review: skip-count fix, atomic writes, dedupe span reconstruction, role guards

**#1 Plan-update phase reports correct skip count.**
``_run_plan_update_phase`` only ran ``run_plan_updates`` for episodes
with at least one interjection but hardcoded ``episodes_skipped=0``.
The summary undercounted skipped episodes. Now returns
``len(records) - processed`` so processed + skipped == total.

**#2 ``run_hf_job.py`` installs ``openai``.**
The ``CMD`` block does ``pip install --no-deps lerobot[branch]`` then
explicitly lists transitive deps. ``openai`` was missing — and since
``VlmConfig.backend`` defaults to ``"openai"``, the job would have
``ImportError``'d when ``vlm_client._make_openai_client`` ran.

**#3 Dedupe subtask-span reconstruction.**
Module 1's ``_reconstruct_subtasks_from_rows`` (no ``and spans`` guard)
and Module 2's ``_read_subtask_spans`` (with the guard) had near-
identical logic. Promoted to ``reconstruct_subtask_spans`` in
``reader.py`` using the safer guarded form. Both modules now import
the single helper.

**#5 Atomic staging.py JSONL writes.**
Mirroring the parquet-writer fix from an earlier review round:
``EpisodeStaging.write`` now writes to a sibling ``.tmp`` and
``Path.replace`` atomically. A crash mid-write can no longer leave a
half-written JSONL that ``read()`` would then fail to parse.

**#6 Atomic ``info.json`` write.**
Same pattern in ``executor._ensure_annotation_metadata_in_info`` —
``info.json`` is load-bearing for dataset metadata, so partial writes
brick the dataset.

**#7 Writer's role-key guard.**
``_normalize_persistent_row`` and ``_normalize_event_row`` accessed
``row["role"]`` directly while every other field used ``.get()``.
Pre-validate ``"role" in row`` and raise a friendly ``ValueError``
naming the row, so a future module that accidentally drops ``role``
fails with a triagable message instead of a bare KeyError deep in the
writer.

**#8 Last subtask span's ``end`` extends to episode end.**
``reconstruct_subtask_spans`` (the new shared helper) takes an optional
``episode_end_t``. When provided, the final span's ``end`` is closed
to that timestamp instead of equalling its own ``start`` (zero
duration). Both Module 1's plan-update pass and Module 2's interjection
anchoring pass ``record.frame_timestamps[-1]``, so downstream "current
subtask at refresh_t" lookups no longer miss refreshes that land
inside the final span.

Sweep: 66 passed, 0 failed. Pre-commit clean.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

examples/annotation/run_hf_job.py

@@ -21,16 +21,18 @@ from huggingface_hub import get_token, run_job
 
 token = os.environ.get("HF_TOKEN") or get_token()
 if not token:
-    raise RuntimeError(
-        "No HF token. Run `huggingface-cli login` or `export HF_TOKEN=hf_...`"
-    )
+    raise RuntimeError("No HF token. Run `huggingface-cli login` or `export HF_TOKEN=hf_...`")
 
 CMD = (
     "apt-get update -qq && apt-get install -y -qq git ffmpeg && "
     "pip install --no-deps "
     "'lerobot @ git+https://github.com/huggingface/lerobot.git@feat/language-annotation-pipeline' && "
     "pip install --upgrade-strategy only-if-needed "
-    "datasets pyarrow av jsonlines draccus gymnasium torchcodec mergedeep pyyaml-include toml typing-inspect && "
+    # Mirror lerobot's [annotations] runtime deps. ``openai`` is required
+    # because ``VlmConfig.backend`` defaults to ``"openai"`` (which talks
+    # to a vllm/transformers/ktransformers OpenAI-compatible server).
+    "datasets pyarrow av jsonlines draccus gymnasium torchcodec mergedeep pyyaml-include "
+    "toml typing-inspect openai && "
     "export VLLM_MEMORY_PROFILER_ESTIMATE_CUDAGRAPHS=0 && "
     "export VLLM_VIDEO_BACKEND=pyav && "
     "lerobot-annotate "