openbot-data 0.0.3 · updated 2026-09-02
Why a Sample Audit Is Not Full Dataset Readiness
Compare sampled and full-integrity robot dataset audits without overstating what a fast preflight actually verified.
Direct answer
Use a sample audit to bound fast triage, not to certify a complete dataset. Full-integrity inspection expands coverage across every locally available episode, frame, and media reference; policy readiness is a separate decision because structural validity alone does not prove training compatibility.
Run the check
openbot-data audit ./lerobot_dataset \
--format lerobot \
--integrity sample \
--out ./sample.audit.json \
--fail-on error
openbot-data audit ./lerobot_dataset \
--format lerobot \
--integrity full \
--out ./full.audit.json \
--fail-on errorMachine-readable output: sample.audit.json and full.audit.json (`openbot.dataset_audit.v1`)
What this proves
- A sampled audit can quickly expose structural and selected media problems.
- The output records coverage and skipped capabilities instead of converting missing checks into a pass.
- A full-integrity run expands evidence across the complete local source available to the tool.
What it does not prove
- That an unexamined frame, episode, or shard is valid after only a sample run.
- That no semantic labeling or task-quality problem exists.
- That a zero-error audit is equivalent to policy-specific readiness.
Decision checklist
- 01Use sample integrity for bounded triage and label the result as sampled.
- 02Use full integrity before release, merge acceptance, or an expensive training run.
- 03Run a policy profile separately when training compatibility is the actual decision.
- 04Preserve both artifacts if the sampled run determined whether deeper inspection was warranted.
Reviewed sources
Reviewed by OpenBot Catalog team