rerun-chunk-processing
rerun-chunk-processing is a Data pipelines & ETL skill for AI agents, published by rerun-io in the rerun repository on GitHub. Skillspace rates rerun-chunk-processing D (66/100) and it passed the safety scan; the rating is based on static analysis only.
Core mechanics of the Rerun Chunk Processing API (rerun.experimental) — LazyChunkStream pipelines, Chunk, lenses (MutateLens/DeriveLens/Selector), RrdReader, writing optimized RRDs. Read BEFORE writing any ingestion/conversion/preprocessing code (convert an MCAP, build a recording from a dataset, preprocess an .rrd, port an old converter): it mandates reader+lens pipelines and steers away from hand-built chunks — no Chunk.from_columns for data a reader/lens can produce, no per-message rr.log, no manual pa.array assembly. Source-specific knowledge lives in the importer skills (rerun-mcap, rerun-urdf, rerun-parquet, rerun-lerobot); read rerun-data-model first to decide what the data should become.
- Grade
- D
- Quality
- 66 / 100
- Safety
- Passed
- GitHub stars
- 11,133
Unproven: rated by static analysis only, not yet compared head-to-head.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 96 / 100
- Maturity
- Basic: a single SKILL.md
- Security scan
- No issues found
- License
- Apache-2.0
- Adoption
- Adopted by 1 other repositories, in 0 collections
- Scope
- Vendor-specific: built around one product. Documents Rerun's public chunk-processing API from vendor repo
Not checked yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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