__ import annotations
+
+import argparse
+import sys
+from pathlib import Path
+
+import boto3
+import numpy as np
+import yaml
+
+REPO = Path(__file__).resolve().parents[1]
+sys.path[:0] = [str(REPO), str(REPO / "engine")]
+
+
+def main() -> int:
+    from gridprint_engine.adapters import LocalGridLog
+    from node.ingest.aws_gridlog import DynamoGridLog
+
+    ap = argparse.ArgumentParser()
+    ap.add_argument("--results-bucket", required=True)
+    ap.add_argument("--gridlog-table", required=True)
+    ap.add_argument("--zone", default="SIM50")
+    ap.add_argument("--data-root", default=str(REPO), help="folder that holds data/demo and data/gridlog")
+    ap.add_argument("--gridlog-root", default=None)
+    a = ap.parse_args()
+    root = Path(a.data_root)
+    a.gridlog_root = a.gridlog_root or str(root / "data" / "gridlog")
+    cfg = yaml.safe_load((REPO / "config" / "default.yaml").read_text())
+    s = boto3.Session(profile_name=cfg["aws"]["profile"], region_name=cfg["aws"]["region"])
+    s3 = s.client("s3")
+    cases = yaml.safe_load((REPO / "config" / "demo_cases.yaml").read_text())["cases"]
+    for c in cases:
+        for field in ("video", "sidecar"):
+            rel = c.get(field)
+            if rel and (root / rel).exists():
+                s3.upload_file(str(root / rel), a.results_bucket, f"demo/{Path(rel).name}")
+                print(f"uploaded demo/{Path(rel).name}")
+    local = LocalGridLog(Path(a.gridlog_root))
+    files = sorted((Path(a.gridlog_root) / a.zone).glob("*.csv"))
+    remote = DynamoGridLog(table_name=a.gridlog_table, profile=cfg["aws"]["profile"], region=cfg["aws"]["region"])
+    total = 0
+    for f in files:
+        day0 = int(np.datetime64(f"{f.stem[:4]}-{f.stem[4:6]}-{f.stem[6:]}").astype("datetime64[s]").astype(int))
+        t, fr = local.read(a.zone, day0, day0 + 86399)
+        if len(t):
+            remote.write(a.zone, t, fr, source="simulator", node="seed")
+            total += len(t)
+    print(f"GridLog {a.zone}: {total} seconds written to {a.gridlog_table}")
+    return 0
+
+
+if __name__ == "__main__":
+    sys.exit(main())
diff --git a/tests/test_stress.py b/tests/test_stress.py
new file mode 100644
index 0000000..f36e7c2
--- /dev/null
+++ b/tests/test_stress.py
@@ -0,0 +1,158 @@
+"""Stress and fuzz tests: invariants that must hold for any input.
+
+- S13 verdict logic over random reason sets and flags (R1, R2, R3, R9).
+- Agent policies under a random (adversarial) planner: verdict always computed, never FINAL for CONTRADICTED,
+  budgets respected, no analysis after the verdict.
+- Engine on malformed and edge-case files: no crash with a wrong verdict; never CONTRADICTED without signal.
+"""
+
+from __future__ import annotations
+
+import asyncio
+import random
+from pathlib import Path
+from typing import Any
+
+import av
+import numpy as np
+import pytest
+
+from agent.orchestrator import run_job
+from agent.policies import ALL_TOOLS, Action
+from gridprint_engine.adapters import LocalGridLog
+from gridprint_engine.pipeline import run_default
+from gridprint_engine.schemas import LifecycleState, Reason, Verdict
+from gridprint_engine.verdict import STOP_REASONS, VerdictInputs, decide
+
+ALL_REASONS = list(Reason)
+
+
+def test_verdict_invariants_fuzz():
+    rng = random.Random(0)
+    for _ in range(20000):
+        rs = set(rng.sample(ALL_REASONS, rng.randint(0, 8)))
+        inp = VerdictInputs(reasons=rs, match_passes=rng.random() < 0.5, claim_present=rng.random() < 0.3,
+                            claim_within_tolerance=rng.choice([None, True, False]),
+                            significant_edit=rng.random() < 0.3, face_anomaly=rng.random() < 0.3)
+        out = decide(inp)
+        assert out.verdict in (Verdict.VERIFIED, Verdict.CONTRADICTED, Verdict.INCONCLUSIVE)  # R1
+        if rs & STOP_REASONS:
+            assert out.verdict == Verdict.INCONCLUSIVE  # R2 (absence of signal) and S13.1
+        if out.verdict == Verdict.CONTRADICTED:
+            assert out.state == LifecycleState.PENDING_REVIEW  # R3
+            assert inp.significant_edit or Reason.SEGMENT_OFFSET_INCONSISTENT in rs or (
+                inp.claim_present and inp.match_passes and inp.claim_within_tolerance is False)  # R9
+        else:
+            assert out.state == LifecycleState.DRAFT
+        if out.verdict == Verdict.VERIFIED:
+            assert inp.match_passes and not inp.significant_edit
+
+
+class RandomPlanner:
+    """Adversarial planner double: random tools, random (often disallowed) arguments, random stops."""
+
+    kind = "fallback"
+    model_id = None
+
+    def __init__(self, seed: int):
+        self.rng = random.Random(seed)
+
+    def next_action(self, history: list[Any]) -> Action:
+        r = self.rng.random()
+        if r < 0.05:
+            return Action(None, {}, "random stop")
+        tool = self.rng.choice(sorted(ALL_TOOLS) + ["delete_everything", "set_threshold"])
+        args = self.rng.choice([{}, {"final": True}, {"snr_weak_db": -100}, {"verdict": "VERIFIED"},
+                                {"strategy": "top"}, {"kind": "camera_model", "message": "m"}])
+        return Action(tool, args, "random")
+
+
+class RecordingTools:
+    def __init__(self, seed: int):
+        self.rng = random.Random(seed)
+        self.calls: list[tuple[str, dict[str, Any]]] = []
+
+    async def call(self, tool: str, args: dict[str, Any]) -> dict[str, Any]:
+        self.calls.append((tool, args))
+        if self.rng.random() < 0.1:
+            raise RuntimeError("tool failure")
+        if tool == "compute_verdict":
+            return {"verdict": self.rng.choice(["VERIFIED", "CONTRADICTED", "INCONCLUSIVE"])}
+        return {}
+
+
+@pytest.mark.parametrize("seed", range(200))
+def test_policies_hold_under_random_planner(seed):
+    tools = RecordingTools(seed)
+    max_calls = 20
+    trace, hist = asyncio.run(run_job("j", RandomPlanner(seed), tools, 4, max_calls))
+    names = [c[0] for c in tools.calls]
+    assert set(names) <= ALL_TOOLS
+    assert len(names) <= max_calls + 3
+    assert sum(n == "extract_flicker" for n in names) <= 4
+    for _, args in tools.calls:
+        assert not ({"snr_weak_db", "verdict"} & set(args))
+    # history and tool calls align one to one; find the first verdict that succeeded
+    first = next((i for i, h in enumerate(hist) if h.tool == "compute_verdict" and h.error is None), None)
+    if first is not None:
+        analysis = {"probe_video", "estimate_readout", "analyze_motion", "propose_patches", "extract_flicker",
+                    "match_reference", "check_continuity", "face_region_check", "compute_verdict"}
+        assert all(n not in analysis for n, _ in tools.calls[first + 1:])
+        if hist[first].result["verdict"] == "CONTRADICTED":
+            assert not [a for n, a in tools.calls[first + 1:] if n == "render_report" and a.get("final", True)]
+    for st in trace.steps:
+        assert st.t_start and st.t_end and st.planner and st.tool
+
+
+# ---------------------------------------------------------------- malformed and edge-case inputs
+def _write(path: Path, frames: list[np.ndarray], fps: int = 30) -> Path:
+    with av.open(str(path), "w") as c:
+        s = c.add_stream("libx264", rate=fps)
+        s.height, s.width = frames[0].shape
+        s.pix_fmt = "yuv420p"
+        for f in frames:
+            for p in s.encode(av.VideoFrame.from_ndarray(np.stack([f] * 3, -1), format="rgb24")):
+                c.mux(p)
+        for p in s.encode():
+            c.mux(p)
+    return path
+
+
+EDGE = {
+    "black": lambda: [np.zeros((48, 64), np.uint8)] * 30,
+    "saturated": lambda: [np.full((48, 64), 255, np.uint8)] * 30,
+    "noise": lambda: [np.random.default_rng(i).integers(0, 255, (48, 64), dtype=np.uint8) for i in range(30)],
+    "one_frame": lambda: [np.full((48, 64), 120, np.uint8)],
+    "flat_grey": lambda: [np.full((48, 64), 120, np.uint8)] * 60,
+}
+
+
+@pytest.mark.parametrize("name", sorted(EDGE))
+def test_edge_case_videos_never_contradicted(tmp_path, name):
+    v = _write(tmp_path / f"{name}.mp4", EDGE[name]())
+    job = run_default(v, tmp_path / "work", LocalGridLog(tmp_path / "gridlog"))
+    assert job.result is not None
+    assert job.result.verdict == Verdict.INCONCLUSIVE
+
+
+@pytest.mark.parametrize("payload", [b"", b"\x00" * 10, b"not a video", b"\x00\x00\x00\x18ftypisom" + b"\x01" * 200])
+def test_malformed_files_raise_clean_errors(tmp_path, payload):
+    p = tmp_path / "bad.mp4"
+    p.write_bytes(payload)
+    with pytest.raises(Exception) as ei:
+        run_default(p, tmp_path / "work", LocalGridLog(tmp_path / "gridlog"))
+    assert not isinstance(ei.value, (SystemExit, KeyboardInterrupt))
+
+
+def test_truncated_real_video_does_not_verify(tmp_path):
+    from eval.simulator.render import SimConfig, simulate
+
+    tr = simulate(SimConfig(seed=5, duration_s=3, width=64, height=48, ref_margin_s=20), tmp_path, "t")
+    data = (tmp_path / tr["video"]).read_bytes()
+    cut = tmp_path / "trunc.mp4"
+    cut.write_bytes(data[: len(data) // 2])
+    try:
+        job = run_default(cut, tmp_path / "work", LocalGridLog(tmp_path / tr["gridlog_root"]))
+    except Exception:
+        return  # a clean failure is acceptable for a broken container
+    assert job.result is not None and job.result.verdict != Verdict.CONTRADICTED