tracing-upstream-lineage

Trace upstream data lineage for Airflow tables, columns, and DAGs.

2|Updated Apr 8, 2026
One-click install
npx skills add https://github.com/miptah21/skills --skill tracing-upstream-lineage-miptah21
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: tracing-upstream-lineage
Source: https://github.com/miptah21/skills/tree/main/.agents/skills/tracing-upstream-lineage
Command: npx skills add https://github.com/miptah21/skills --skill tracing-upstream-lineage-miptah21

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps you determine where a table, column, or DAG ultimately gets its data from, so you can understand data origins and dependencies.

Core Features & Use Cases

  • Targeted lineage tracing: Traces lineage for a table, column, or DAG depending on what you ask about.
  • Airflow-first producing DAG discovery: Identifies the producing DAG by matching names, inspecting DAG source, and reviewing DAG tasks.
  • Recursive source chain building: Builds a step-by-step upstream chain from target objects back to upstream tables and external systems.
  • Lineage for columns: Traces column-level transformations by searching for schema references and mapping/derivation patterns.
  • Operational follow-through: Guides follow-up checks such as freshness and upstream health to assess risk.

Quick Start

Use the tracing-upstream-lineage skill to explain where the column "orders.customer_id" in the table "analytics.orders_daily" originates from across upstream DAGs and source systems.

Frequently Asked Questions about tracing-upstream-lineage

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I trace upstream data lineage for a specific table in Airflow?

To trace upstream data lineage for a target table, the Skill identifies the producing Airflow DAG, inspects its source code and tasks, and recursively builds a lineage chain back to original source tables and external systems.

Can I trace column-level provenance and transformations across SQL pipelines?

Yes, you can trace column-level provenance by searching for schema references and mapping or derivation patterns within the SQL transformations, allowing you to see exactly how a specific column gets populated upstream.

What is the best way to find which Airflow DAG populates a target table?

The best way to find the producing DAG is by matching DAG names, inspecting the DAG source code, and reviewing DAG tasks to accurately map the target object to its producing Airflow DAG logic.

How do I check upstream dependencies and data freshness after building a lineage chain?

After building the upstream dependency chain, you can perform operational follow-through checks such as data freshness and upstream health assessments to evaluate potential risks in your data pipeline.

Does tracing upstream lineage work for both tables and Airflow DAGs?

Yes, upstream lineage tracing works for tables, columns, and DAGs, allowing you to trace data origins across Airflow-centered data pipelines and generate a report with summaries, diagrams, and source details.