data-pipelines
claudeML data pipelines: Apache Beam, Spark, dbt, orchestration, streaming features, validation, and backfills.
1 skill · 1 command · 1 agent
0
claude
data-labeling
Data labeling: annotation guidelines, platforms, inter-annotator agreement, active learning, weak supervision, and label error detection.
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Plugin data-labeling from marketplace libre-mlops in HermeticOrmus/LibreMLOps-Claude-Code. Commands read from the repo's manifest — 1 month ago.
What it installs
Skills (1)
labeling-patternsAnnotation patterns with code: labeling guideline design, active learning sampling loops, Snorkel labeling functions, inter-annotator agreement monitoring, gold-label injection for annotator QA, and Cleanlab label error detection. Use when building or auditing a labeling pipeline.
Slash commands (1)
/data-labeling:label-dataPlan an annotation project, prepare tasks for Label Studio, measure inter-annotator agreement and flag weak annotators, or export labeled data with quality filters.
Subagents (1)
data-labeling-engineerUse this agent when setting up or auditing data annotation: writing labeling guidelines, choosing an annotation platform, measuring inter-annotator agreement, cutting labeling cost with active learning or Snorkel weak supervision, or finding label errors. It treats label quality as the ceiling on mo
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