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Convert an agentic HDF5 recording into a LeRobot dataset (parquet, meta, videos).
Passed 15 of 21 test cases with the skill, and 4 of 21 without it.
and 16 more in the full report
14 fixed3 passed either way6 still failing1 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 14 test cases the skill fixed. Same model, same prompt, with and without the skill.
I need to re-convert `/data/sim.hdf5` under `assemble_trocar` into `local/assemble_trocar`, but an earlier dataset export exists in the destination path. Which flag forces replacing the existing files?
| Checked | Without skill | With skill |
|---|---|---|
| Includes --overwrite in the conversion command parameters | Missed | Passed |
The instructions your model reads when the skill loads.
Convert an agentic HDF5 recording into a LeRobot dataset (parquet + meta + videos). Use when the user asks to convert HDF5, prepare for training, or export to LeRobot.
These steps drive the i4h-workflows base code (the workflows/agentic/ tree). To reuse an existing checkout, set I4H_WORKFLOWS to its path (no clone happens). Otherwise this resolves the current repo, or clones to ~/i4h-workflows — pick that default without prompting. Run every command below from the resolved root:
# Resolve the i4h-workflows base code (provides workflows/agentic/).
ROOT="${I4H_WORKFLOWS:-$(git rev-parse --show-toplevel 2>/dev/null)}"
if [ ! -d "$ROOT/workflows/agentic" ]; then
ROOT="${I4H_WORKFLOWS:-$HOME/i4h-workflows}"
[ -d "$ROOT/workflows/agentic" ] || git clone https://github.com/isaac-for-healthcare/i4h-workflows "$ROOT"
fi
export I4H_WORKFLOWS="$ROOT"; cd "$ROOT"
--env that produced the HDF5.workflows/agentic/config/environments/<env>.yaml supplies the robot, task, cameras, and dataset.* (action/state names, splits, modality) converter defaults.HF_LEROBOT_HOME/<repo-id>.Run the steps below in order. Each step is a separate bash call; variables persist in the local agent's tmux session.
REPO_ROOT="${I4H_WORKFLOWS:-$(git rev-parse --show-toplevel 2>/dev/null)}"; [ -d "$REPO_ROOT/workflows/agentic" ] || REPO_ROOT="$HOME/i4h-workflows"
ENV_ID=scissor_pick_and_place
RUNS_ROOT="${REPO_ROOT}/workflows/agentic/runs"
# Point HDF5_PATH at a real recording (absolute path). Recordings come from teleop, mimic, or
# validate (which writes data/verify.hdf5 under each runs/eval_* dir). List candidates newest-first:
# find "${RUNS_ROOT}" -name '*.hdf5' -printf '%TY-%Tm-%Td %TH:%TM %p\n' | sort -r | head
test cases passed, vs 4 / 21 without
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