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Trace, diff, and fix broken data transformations in any ETL pipeline.
Debugging an ETL means hunting which transform broke the data. This snapshots each step and walks the diff back to the first failing one for you.
Listed for review
No verified public repo for this skill yet, so this page does not give you an install command. Skills with a verified source install in one command — or fully manual: copy the skill folder into .claude/skills/ and your agent picks it up.
Boostor Quality Score
84/100 · B
Data Pipeline Debugger attaches to your Python or TypeScript ETL code and captures intermediate dataframe snapshots at each transformation step. When output diverges from expected, it walks back the diff to the earliest failing transform and suggests a fix. Works with Pandas, Polars, and DuckDB-based pipelines.
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