Rerun Dataset Conversion
Convert a multi-modal robotics dataset (MCAP, HDF5, LeRobot, parquet, raw video) into...
Install
npx skills add rerun-io/rerun --skill rerun-dataset-conversion -g -a claude-code -y- Repository
- rerun-io/rerun11.7k
- Category
- Data and ML
- Updated
- 3d ago
- License
- Apache-2.0
- Context cost
- Mediumabout 3,000 tokens
- Runs scripts
- No, instructions only
What it does
Convert a multi-modal robotics dataset (MCAP, HDF5, LeRobot, parquet, raw video) into layered Rerun recordings (.rrd) and a catalog-ready dataset. Use whenever the user wants a dataset converted or ingested into Rerun, a conversion pipeline reviewed or extended, or an existing dataset enriched with a new layer, even when they only say 'convert X to rrd', 'ingest this dataset', 'enrich this dataset', or 'append a layer'. Routes to the rerun-* skills for Rerun mechanics.
Dataset conversion
This skill guides the conversion of a multi-modal robotics dataset into layered Rerun recordings (.rrd).
It covers the high-level workflow guidelines: surveying the source, building layers, designing the default blueprint, registering a catalog, and validating the result.
It also provides DOs and DON'Ts for each stage of the conversion process.
Terms
The skill and its references use these terms throughout:
| Term | Meaning |
|---|---|
| episode | The source's natural unit of recording. |
| recording id | The string that identifies one episode's recordings. All of the episode's layers share it. |
| layer | One .rrd file per episode. The viewer and the catalog stack an episode's layers into one recording. |
| base layer | The layer that reflects the source. It is the one record, sufficient without the source. |
| segment | One episode as the catalog sees it: its layers stacked under one recording id. |
| property | A per-episode value stored as a recording property. The catalog shows it as a column. |
| census | A count of decoded rows against the source's own counts, so a silent drop surfaces. |
| survey | The phase that measures sample diversity before any conversion code exists. |
What this skill adds, and what it routes away
This skill adds how a conversion, or a layer addition, is shaped, decided, and validated, and which judgment calls recur from one dataset to the next.
