"Use RoboTwin datasets, collect demonstrations, validate XPolicyLab
Scanned 9/9/2026
Install to Claude Code
npx -y skills add VectorSpaceLab/AREX-Skill --skill data-pipeline --agent claude-codeInstalls into .claude/skills of the current project.
Are you the author of Data Pipeline?
Add the live security badge to your README — it updates automatically with every re-scan.
[](https://www.skillsdirectory.com/skills/vectorspacelab-data-pipeline-cf948871)More formats (shields.io, HTML) on the badges page.
---
name: data-pipeline
description: "Use RoboTwin datasets, collect demonstrations, validate XPolicyLab
HDF5 trajectories, and convert legacy data layouts."
metadata:
disco-role: operating
disable-model-invocation: true
license: MIT
---
# RoboTwin data pipeline
Use this sub-skill when the user asks about RoboTwin pre-collected data, data collection, trajectory layout, HDF5 validation, legacy data conversion, asset downloads, or preparing data for XPolicyLab/LeRobot workflows.
## Route first
- For SAPIEN, `Base_Task`, robot/camera/config bootstrap, or render/backend setup, read [simulation-core](../simulation-core/SKILL.md).
- For policy rollout/evaluation, scheduler configs, remote server mode, or action adapter shapes, read [policy-eval](../policy-eval/SKILL.md).
- For adding new tasks or language templates, read [task-authoring](../task-authoring/SKILL.md).
## Main workflows
1. **Use pre-collected data**: prefer public XPolicyLab-format RoboTwin trajectories when the task is training or evaluation data preparation. Read [workflows.md](references/workflows.md).
2. **Collect demonstrations**: use task/config/GPU arguments and verify simulation prerequisites first. Read [workflows.md](references/workflows.md) and [troubleshooting.md](references/troubleshooting.md).
3. **Validate a trajectory file or downloaded layout**: use [scripts/inspect_xpolicylab_hdf5.py](scripts/inspect_xpolicylab_hdf5.py) for one file and [scripts/validate_download_layout.py](scripts/validate_download_layout.py) for a downloaded task/config/embodiment directory.
4. **Convert old raw data**: read [data-formats.md](references/data-formats.md) and the conversion section in [workflows.md](references/workflows.md).
5. **Create or bootstrap a standalone workspace**: use the root [workspace bootstrapper](../../references/workspace-bootstrap.md) instead of expecting the original checkout.
## Key layout facts
- Recommended downloaded/current collection layout:
```text
data/<task_config>/<task_name>/<embodiment>/
data/episode_0000000.hdf5
video/episode_0000000.mp4
instruction/episode_0000000.json
```
- Legacy raw layout converted by the repository utility:
```text
data/<task_name>/<task_config>/data/episode0.hdf5
```
- Default config/embodiment examples: `demo_clean`, `demo_randomized`, `aloha_agilex`.
- Collection writes XPolicyLab trajectory HDF5 directly in current RoboTwin 2.0 paths.
## Validation signals
- HDF5 contains `data_format_version`, `state/`, `action/`, `vision/`, and `additional_info/frequency`.
- Required state/action datasets have matching horizon lengths.
- RGB camera data lives under `vision/cam_head/colors` and optionally wrist camera groups.
- Instruction data exists as `instruction` or `instructions`.
- Downloaded layout contains at least one `episode_0000000.hdf5`; videos/instructions are useful but may be optional depending on archive version.
## Safety
- Dataset download and asset download commands can be large and network-heavy; do not run them unless the user asks or the workspace clearly needs them.
- Data collection launches SAPIEN simulation and can use GPU/rendering resources; start with one small task/config before scaling.
- Do not delete stuck episodes or rewrite seed files unless the user explicitly wants data cleanup.
Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.
No comments yet. Be the first to comment!