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rerun-chunk-processing

Core mechanics of the Rerun Chunk Processing API (rerun.chunk) — 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-mp4, rerun-lerobot); read rerun-data-model first to decide what the data should become.

Quality

90%

Does it follow best practices?

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SKILL.md
Quality
Evals
Security

Quality

Content

78%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A dense, highly actionable API reference with executable examples and a strong decision-rule sequence, weakened mainly by monolithic structure — no detail is offloaded to reference files — and the absence of an explicit output-validation step after write_rrd. Conciseness is good overall with a few over-explained passages.

Suggestions

Split the Selector grammar and full lens/output-mode reference into references/ files (e.g., references/selector-grammar.md, references/lenses.md), keeping SKILL.md as the decision-rule overview — this would also cut context-window cost.

Add an explicit verification step after write_rrd (e.g., 'read back with RrdReader(path).stream() and spot-check entity/timeline counts before declaring success') to close the workflow's validation gap.

Trim the recording-properties anti-example to one code block plus a single sentence on the '# type: ignore' signal.

DimensionReasoningScore

Conciseness

Mostly lean, telegraphic prose ('Execution is streaming, multithreaded, and mostly GIL-free') with no explanation of concepts Claude already knows, but a few passages over-explain — the recording-properties section spends two code blocks plus three bullets on why '/__properties/ is Rerun's internal layout', which could be trimmed to the 'do this' example and one line. Fits 'efficient; minor instances of over-explanation' rather than the fully lean anchor.

4 / 5

Actionability

Copy-paste-ready code covers the common cases: MutateLens resolution fix, DeriveLens unit conversion via PyArrow compute, sidecar Chunk.from_columns, Chunk.from_property, and the merge→write_rrd pipeline — plus an executable surface-check command ('python -c "from rerun.chunk import LazyChunkStream; help(LazyChunkStream)"') and a real end-to-end example URL. Not below 5: the examples span the skill's core operations and are complete, not pseudocode.

5 / 5

Workflow Clarity

The 6-step 'Decision rule' section gives a clear, sequenced decision procedure, and the pyarrow error-smell passage provides a diagnose→refactor feedback loop. Not 5: there is no explicit post-write verification step (e.g., reading the written RRD back with RrdReader to confirm), so a checkpoint is implicit ('pin-check signatures') rather than commanded.

4 / 5

Progressive Disclosure

Good inline structure with clean ## sections and a clearly signaled References section, but no bundle files exist and ~300 lines of API reference (full lens/output-mode semantics, Selector grammar, stream composition API) are inlined in SKILL.md where a references/ split would be appropriate. Matches 'some structure... content that should be separate is inline' better than the mostly-appropriate-placement anchor.

3 / 5

Total

16

/

20

Passed

Description

100%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

An exemplary description: concrete capability list, explicit read-before trigger with natural user scenarios, third-person voice, and deliberate boundary-setting against sibling importer skills. Every clause carries trigger or disambiguation value rather than padding.

DimensionReasoningScore

Specificity

Names the domain and its concrete machinery in detail — 'LazyChunkStream pipelines, Chunk, lenses (MutateLens/DeriveLens/Selector), RrdReader, writing optimized RRDs' — plus concrete actions ('convert an MCAP, build a recording from a dataset, preprocess an .rrd, port an old converter'). Coverage is comprehensive; not below because nothing significant in the skill's scope is left unmentioned, and the density is informational rather than padded.

5 / 5

Completeness

Explicitly answers both questions: what ('Core mechanics of the Rerun Chunk Processing API (rerun.chunk)...') and when ('Read BEFORE writing any ingestion/conversion/preprocessing code' with four concrete trigger scenarios). A 'use when' clause of exactly this explicitness is the anchor-5 example; it cannot score lower.

5 / 5

Trigger Term Quality

Natural user phrasings and file formats/extensions are all present: 'convert an MCAP', 'preprocess an .rrd', 'port an old converter', 'build a recording from a dataset', 'ingestion/conversion/preprocessing'. These map directly onto what a user would say when needing this skill, matching the top anchor including synonyms and extensions.

5 / 5

Distinctiveness Conflict Risk

The trigger is anchored to the rerun.chunk API and the description actively disambiguates against sibling skills ('Source-specific knowledge lives in the importer skills (rerun-mcap, rerun-urdf, ...); read rerun-data-model first'), which reduces rather than creates conflict risk. Clear niche, minimal overlap.

5 / 5

Total

20

/

20

Passed

Validation

87%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 14 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

allowed_tools_field

'allowed-tools' contains unusual tool name(s)

Warning

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

14

/

16

Passed

Repository

rerun-io/rerun

Path

skills/rerun-chunk-processing/SKILL.md

Reviewed

Table of Contents

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