diff --git a/docs/docs/configuration/custom_classification/state_classification.md b/docs/docs/configuration/custom_classification/state_classification.md
index b24ce17922..495e0173cc 100644
--- a/docs/docs/configuration/custom_classification/state_classification.md
+++ b/docs/docs/configuration/custom_classification/state_classification.md
@@ -85,6 +85,14 @@ An optional config, `save_attempts`, can be set as a key under the model name. T
 </TabItem>
 </ConfigTabs>
 
+## Review items
+
+When a model's state changes while its camera has an active review item, the change is recorded on that review item. This includes changes in the few seconds before the item starts, such as a garage door opening just before the car is detected. State changes never create or extend review items on their own, and the first state reported after Frigate starts is not recorded as a change.
+
+Recorded changes appear in the review item's data as `classification_state_changes` (see the [`frigate/reviews`](/integrations/mqtt#frigatereviews) MQTT topic) and are passed to [GenAI review summaries](/configuration/genai/review_summaries) as facts, so a description can note that a gate was opened during the activity.
+
+Change times are most accurate with `motion: true`. A model that only runs on an `interval` notices a change at its next run, so the change may be recorded late or attached to a later review item.
+
 ## Training the model
 
 Creating and training the model is done within the Frigate UI using the `Classification` page. The process consists of three steps:
diff --git a/docs/docs/configuration/genai/review_summaries.md b/docs/docs/configuration/genai/review_summaries.md
index a4155b4058..822da4852d 100644
--- a/docs/docs/configuration/genai/review_summaries.md
+++ b/docs/docs/configuration/genai/review_summaries.md
@@ -201,6 +201,8 @@ Review items are sent to the model as a sequence of still frames. Some models fo
 
 The notes come from tracking data rather than from the images, so they describe activity the model may not have picked up on its own. In testing with a person carrying three waste bins to the curb one at a time, `gemma4` described a single trip on every attempt with `frames`, and consistently described multiple trips with `annotated_frames`. Models that already handle these sequences well, such as the `qwen3-vl` family, gain little and should stay on `frames`.
 
+Changes reported by [state classification](/configuration/custom_classification/state_classification#review-items) models during the review item are listed in the prompt in both modes. `annotated_frames` also notes each change before the frame where it happened.
+
 Annotated mode also caps the number of frames, since the notes already establish the order of events and extra near-duplicate frames tend to crowd out the middle of a clip. Longer review items are sampled more sparsely as a result, and typically use fewer tokens than `frames` mode for the same item.
 
 :::note
diff --git a/docs/docs/integrations/mqtt.md b/docs/docs/integrations/mqtt.md
index 6363021188..6a3d576ae2 100644
--- a/docs/docs/integrations/mqtt.md
+++ b/docs/docs/integrations/mqtt.md
@@ -212,6 +212,7 @@ An `update` with the same ID will be published when:
 - The severity changes from `detection` to `alert`
 - Additional objects are detected
 - An object is recognized via face, lpr, etc.
+- A [state classification](/configuration/custom_classification/state_classification#review-items) model changes state
 
 When the review activity has ended a final `end` message is published.
 
@@ -235,7 +236,8 @@ When the review activity has ended a final `end` message is published.
       "objects": ["person", "car"],
       "sub_labels": [],
       "zones": [],
-      "audio": []
+      "audio": [],
+      "classification_state_changes": []
     }
   },
   "after": {
@@ -254,7 +256,16 @@ When the review activity has ended a final `end` message is published.
       "objects": ["person", "car"],
       "sub_labels": ["Bob"],
       "zones": ["front_yard"],
-      "audio": []
+      "audio": [],
+      "classification_state_changes": [
+        // verified changes of state classification models on this camera
+        {
+          "model": "front_gate",
+          "from": "closed",
+          "to": "open",
+          "timestamp": 1718987131.52
+        }
+      ]
     }
   }
 }
diff --git a/frigate/comms/detections_updater.py b/frigate/comms/detections_updater.py
index dff61c8a2a..fbd0750820 100644
--- a/frigate/comms/detections_updater.py
+++ b/frigate/comms/detections_updater.py
@@ -12,6 +12,7 @@ class DetectionTypeEnum(str, Enum):
     video = "video"
     audio = "audio"
     lpr = "lpr"
+    classification_state = "classification_state"
 
 
 class DetectionPublisher(Publisher):
diff --git a/frigate/data_processing/post/review_annotations.py b/frigate/data_processing/post/review_annotations.py
index da4568d48b..4f55a25410 100644
--- a/frigate/data_processing/post/review_annotations.py
+++ b/frigate/data_processing/post/review_annotations.py
@@ -1,10 +1,10 @@
 """Frame annotations derived from object tracking data.
 
 Builds short notes describing what changed during a review item, keyed to the
-frames sampled from it. Everything here comes from tracked object data already
-in the database (each event's `path_data` trajectory and the timeline's
-stationary/active changes), so the notes can be stated to the model as fact
-rather than as something it must perceive.
+frames sampled from it. Everything here comes from data already recorded
+(each event's `path_data` trajectory, the timeline's stationary/active
+changes, and the review item's state classification changes), so the notes
+can be stated to the model as fact rather than as something it must perceive.
 """
 
 import logging
@@ -95,6 +95,15 @@ def event_name(event: dict[str, Any]) -> str:
     return f"{article} {label}"
 
 
+def describe_classification_change(change: dict[str, Any]) -> str:
+    """Phrase a state classification change, e.g. 'front gate changed from
+    closed to open'."""
+    model = str(change["model"]).replace("_", " ")
+    before = str(change["from"]).replace("_", " ")
+    after = str(change["to"]).replace("_", " ")
+    return f"{model} changed from {before} to {after}"
+
+
 def path_legs(points: list[Point]) -> list[Leg]:
     """Split a trajectory into runs of travel in a consistent direction.
 
@@ -359,13 +368,15 @@ def get_state_changes(detection_ids: list[str]) -> list[dict[str, Any]]:
 def build_frame_captions(
     detection_ids: list[str],
     frame_times: list[float],
+    classification_changes: Sequence[dict[str, Any]] = (),
 ) -> list[str]:
     """A caption for each sampled frame, in frame order.
 
     Every frame gets its index and elapsed time so the model can tell them
-    apart; frames where something changed also carry the tracker notes for
-    that moment. Returns an empty list when there is nothing to say, which
-    callers treat as a reason to fall back to sending plain frames.
+    apart; frames where something changed also carry the tracker and state
+    classification notes for that moment. Returns an empty list when there is
+    nothing to say, which callers treat as a reason to fall back to sending
+    plain frames.
     """
     if not frame_times:
         return []
@@ -376,8 +387,19 @@ def build_frame_captions(
         logger.debug("No tracked events found for review item, skipping annotations")
         return []
 
-    timeline = build_timeline(events, frame_times[-1], get_state_changes(detection_ids))
-    buckets = annotations_by_frame(timeline, frame_times)
+    span_end = frame_times[-1]
+    timeline = [
+        (timestamp, f"[tracker] {note}")
+        for timestamp, note in build_timeline(
+            events, span_end, get_state_changes(detection_ids)
+        )
+    ]
+    timeline.extend(
+        (change["timestamp"], f"[state] {describe_classification_change(change)}")
+        for change in classification_changes
+        if change["timestamp"] <= span_end
+    )
+    buckets = annotations_by_frame(sorted(timeline, key=lambda m: m[0]), frame_times)
 
     if not buckets:
         return []
@@ -388,7 +410,7 @@ def build_frame_captions(
 
     for index, timestamp in enumerate(frame_times):
         lines = [f"Frame {index + 1} of {total} (+{timestamp - origin:.1f}s):"]
-        lines.extend(f"[tracker] {note}" for note in buckets.get(index, []))
+        lines.extend(buckets.get(index, []))
         captions.append("\n".join(lines))
 
     return captions
diff --git a/frigate/data_processing/post/review_descriptions.py b/frigate/data_processing/post/review_descriptions.py
index dbc0b9fcf1..58e105736b 100644
--- a/frigate/data_processing/post/review_descriptions.py
+++ b/frigate/data_processing/post/review_descriptions.py
@@ -40,7 +40,7 @@ from frigate.util.image import get_image_from_recording
 
 from ..post.api import PostProcessorApi
 from ..types import DataProcessorMetrics
-from .review_annotations import build_frame_captions
+from .review_annotations import build_frame_captions, describe_classification_change
 
 logger = logging.getLogger(__name__)
 
@@ -254,6 +254,10 @@ class ReviewDescriptionProcessor(PostProcessorApi):
                     "start_time": r["start_time"],
                     "end_time": r["end_time"],
                     "metadata": r["data"]["metadata"],
+                    "state_changes": [
+                        describe_classification_change(change)
+                        for change in sorted_classification_state_changes(r["data"])
+                    ],
                 }
                 for r in (
                     ReviewSegment.select(
@@ -298,6 +302,9 @@ class ReviewDescriptionProcessor(PostProcessorApi):
                 primary_item["start_time"] = primary_seg["start_time"]
                 primary_item["end_time"] = primary_seg["end_time"]
 
+                if primary_seg["state_changes"]:
+                    primary_item["state_changes"] = primary_seg["state_changes"]
+
                 # Find overlapping contextual items from other cameras
                 primary_start = primary_seg["start_time"]
                 primary_end = primary_seg["end_time"]
@@ -324,6 +331,9 @@ class ReviewDescriptionProcessor(PostProcessorApi):
                             contextual_item["camera"] = seg_camera
                             contextual_item["start_time"] = seg_start
                             contextual_item["end_time"] = seg_end
+
+                            if seg["state_changes"]:
+                                contextual_item["state_changes"] = seg["state_changes"]
                             contextual_items.append(contextual_item)
                             seen_contextual_cameras.add(seg_camera)
 
@@ -439,6 +449,7 @@ class ReviewDescriptionProcessor(PostProcessorApi):
             captions = build_frame_captions(
                 final_data["data"].get("detections") or [],
                 [timestamp for _, timestamp in frames],
+                sorted_classification_state_changes(final_data["data"]),
             )
 
             if not captions:
@@ -688,6 +699,39 @@ def get_recording_buffer_extension(duration: float) -> float:
     return buffer_extension
 
 
+def sorted_classification_state_changes(
+    review_data: dict[str, Any],
+) -> list[dict[str, Any]]:
+    """A review item's state classification changes in time order."""
+    return sorted(
+        review_data.get("classification_state_changes") or [],
+        key=lambda change: change["timestamp"],
+    )
+
+
+def format_classification_state_changes(
+    changes: list[dict[str, Any]], start_time: float, end_time: float
+) -> list[str]:
+    """Phrase state classification changes with their timing in the activity.
+
+    Changes are attached while the review item is active, which runs past its
+    end_time by the review cutoff, and a few seconds before its start.
+    """
+    lines = []
+
+    for change in changes:
+        if change["timestamp"] < start_time:
+            when = "just before the activity started"
+        elif change["timestamp"] > end_time:
+            when = "after the activity ended"
+        else:
+            when = f"{round(change['timestamp'] - start_time)}s into the activity"
+
+        lines.append(f"{describe_classification_change(change)}, {when}")
+
+    return lines
+
+
 def run_analysis(
     requestor: InterProcessRequestor,
     genai_client: GenAIClient,
@@ -743,6 +787,13 @@ def run_analysis(
                 unified_objects.append(object_type)
 
     analytics_data["unified_objects"] = unified_objects
+    analytics_data["classification_state_changes"] = (
+        format_classification_state_changes(
+            sorted_classification_state_changes(final_data["data"]),
+            final_data["start_time"],
+            final_data["end_time"],
+        )
+    )
 
     metadata = genai_client.generate_review_description(
         analytics_data,
diff --git a/frigate/data_processing/real_time/custom_classification.py b/frigate/data_processing/real_time/custom_classification.py
index 9ba21893cf..993618d053 100644
--- a/frigate/data_processing/real_time/custom_classification.py
+++ b/frigate/data_processing/real_time/custom_classification.py
@@ -134,15 +134,20 @@ class CustomStateClassificationProcessor(DeferredRealtimeProcessorApi):
         # Don't save if state is stable (detected_state == current_state) AND score is 100%
         return False
 
-    def verify_state_change(self, camera: str, detected_state: str) -> str | None:
+    def verify_state_change(
+        self, camera: str, detected_state: str, timestamp: float
+    ) -> tuple[str | None, float] | None:
         """
         Verify state change requires 3 consecutive identical states before publishing.
-        Returns state to publish or None if verification not complete.
+        Returns (previous state, time the new state was first seen) once verified,
+        or None if verification not complete. The previous state is None for the
+        first state verified on a camera.
         """
         if camera not in self.state_history:
             self.state_history[camera] = {
                 "current_state": None,
                 "pending_state": None,
+                "pending_since": 0.0,
                 "consecutive_count": 0,
             }
 
@@ -157,12 +162,14 @@ class CustomStateClassificationProcessor(DeferredRealtimeProcessorApi):
             verification["consecutive_count"] += 1
 
             if verification["consecutive_count"] >= 3:
+                previous_state = verification["current_state"]
                 verification["current_state"] = detected_state
                 verification["pending_state"] = None
                 verification["consecutive_count"] = 0
-                return detected_state
+                return previous_state, verification["pending_since"]
         else:
             verification["pending_state"] = detected_state
+            verification["pending_since"] = timestamp
             verification["consecutive_count"] = 1
             logger.debug(
                 f"New state '{detected_state}' detected for {camera}, need {3 - verification['consecutive_count']} more consecutive detections"
@@ -340,16 +347,19 @@ class CustomStateClassificationProcessor(DeferredRealtimeProcessorApi):
             )
             return
 
-        verified_state = self.verify_state_change(camera, detected_state)
+        verified = self.verify_state_change(camera, detected_state, timestamp)
 
-        if verified_state is not None:
+        if verified is not None:
+            previous_state, changed_at = verified
             self._emit_result(
                 {
                     "type": "classification",
                     "processor": "state",
                     "model_name": self.model_config.name,
                     "camera": camera,
-                    "state": verified_state,
+                    "state": detected_state,
+                    "previous_state": previous_state,
+                    "timestamp": changed_at,
                 }
             )
 
diff --git a/frigate/embeddings/maintainer.py b/frigate/embeddings/maintainer.py
index 34ca862aab..f1055f26f5 100644
--- a/frigate/embeddings/maintainer.py
+++ b/frigate/embeddings/maintainer.py
@@ -11,7 +11,11 @@ from typing import Any
 from peewee import DoesNotExist
 
 from frigate.comms.config_updater import ConfigSubscriber
-from frigate.comms.detections_updater import DetectionSubscriber, DetectionTypeEnum
+from frigate.comms.detections_updater import (
+    DetectionPublisher,
+    DetectionSubscriber,
+    DetectionTypeEnum,
+)
 from frigate.comms.embeddings_updater import (
     EmbeddingsRequestEnum,
     EmbeddingsResponder,
@@ -168,6 +172,7 @@ class EmbeddingMaintainer(threading.Thread):
         )
         self.review_subscriber = ReviewDataSubscriber("")
         self.detection_subscriber = DetectionSubscriber(DetectionTypeEnum.video.value)
+        self.detection_publisher = DetectionPublisher(DetectionTypeEnum.all.value)
         self.embeddings_responder = EmbeddingsResponder()
         self.frame_manager = SharedMemoryFrameManager()
 
@@ -356,6 +361,7 @@ class EmbeddingMaintainer(threading.Thread):
         self.event_end_subscriber.stop()
         self.recordings_subscriber.stop()
         self.detection_subscriber.stop()
+        self.detection_publisher.stop()
         self.event_metadata_publisher.stop()
         self.event_metadata_subscriber.stop()
         self.embeddings_responder.stop()
@@ -851,6 +857,21 @@ class EmbeddingMaintainer(threading.Thread):
                         f"{result['camera']}/classification/{result['model_name']}",
                         result["state"],
                     )
+
+                    # the first state verified after startup is not a change
+                    if result["previous_state"] is not None:
+                        self.detection_publisher.publish(
+                            (
+                                result["camera"],
+                                {
+                                    "model": result["model_name"],
+                                    "from": result["previous_state"],
+                                    "to": result["state"],
+                                    "timestamp": result["timestamp"],
+                                },
+                            ),
+                            DetectionTypeEnum.classification_state.value,
+                        )
                 elif result["processor"] == "object":
                     object_id = result["object_id"]
                     camera = result["camera"]
diff --git a/frigate/genai/prompts.py b/frigate/genai/prompts.py
index 8a7460f4a3..f30d9fce4a 100644
--- a/frigate/genai/prompts.py
+++ b/frigate/genai/prompts.py
@@ -104,6 +104,21 @@ def build_review_description_prompt(
         else:
             return "\n- (No objects detected)"
 
+    def get_state_changes_section() -> str:
+        # empty when nothing changed so the prompt is otherwise unaffected
+        changes = review_data.get("classification_state_changes")
+
+        if not changes:
+            return ""
+
+        return (
+            "\n\n## State Changes\n\n"
+            "The camera's state classifiers watch fixed areas of the scene and "
+            "reported these changes. They come from the classifiers rather than "
+            "from the images, and they are reliable. Describe each one where it "
+            "fits in the sequence of events.\n- " + "\n- ".join(changes)
+        )
+
     fields = get_review_field_guidelines(response_style)
     frame_guidance = f"\n{FRAME_ANNOTATION_GUIDANCE}" if frame_captions else ""
 
@@ -145,7 +160,7 @@ Respond with a JSON object matching the provided schema. Field-specific guidance
 - Camera: {review_data["camera"]}
 - Total frames: {len(thumbnails)} (Frame 1 = earliest, Frame {len(thumbnails)} = latest){frame_guidance}
 - Activity started at {review_data["start"]} and lasted {review_data["duration"]} seconds
-- Zones involved: {", ".join(review_data["zones"]) if review_data["zones"] else "None"}
+- Zones involved: {", ".join(review_data["zones"]) if review_data["zones"] else "None"}{get_state_changes_section()}
 
 ## Objects in Scene
 
@@ -196,6 +211,17 @@ def build_review_summary_prompt(
         f" to "
         f"{datetime.datetime.fromtimestamp(end_ts).strftime('%B %d, %Y at %I:%M %p')}"
     )
+    has_state_changes = any(
+        "state_changes" in item
+        for event in events
+        for item in [event, *event.get("context", [])]
+    )
+    state_changes_format = (
+        '\n- "state_changes" (only on some events): changes to monitored areas '
+        "reported by the camera's state classifiers, which are reliable"
+        if has_state_changes
+        else ""
+    )
     prompt = f"""
 You are a security officer writing a concise security report.
 
@@ -203,7 +229,7 @@ Time range: {time_range}
 
 Input format: Each event is a JSON object with:
 - "title", "scene", "confidence", "potential_threat_level" (0-2), "other_concerns", "camera", "time", "start_time", "end_time"
-- "context": array of related events from other cameras that occurred during overlapping time periods
+- "context": array of related events from other cameras that occurred during overlapping time periods{state_changes_format}
 
 **Note: Use the "scene" field for event descriptions in the report. Ignore any "shortSummary" field if present.**
 
diff --git a/frigate/record/maintainer.py b/frigate/record/maintainer.py
index e4151069f9..9aa15752c7 100644
--- a/frigate/record/maintainer.py
+++ b/frigate/record/maintainer.py
@@ -1127,6 +1127,7 @@ class RecordingMaintainer(threading.Thread):
                 elif (
                     topic == DetectionTypeEnum.api.value
                     or topic == DetectionTypeEnum.lpr.value
+                    or topic == DetectionTypeEnum.classification_state.value
                 ):
                     continue
 
diff --git a/frigate/review/maintainer.py b/frigate/review/maintainer.py
index e1017dd0ce..b770bbd8e0 100644
--- a/frigate/review/maintainer.py
+++ b/frigate/review/maintainer.py
@@ -40,6 +40,10 @@ logger = logging.getLogger(__name__)
 THUMB_HEIGHT = 180
 THUMB_WIDTH = 320
 
+# seconds before a review item starts that a state classification change is
+# still attached to it, e.g. a garage door opening before the car is visible
+CLASSIFICATION_STATE_PRE_ROLL = 5
+
 
 class PendingReviewSegment:
     def __init__(
@@ -61,6 +65,7 @@ class PendingReviewSegment:
         self.sub_labels = sub_labels
         self.zones = zones
         self.audio = audio
+        self.classification_state_changes: list[dict[str, Any]] = []
         self.thumb_time: float | None = None
         self.last_alert_time: float | None = None
         self.last_detection_time: float = frame_time
@@ -162,6 +167,7 @@ class PendingReviewSegment:
                     "sub_labels": list(self.sub_labels.values()),
                     "zones": self.zones,
                     "audio": list(self.audio),
+                    "classification_state_changes": self.classification_state_changes,
                     "thumb_time": self.thumb_time,
                     "metadata": None,
                 },
@@ -293,6 +299,9 @@ class ReviewSegmentMaintainer(threading.Thread):
         # manual events
         self.indefinite_events: dict[str, dict[str, Any]] = {}
 
+        # state classification changes seen while a camera had no review item
+        self.recent_classification_state_changes: dict[str, list[dict[str, Any]]] = {}
+
         # ensure dirs
         Path(os.path.join(CLIPS_DIR, "review")).mkdir(exist_ok=True)
 
@@ -374,6 +383,43 @@ class ReviewSegmentMaintainer(threading.Thread):
         self.active_review_segments[segment.camera] = None
         return end_time
 
+    def _activate_segment(self, segment: PendingReviewSegment) -> None:
+        """Make a segment the camera's active one, attaching any state
+        classification changes seen just before it started."""
+        self.active_review_segments[segment.camera] = segment
+        recent = self.recent_classification_state_changes.pop(segment.camera, [])
+        segment.classification_state_changes.extend(
+            c
+            for c in recent
+            if c["timestamp"] >= segment.start_time - CLASSIFICATION_STATE_PRE_ROLL
+        )
+
+    def handle_classification_state_change(
+        self, camera: str, change: dict[str, Any]
+    ) -> None:
+        """Attach a verified state classification change to the active segment.
+
+        State changes never start, extend, or upgrade a segment. A change seen
+        with no active segment is held briefly for a segment starting right
+        after it.
+        """
+        segment = self.active_review_segments.get(camera)
+
+        if segment is None:
+            cutoff = change["timestamp"] - CLASSIFICATION_STATE_PRE_ROLL
+            self.recent_classification_state_changes[camera] = [
+                c
+                for c in self.recent_classification_state_changes.get(camera, [])
+                if c["timestamp"] >= cutoff
+            ] + [change]
+            return
+
+        prev_data = segment.get_data(False)
+        segment.classification_state_changes.append(change)
+        self._publish_segment_update(
+            segment, self.config.cameras[camera], None, [], prev_data
+        )
+
     def forcibly_end_segment(self, camera: str) -> Any:
         """Forcibly end the pending segment for a camera."""
         segment = self.active_review_segments.get(camera)
@@ -422,6 +468,7 @@ class ReviewSegmentMaintainer(threading.Thread):
         """Close out a deleted camera's segment so a reused name cannot inherit it."""
         self.forcibly_end_segment(camera)
         self.indefinite_events.pop(camera, None)
+        self.recent_classification_state_changes.pop(camera, None)
 
     def update_existing_segment(
         self,
@@ -579,7 +626,7 @@ class ReviewSegmentMaintainer(threading.Thread):
                             audio=set(),
                             zones=list(new_zones),
                         )
-                        self.active_review_segments[segment.camera] = new_segment
+                        self._activate_segment(new_segment)
                         self._publish_segment_start(new_segment)
                         new_segment.last_detection_time = last_detection_time
             elif segment.severity == SeverityEnum.detection and frame_time > (
@@ -639,7 +686,7 @@ class ReviewSegmentMaintainer(threading.Thread):
                     audio=set(),
                     zones=zones,
                 )
-                self.active_review_segments[camera] = new_segment
+                self._activate_segment(new_segment)
 
                 try:
                     yuv_frame = self.frame_manager.get(
@@ -713,6 +760,10 @@ class ReviewSegmentMaintainer(threading.Thread):
 
                 if camera not in self.indefinite_events:
                     self.indefinite_events[camera] = {}
+            elif topic == DetectionTypeEnum.classification_state.value:
+                (camera, classification_change) = data
+            else:
+                continue
 
             if camera not in self.config.cameras:
                 continue
@@ -723,6 +774,10 @@ class ReviewSegmentMaintainer(threading.Thread):
             ):
                 continue
 
+            if topic == DetectionTypeEnum.classification_state:
+                self.handle_classification_state_change(camera, classification_change)
+                continue
+
             current_segment = self.active_review_segments.get(camera)
 
             # Check if the current segment should be processed based on enabled settings
@@ -864,14 +919,16 @@ class ReviewSegmentMaintainer(threading.Thread):
                                 severity = SeverityEnum.detection
 
                     if severity:
-                        self.active_review_segments[camera] = PendingReviewSegment(
-                            camera,
-                            frame_time,
-                            severity,
-                            {},
-                            {},
-                            [],
-                            detections,
+                        self._activate_segment(
+                            PendingReviewSegment(
+                                camera,
+                                frame_time,
+                                severity,
+                                {},
+                                {},
+                                [],
+                                detections,
+                            )
                         )
                 elif topic == DetectionTypeEnum.api:
                     severity = self.get_manual_event_severity(
@@ -888,7 +945,7 @@ class ReviewSegmentMaintainer(threading.Thread):
                             [],
                             set(),
                         )
-                        self.active_review_segments[camera] = api_segment
+                        self._activate_segment(api_segment)
 
                         if manual_info["state"] == ManualEventState.start:
                             self.indefinite_events[camera][manual_info["event_id"]] = (
@@ -915,7 +972,7 @@ class ReviewSegmentMaintainer(threading.Thread):
                             [],
                             set(),
                         )
-                        self.active_review_segments[camera] = lpr_segment
+                        self._activate_segment(lpr_segment)
 
                         if manual_info["state"] == ManualEventState.start:
                             self.indefinite_events[camera][manual_info["event_id"]] = (
diff --git a/frigate/test/test_camera_lifecycle.py b/frigate/test/test_camera_lifecycle.py
index d9ce8ae537..1b5b8920ac 100644
--- a/frigate/test/test_camera_lifecycle.py
+++ b/frigate/test/test_camera_lifecycle.py
@@ -179,12 +179,16 @@ class TestReviewMaintainerRemoval(unittest.TestCase):
         maintainer = ReviewSegmentMaintainer.__new__(ReviewSegmentMaintainer)
         maintainer.active_review_segments = {"deleted_cam": MagicMock()}
         maintainer.indefinite_events = {"deleted_cam": {"1234.5-abcdef": 1.0}}
+        maintainer.recent_classification_state_changes = {
+            "deleted_cam": [{"model": "gate", "from": "a", "to": "b", "timestamp": 1.0}]
+        }
         maintainer.forcibly_end_segment = MagicMock()
 
         maintainer._handle_camera_removed("deleted_cam")
 
         maintainer.forcibly_end_segment.assert_called_once_with("deleted_cam")
         self.assertNotIn("deleted_cam", maintainer.indefinite_events)
+        self.assertNotIn("deleted_cam", maintainer.recent_classification_state_changes)
 
 
 class TestAutotrackerMoveQueue(unittest.TestCase):
diff --git a/frigate/test/test_genai_prompts.py b/frigate/test/test_genai_prompts.py
index 2d6d97c531..b8129ac54b 100644
--- a/frigate/test/test_genai_prompts.py
+++ b/frigate/test/test_genai_prompts.py
@@ -7,6 +7,7 @@ from frigate.genai.prompts import (
     REVIEW_DESCRIPTION_FIELD_GUIDELINES,
     REVIEW_RESPONSE_STYLES,
     build_review_description_prompt,
+    build_review_summary_prompt,
     get_review_field_guidelines,
 )
 
@@ -83,5 +84,49 @@ class TestReviewResponseStyle(unittest.TestCase):
         )
 
 
+class TestClassificationStateChanges(unittest.TestCase):
+    def _build_prompt(self, **extra) -> str:
+        review_data = {
+            "camera": "Front Door",
+            "start": "Monday, 09:30 AM",
+            "duration": 25,
+            "zones": [],
+            "unified_objects": ["person"],
+            **extra,
+        }
+        return build_review_description_prompt(
+            review_data, [b"fake-image"], [], None, "activity context"
+        )
+
+    def test_no_changes_leaves_prompt_unchanged(self):
+        self.assertEqual(
+            self._build_prompt(classification_state_changes=[]),
+            self._build_prompt(),
+        )
+        self.assertNotIn("## State Changes", self._build_prompt())
+
+    def test_changes_are_listed_before_objects(self):
+        change = "front gate changed from closed to open, 12s into the activity"
+        prompt = self._build_prompt(classification_state_changes=[change])
+        self.assertIn(f"\n- {change}\n\n## Objects in Scene", prompt)
+        self.assertLess(
+            prompt.index("## Sequence Details"), prompt.index("## State Changes")
+        )
+
+    def test_summary_describes_state_changes_only_when_present(self):
+        event = {"title": "Person at door", "camera": "Front Door", "context": []}
+        without = build_review_summary_prompt(0, 3600, [event], None)
+        self.assertNotIn('"state_changes"', without)
+
+        context_event = {
+            **event,
+            "context": [
+                {"camera": "Driveway", "state_changes": ["gate changed from a to b"]}
+            ],
+        }
+        with_changes = build_review_summary_prompt(0, 3600, [context_event], None)
+        self.assertIn('- "state_changes"', with_changes)
+
+
 if __name__ == "__main__":
     unittest.main()
diff --git a/frigate/test/test_review_annotations.py b/frigate/test/test_review_annotations.py
index b58b2b2fa8..e163babaf1 100644
--- a/frigate/test/test_review_annotations.py
+++ b/frigate/test/test_review_annotations.py
@@ -1,10 +1,13 @@
 """Tests for tracker-derived review frame annotations."""
 
 import unittest
+from unittest.mock import patch
 
 from frigate.data_processing.post.review_annotations import (
     annotations_by_frame,
+    build_frame_captions,
     build_timeline,
+    describe_classification_change,
     describe_heading,
     describe_position,
     event_name,
@@ -312,5 +315,56 @@ class TestFrameBucketing(unittest.TestCase):
         self.assertEqual(annotations_by_frame([(1.0, "x")], []), {})
 
 
+class TestClassificationChangeCaptions(unittest.TestCase):
+    def setUp(self):
+        person = track(
+            "1789481994.684479-lpyc2z",
+            "person",
+            0.0,
+            straight_path((0.9, 0.6), (0.4, 0.3), 10, 0.0),
+        )
+        patcher = patch(
+            "frigate.data_processing.post.review_annotations.get_tracked_events",
+            return_value=[person],
+        )
+        patcher.start()
+        self.addCleanup(patcher.stop)
+        patcher = patch(
+            "frigate.data_processing.post.review_annotations.get_state_changes",
+            return_value=[],
+        )
+        patcher.start()
+        self.addCleanup(patcher.stop)
+
+    def test_change_is_phrased_without_underscores(self):
+        self.assertEqual(
+            describe_classification_change(
+                {"model": "trash_day", "from": "no_bins", "to": "bins_at_curb"}
+            ),
+            "trash day changed from no bins to bins at curb",
+        )
+
+    def test_change_is_noted_before_the_frame_it_precedes(self):
+        change = {"model": "front_gate", "from": "closed", "to": "open"}
+        captions = build_frame_captions(
+            ["1789481994.684479-lpyc2z"],
+            [0.0, 10.0, 20.0],
+            [{**change, "timestamp": 12.0}],
+        )
+        self.assertEqual(
+            captions[2],
+            "Frame 3 of 3 (+20.0s):\n[state] front gate changed from closed to open",
+        )
+        self.assertTrue(captions[0].splitlines()[1].startswith("[tracker] "))
+
+    def test_change_after_the_last_frame_is_dropped(self):
+        captions = build_frame_captions(
+            ["1789481994.684479-lpyc2z"],
+            [0.0, 10.0, 20.0],
+            [{"model": "gate", "from": "a", "to": "b", "timestamp": 25.0}],
+        )
+        self.assertFalse(any("[state]" in caption for caption in captions))
+
+
 if __name__ == "__main__":
     unittest.main()
diff --git a/frigate/test/test_review_classification_state.py b/frigate/test/test_review_classification_state.py
new file mode 100644
index 0000000000..f0a6bfc49b
--- /dev/null
+++ b/frigate/test/test_review_classification_state.py
@@ -0,0 +1,181 @@
+"""Tests for attaching state classification changes to review items."""
+
+import unittest
+from unittest.mock import MagicMock
+
+from frigate.config import FrigateConfig
+from frigate.data_processing.post.review_descriptions import (
+    format_classification_state_changes,
+)
+from frigate.data_processing.real_time.custom_classification import (
+    CustomStateClassificationProcessor,
+)
+from frigate.review.maintainer import (
+    CLASSIFICATION_STATE_PRE_ROLL,
+    PendingReviewSegment,
+    ReviewSegmentMaintainer,
+)
+from frigate.review.types import SeverityEnum
+
+CONFIG = """
+mqtt:
+  enabled: False
+cameras:
+  front_door:
+    ffmpeg:
+      inputs:
+        - path: rtsp://10.0.0.1:554/video
+          roles:
+            - detect
+    detect:
+      width: 1920
+      height: 1080
+      fps: 5
+"""
+
+
+def gate_change(timestamp: float, before: str = "closed", after: str = "open"):
+    return {"model": "front_gate", "from": before, "to": after, "timestamp": timestamp}
+
+
+class TestVerifyStateChange(unittest.TestCase):
+    def setUp(self):
+        self.processor = CustomStateClassificationProcessor.__new__(
+            CustomStateClassificationProcessor
+        )
+        self.processor.state_history = {}
+
+    def verify(self, state: str, timestamp: float):
+        return self.processor.verify_state_change("front_door", state, timestamp)
+
+    def test_first_verified_state_has_no_previous_state(self):
+        self.assertIsNone(self.verify("closed", 1.0))
+        self.assertIsNone(self.verify("closed", 2.0))
+        self.assertEqual(self.verify("closed", 3.0), (None, 1.0))
+
+    def test_change_reports_previous_state_and_first_sighting(self):
+        for timestamp in (1.0, 2.0, 3.0):
+            self.verify("closed", timestamp)
+
+        self.assertIsNone(self.verify("open", 10.0))
+        self.assertIsNone(self.verify("open", 11.0))
+        self.assertEqual(self.verify("open", 12.0), ("closed", 10.0))
+
+    def test_interrupted_verification_restarts_the_first_sighting(self):
+        for timestamp in (1.0, 2.0, 3.0):
+            self.verify("closed", timestamp)
+
+        self.verify("open", 10.0)
+        self.verify("closed", 11.0)
+        self.verify("open", 20.0)
+        self.verify("open", 21.0)
+        self.assertEqual(self.verify("open", 22.0), ("closed", 20.0))
+
+
+class TestReviewSegmentAttachment(unittest.TestCase):
+    def setUp(self):
+        self.maintainer = ReviewSegmentMaintainer.__new__(ReviewSegmentMaintainer)
+        self.maintainer.config = FrigateConfig.parse_yaml(CONFIG)
+        self.maintainer.active_review_segments = {}
+        self.maintainer.recent_classification_state_changes = {}
+        self.maintainer._publish_segment_update = MagicMock()
+
+    def segment(self, start_time: float) -> PendingReviewSegment:
+        return PendingReviewSegment(
+            "front_door",
+            start_time,
+            SeverityEnum.alert,
+            {"1.0-abcdef": "person"},
+            {},
+            [],
+            set(),
+        )
+
+    def test_change_during_segment_is_attached_and_published(self):
+        segment = self.segment(100.0)
+        self.maintainer.active_review_segments["front_door"] = segment
+
+        self.maintainer.handle_classification_state_change(
+            "front_door", gate_change(110.0)
+        )
+
+        self.assertEqual(segment.classification_state_changes, [gate_change(110.0)])
+        self.maintainer._publish_segment_update.assert_called_once()
+        prev_data = self.maintainer._publish_segment_update.call_args.args[4]
+        self.assertEqual(prev_data["data"]["classification_state_changes"], [])
+        self.assertEqual(
+            segment.get_data(False)["data"]["classification_state_changes"],
+            [gate_change(110.0)],
+        )
+
+    def test_change_never_starts_a_segment(self):
+        self.maintainer.handle_classification_state_change(
+            "front_door", gate_change(110.0)
+        )
+
+        self.assertIsNone(self.maintainer.active_review_segments.get("front_door"))
+        self.maintainer._publish_segment_update.assert_not_called()
+
+    def test_change_just_before_a_segment_is_attached_when_it_starts(self):
+        self.maintainer.handle_classification_state_change(
+            "front_door", gate_change(98.0)
+        )
+        segment = self.segment(100.0)
+
+        self.maintainer._activate_segment(segment)
+
+        self.assertIs(self.maintainer.active_review_segments["front_door"], segment)
+        self.assertEqual(segment.classification_state_changes, [gate_change(98.0)])
+        self.assertNotIn(
+            "front_door", self.maintainer.recent_classification_state_changes
+        )
+
+    def test_change_long_before_a_segment_is_not_attached(self):
+        self.maintainer.handle_classification_state_change(
+            "front_door", gate_change(100.0 - CLASSIFICATION_STATE_PRE_ROLL - 1)
+        )
+        segment = self.segment(100.0)
+
+        self.maintainer._activate_segment(segment)
+
+        self.assertEqual(segment.classification_state_changes, [])
+
+    def test_held_changes_are_pruned(self):
+        self.maintainer.handle_classification_state_change(
+            "front_door", gate_change(10.0)
+        )
+        self.maintainer.handle_classification_state_change(
+            "front_door", gate_change(50.0, "open", "closed")
+        )
+
+        self.assertEqual(
+            self.maintainer.recent_classification_state_changes["front_door"],
+            [gate_change(50.0, "open", "closed")],
+        )
+
+
+class TestChangeTiming(unittest.TestCase):
+    def test_changes_are_placed_relative_to_the_activity(self):
+        lines = format_classification_state_changes(
+            [
+                gate_change(98.0),
+                gate_change(112.4, "open", "closed"),
+                gate_change(140.0),
+            ],
+            start_time=100.0,
+            end_time=130.0,
+        )
+
+        self.assertEqual(
+            lines,
+            [
+                "front gate changed from closed to open, "
+                "just before the activity started",
+                "front gate changed from open to closed, 12s into the activity",
+                "front gate changed from closed to open, after the activity ended",
+            ],
+        )
+
+
+if __name__ == "__main__":
+    unittest.main()