Track DataFrame transformation lineage across Python notebooks and pipelines.
npx skills add https://github.com/etoyama/insight-blueprint --skill data-lineage-etoyama
Please help me install this Agent Skill. Skill: data-lineage Source: https://github.com/etoyama/insight-blueprint/tree/main/skills/data-lineage Command: npx skills add https://github.com/etoyama/insight-blueprint --skill data-lineage-etoyama
Track data transformation lineage across notebooks and Python scripts, enabling transparent auditing of how data evolves in your pipelines.
Open a notebook and enable lineage tracking using the provided workflow to generate a Mermaid diagram.
High-intent search queries and answers about installing and using this skill.
You can track data lineage in Python notebooks by wrapping DataFrame pipelines with the tracked_pipe wrapper, which records transformations and row-count changes to create an auditable record of data evolution.
You can visualize DataFrame transformation lineage by exporting Mermaid diagrams that map pipeline flows, providing a quick graphical review for auditing and documentation of data evolution.
Yes, data lineage tracking applies to standard Python notebooks and scripts during data wrangling to produce an auditable record of transformations for reproducibility.
You need tracked_pipe to wrap DataFrame pipelines because it actively monitors and records row-count changes across transformations, ensuring transparent auditing of how data evolves.
Yes, the Skill exposes a lineage management API that allows you to programmatically manage data transformation tracking across notebooks and pipeline workflows.
The best way to document data evolution across notebooks is to wrap pipelines with tracked_pipe to record transformations and export Mermaid visualizations for transparent auditing.
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