Quickstart validation record

This records the scope of the first-user walkthrough, rather than qualifying all Task Program tasks, robots, seeds or physics backends.

Environment and scope

Item	Validated value
Date	2026-10-17
SDK baseline	a8226e143343ed13fae0cdc4e71bf754ce364178 (0.3.1 metadata), installed from a built wheel
CLI	embodichain run-env; run-task exists as an alias at this baseline
Runtime	Python 3.11.14, Linux, DexSim 0.5.1rc1, Warp 1.17.0, Newton dependency 1.6.0
GPU	NVIDIA RTX PRO 5000 72 GB Blackwell; driver 580.126.20; PyTorch 2.7.0+cu128; one GPU selected with CUDA_VISIBLE_DEVICES=1
Deployment	embodichain_tasks/configs/tasks/manipulation/repeated_pick_place/task.franka.yaml
Physics / execution	Default; trajectory_open_loop.yaml; effect_assurance: projected
Selection	Seed 7, one environment, one episode, no expansion
User directory	Empty directory outside the repository; installed package deployment plus local program overrides

The isolated Python environment inherited other SDK dependencies from the host; this was an installed-wheel, outside-checkout usage check, not a clean-room installation audit. Required robot assets were already cached on the host. The existing development DexSim installation failed during import. Installing the pinned wheel and matching Warp/Newton dependencies in an isolated environment resolved that failure without modifying the shared install.

Launcher migration

The current walkthrough uses embodichain run-task, the sole execution entry point after main commit db821682 (#793). The historical physical runs above used run-env at baseline a8226e14; their measurements and screenshots are retained unchanged. Synchronizing the documentation changes the command spelling and launcher-guide links, not the tested program, deployment or physics policy.

Observed results

Case	Result
Discover/inspect	list-task and show-task resolve the installed official task.
Original	Six segments, 240 steps, A → B → A; command execution completed with saving disabled.
Two moves	Four segments, 160 steps, B → A; command execution completed with saving disabled.
Checked without saving	Four segments completed, including two successful settling/position checks.
Checked/save	Four segments, 188 frames, 7.52 s; two settling checks and two 3 cm position checks passed; one episode saved.
Repeat checked/save with the ordinary CLI	One episode, 188 frames; both position/stability checks passed again without the capture harness.
Dataset reader	preview_lerobot_data reads the episode, task/subtask language and four segment ranges; consistency check passes.
Unknown object	reference_validation_failed at $.program.body.items[0].steps.call.object; exit 1 before environment construction.
Unsupported field	unknown_field at $.program.speed; exit 1 before environment construction.

In the first checked run, the Place segments each took 54 steps including settling. Measured position errors were 0.022820491 m at B and 0.016308872 m at A; the threshold remained 0.03 m. Saved sidecars contain completed: true, success: true, the per-segment validation results and settling diagnostics. These observations establish the stated position and stability conditions. Projected Pick/Place effects remain unverified by contact or release monitors.

The original program was also rerun with a temporary capture harness calling SimulationManager.start_window_record() and stop_window_record(), using simulation-time capture at 20 FPS and one fixed viewpoint. The documentation’s three JPEGs are compressed frames 1, 31 and 191 from that original-program video. No scene objects, targets, policy or robot configuration were changed for capture. Raw logs, episode metadata, videos and the capture harness are retained with the implementation’s validation artifacts; the documentation only ships the three compressed frames and the two program downloads.

Maintainer checks

These commands require a source checkout and are separate from the installed SDK walkthrough. The existing read-only inspector uses production component resolution, loader, catalog preflight and lowering, without constructing a simulator:

python .agents/skills/add-task-program/scripts/inspect_deployment.py \
  extensions/embodichain_tasks/configs/tasks/manipulation/repeated_pick_place/task.franka.yaml \
  --json

For each downloadable variant, validation used a temporary copy of that deployment with absolute component paths and only task_program.program replaced. This exercises the same integration, physical UID and contract checks. It is not an additional task configuration that users need to maintain.

The documentation build and public API/context checks are recorded in the PR. No new runtime API, configuration field, tutorial-specific test or production behavior is introduced by these pages. Future changes to the example, robot, policy, physics dependencies or validator semantics require repeating the physical checks, not just rebuilding HTML.