diff --git a/CLAUDE.md b/CLAUDE.md
index c07f0c67..10cce58b 100644
--- a/CLAUDE.md
+++ b/CLAUDE.md
@@ -61,6 +61,13 @@ python3 tools/analyse_framesync.py /home/pi/controller_share/my-session/20260703
 python3 tools/make_aligned_video.py /path/to/session [--output out.mp4] [--layout side|stack|grid]
 # e.g.:
 python3 tools/make_aligned_video.py /home/pi/controller_share/my-session
+
+# Compose a layout video from a session's cameras — no PTP sync_mode required, aligns by
+# each camera's own per-frame timestamp instead (works on unsynced sessions too); no
+# ffmpeg dependency (OpenCV only). Prototype for the frontend feature idea below.
+python3 src/controller/video_compose.py /path/to/session/date_dir [--output out.mp4] [--layout auto|loom]
+# e.g.:
+python3 src/controller/video_compose.py /home/pi/controller_share/my-session/20260703
 ```
 
 ### Installation & role assignment
@@ -293,6 +300,14 @@ These are larger structural issues that require significant refactoring. Recorde
 - [x] **Health schema is duplicated** — canonical `ModuleHealthSnapshot` dataclass lives in `src/shared/health.py`; both `src/modules/health.py` and `src/controller/health.py` import from it.
 - [ ] **No authentication on the command bus** — see the Security section (2026-07-27 review) above for the full detail, including the identity-hijack path and the unauthenticated-RCE chain this enables via `update_saviour`.
 
+### Feature ideas
+
+- [ ] **Frontend: session-detail "compose aggregated video" tool** (proposed 2026-08-05) — `SessionList.jsx` currently only offers raw file downloads (individual files or a zip, via `web.py`'s `/api/sessions/<name>/download[...]` routes) for a stopped session; there is no in-browser preview or compositing of a session's multiple camera feeds into one video. Idea: let an operator pick a layout (which camera goes where, how large) from the session-detail view and have the controller render a single composited video server-side, plus optionally overlay a microphone recording's spectrogram and/or a TTL/event module's timeseries as additional panes/tracks. This is genuinely three separate pieces of new infrastructure, not one feature:
+  - **Video layout compositing** — the bounded, reusable part. `src/controller/video_compose.py` (added 2026-08-05) is a standalone CLI prototype: it discovers each camera module's `.ts`/`.mp4` + `*_timestamps.csv` under a session's date directory, resamples every stream onto one common wall-clock grid built from each frame's real `timestamp_ns` (not raw frame index — cameras in a session can run at genuinely different real framerates, see Hardware gotchas), and composites them via OpenCV (no ffmpeg dependency, works even on a dev machine with no system ffmpeg). It has an `auto` grid layout for an arbitrary camera count plus a named `loom` preset (LoomCam large-left / Home top-right / ScreenCam bottom-right) matching the loom rig's actual 3-camera set. Not yet wired into `web.py` — no Flask route, no frontend layout picker, no job queue/progress reporting for a render that could take a while on a Pi. Next steps if this gets picked up: (1) a POST endpoint that takes a layout spec and kicks off a background render (reuse the `export_queue.py`/threaded-job patterns already in this codebase rather than blocking a request); (2) a minimal frontend layout picker (even a fixed set of named presets to start, rather than full drag-resize); (3) generalize `_loom_regions`'s named-preset approach into something manifest-driven once there's a second real preset to justify it, rather than guessing the right abstraction from one example.
+  - **Audio/spectrogram overlay** — not reusable from existing code despite appearances. `src/modules/examples/microphone/microphone_module.py` already renders a spectrogram, but only live (cv2+numpy FFT, MJPEG monitoring stream during recording) — turning that into a post-hoc renderer from a saved audio file is new work, not a wire-up.
+  - **TTL/event timeseries plot** — genuinely from zero. No charting library exists anywhere in the frontend (`package.json` has no Chart.js/Plotly/D3/recharts); picking one and building a first timeseries component is its own small design decision, independent of the video work.
+  Recommendation if this moves forward: ship video-layout compositing as its own PR first (it already has a working prototype and reuses nothing speculative), then treat spectrogram overlay and TTL charting as separate follow-on PRs — bundling all three into one v1 risks stalling on the two components that don't have a head start.
+
 ### Tests
 
 - [x] **Config merge has no unit tests** — `_merge_defaults`, `_merge_dicts`, `_merge_internal_defaults`, and `reset_to_defaults` are all untested; add `pytest` cases covering each merge path and edge cases (stale keys, `_`-prefix re-application).
diff --git a/src/controller/video_compose.py b/src/controller/video_compose.py
new file mode 100644
index 00000000..d529b408
--- /dev/null
+++ b/src/controller/video_compose.py
@@ -0,0 +1,259 @@
+"""
+Compose a session's per-camera recordings into a single layout video,
+aligned by each camera's real per-frame capture timestamp rather than by
+raw frame index.
+
+Prototype for the "aggregate session video" frontend feature described in
+CLAUDE.md's Feature ideas section — currently a standalone CLI, not wired
+into web.py/Flask yet. Cameras in a session commonly run at different real
+framerates even when nominally "the same" (see Hardware gotchas in
+CLAUDE.md), so pairing frame i<->i<->i drifts noticeably over a session.
+This instead resamples every stream onto one common wall-clock grid built
+from each camera's `_timestamps.csv` `timestamp_ns` column.
+
+Unlike tools/make_aligned_video.py, this does not require PTP framesync
+(camera.sync_mode) — it works from each camera's own capture timestamps,
+so it also produces a (best-effort) result for unsynced sessions. It has
+no ffmpeg dependency — composites directly through OpenCV's bundled
+ffmpeg-backed VideoCapture/VideoWriter, so it also works on a machine
+with no system ffmpeg install.
+
+Usage:
+    python3 src/controller/video_compose.py /path/to/session/date_dir [--output out.mp4]
+
+    # e.g., matching the tools/analyse_framesync.py convention:
+    python3 src/controller/video_compose.py \
+        /home/pi/controller_share/my-session/20260703
+"""
+
+from __future__ import annotations
+
+import argparse
+import csv
+import glob
+import math
+import os
+from dataclasses import dataclass
+
+import cv2
+import numpy as np
+
+DEFAULT_CANVAS_WIDTH = 1920
+DEFAULT_FPS = 30
+
+
+@dataclass
+class CameraStream:
+    name: str
+    video_path: str
+    csv_path: str
+
+
+def discover_camera_streams(date_dir: str) -> list[CameraStream]:
+    """Find every module subfolder in a session's date directory that looks
+    like a camera recording: a video file plus a matching *_timestamps.csv
+    with a timestamp_ns column. Non-camera modules (microphone, ttl, ...)
+    are silently skipped since they don't produce per-frame video."""
+    streams = []
+    for entry in sorted(os.listdir(date_dir)):
+        module_dir = os.path.join(date_dir, entry)
+        if not os.path.isdir(module_dir):
+            continue
+        videos = sorted(
+            glob.glob(os.path.join(module_dir, "*.ts"))
+            + glob.glob(os.path.join(module_dir, "*.mp4"))
+        )
+        csvs = glob.glob(os.path.join(module_dir, "*_timestamps.csv"))
+        if not videos or not csvs:
+            continue
+        with open(csvs[0], newline="") as f:
+            header = next(csv.reader(f), [])
+        if "timestamp_ns" not in header:
+            continue
+        streams.append(CameraStream(name=entry, video_path=videos[0], csv_path=csvs[0]))
+    return streams
+
+
+class _StreamCursor:
+    """Sequential, forward-only frame+timestamp reader for one camera.
+
+    Advances by decoding frames in order (never seeks — .ts/MPEG-TS
+    seeking via OpenCV is not reliably frame-accurate) and tracks which
+    decoded frame is currently the best match for a requested wall-clock
+    time.
+    """
+
+    def __init__(self, stream: CameraStream):
+        self.name = stream.name
+        self.cap = cv2.VideoCapture(stream.video_path)
+        with open(stream.csv_path, newline="") as f:
+            self.timestamps_ns = [int(row["timestamp_ns"]) for row in csv.DictReader(f)]
+        self.idx = -1
+        self.frame = None
+        self._advance()
+
+    def _advance(self) -> bool:
+        ok, frame = self.cap.read()
+        if not ok:
+            return False
+        self.idx += 1
+        self.frame = frame
+        return True
+
+    def sync_to(self, t_ns: int):
+        """Advance while the *next* decoded frame is closer to t_ns than
+        the current one, then return the current frame."""
+        while self.idx + 1 < len(self.timestamps_ns):
+            cur_ts = self.timestamps_ns[self.idx]
+            nxt_ts = self.timestamps_ns[self.idx + 1]
+            if abs(nxt_ts - t_ns) > abs(cur_ts - t_ns):
+                break
+            if not self._advance():
+                break
+        return self.frame
+
+    @property
+    def first_ts(self) -> int:
+        return self.timestamps_ns[0]
+
+    @property
+    def last_ts(self) -> int:
+        return self.timestamps_ns[-1]
+
+    def release(self):
+        self.cap.release()
+
+
+def _grid_regions(
+    n: int, canvas_width: int = DEFAULT_CANVAS_WIDTH, pane_aspect: float = 16 / 9
+) -> tuple[list[tuple[int, int, int, int]], int, int]:
+    """Evenly-sized grid fallback for an arbitrary number of cameras.
+    Returns (regions, canvas_width, canvas_height); each region is
+    (x, y, w, h), w/h forced even for codec compatibility."""
+    cols = math.ceil(math.sqrt(n))
+    rows = math.ceil(n / cols)
+    pane_w = (canvas_width // cols) // 2 * 2
+    pane_h = round(pane_w / pane_aspect / 2) * 2
+    regions = [
+        ((i % cols) * pane_w, (i // cols) * pane_h, pane_w, pane_h) for i in range(n)
+    ]
+    return regions, pane_w * cols, pane_h * rows
+
+
+def _loom_regions(
+    streams: list[CameraStream], right_width: int = 640
+) -> tuple[list[tuple[int, int, int, int]], int, int] | None:
+    """Named layout for the loom rig's 3-camera set: LoomCam large on the
+    left, Home top-right (square), ScreenCam bottom-right (16:9). Matches
+    stream folder names case-insensitively; returns None (falls back to
+    the grid layout) if the rig doesn't have exactly this camera set."""
+    expected_stream_count = 3
+    by_key = {s.name.lower(): s for s in streams}
+    loom = next((s for k, s in by_key.items() if "loom" in k), None)
+    home = next((s for k, s in by_key.items() if "home" in k), None)
+    screen = next((s for k, s in by_key.items() if "screen" in k), None)
+    if not (loom and home and screen) or len(streams) != expected_stream_count:
+        return None
+
+    home_h = right_width
+    screen_h = round(right_width * 9 / 16 / 2) * 2
+    right_h = home_h + screen_h
+    loom_w = round(right_h * 16 / 9 / 2) * 2
+
+    order = [loom, home, screen]
+    regions = {
+        loom.name: (0, 0, loom_w, right_h),
+        home.name: (loom_w, 0, right_width, home_h),
+        screen.name: (loom_w, home_h, right_width, screen_h),
+    }
+    ordered_regions = [regions[s.name] for s in order]
+    return ordered_regions, loom_w + right_width, right_h, order
+
+
+def _label(frame: np.ndarray, text: str) -> np.ndarray:
+    cv2.rectangle(frame, (0, 0), (14 * len(text) + 12, 34), (0, 0, 0), -1)
+    cv2.putText(frame, text, (6, 24), cv2.FONT_HERSHEY_SIMPLEX, 0.8, (255, 255, 255), 2)
+    return frame
+
+
+def compose_session_video(
+    date_dir: str,
+    output_path: str,
+    layout: str = "auto",
+    fps: int = DEFAULT_FPS,
+) -> str:
+    streams = discover_camera_streams(date_dir)
+    if not streams:
+        raise ValueError(
+            f"No camera streams (video + *_timestamps.csv) found under {date_dir}"
+        )
+
+    ordered = streams
+    loom_layout = _loom_regions(streams) if layout in ("auto", "loom") else None
+    if loom_layout is not None:
+        regions, canvas_w, canvas_h, ordered = loom_layout
+    else:
+        if layout == "loom":
+            raise ValueError(
+                "--layout loom requires exactly one "
+                "LoomCam/Home/ScreenCam-named stream each"
+            )
+        regions, canvas_w, canvas_h = _grid_regions(len(streams))
+
+    cursors = [_StreamCursor(s) for s in ordered]
+    t_start = max(c.first_ts for c in cursors)
+    t_end = min(c.last_ts for c in cursors)
+    if t_end <= t_start:
+        raise ValueError(
+            "Camera streams in this session have no overlapping time window"
+        )
+
+    step_ns = int(1e9 / fps)
+    n_out = int((t_end - t_start) / step_ns)
+
+    os.makedirs(os.path.dirname(output_path) or ".", exist_ok=True)
+    fourcc = cv2.VideoWriter_fourcc(*"mp4v")
+    writer = cv2.VideoWriter(output_path, fourcc, fps, (canvas_w, canvas_h))
+    if not writer.isOpened():
+        raise RuntimeError("VideoWriter failed to open — codec unavailable")
+
+    try:
+        for i in range(n_out):
+            t = t_start + i * step_ns
+            canvas = np.zeros((canvas_h, canvas_w, 3), dtype=np.uint8)
+            for cursor, (x, y, w, h) in zip(cursors, regions, strict=True):
+                pane = _label(cv2.resize(cursor.sync_to(t), (w, h)), cursor.name)
+                canvas[y : y + h, x : x + w] = pane
+            writer.write(canvas)
+    finally:
+        writer.release()
+        for cursor in cursors:
+            cursor.release()
+
+    return output_path
+
+
+def main():
+    parser = argparse.ArgumentParser(description=__doc__)
+    parser.add_argument(
+        "date_dir", help="Session date directory, e.g. /path/to/session/20260804"
+    )
+    parser.add_argument(
+        "--output", default=None,
+        help="Output .mp4 path (default: <date_dir>/../<session>_aggregated.mp4)",
+    )
+    parser.add_argument("--layout", choices=["auto", "loom"], default="auto")
+    parser.add_argument("--fps", type=int, default=DEFAULT_FPS)
+    args = parser.parse_args()
+
+    session_dir = os.path.dirname(os.path.normpath(args.date_dir))
+    session_name = os.path.basename(session_dir)
+    output = args.output or os.path.join(session_dir, f"{session_name}_aggregated.mp4")
+    result = compose_session_video(
+        args.date_dir, output, layout=args.layout, fps=args.fps
+    )
+    print(f"Wrote {result}")
+
+
+if __name__ == "__main__":
+    main()