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harnessprotocol
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lineage

Trace column-level data lineage across SQL, Kafka, Spark, JDBC, and ORM code.

9|2|Updated Mar 7, 2026
Search Tags:#impact analysis#sql#data lineage#kafka#spark#jdbc#confidence ratings
One-click install
npx skills add https://github.com/harnessprotocol/harness-kit --skill lineage-harnessprotocol
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: lineage
Source: https://github.com/harnessprotocol/harness-kit/tree/main/plugins/lineage/skills/lineage
Command: npx skills add https://github.com/harnessprotocol/harness-kit --skill lineage-harnessprotocol

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

It removes the guesswork of tracing where a specific data column comes from and what depends on it when your system spans SQL, Spark, Kafka, JDBC, and ORM layers.

Core Features & Use Cases

  • Column-level upstream/downstream tracing across SQL views/tables, Kafka topics, JDBC writes/reads, Spark jobs, and ORM mappings.
  • Structured lineage output that includes hop-by-hop confidence ratings and file references.
  • Visual lineage diagrams as self-contained SVG (with an ASCII fallback for simple cases).
  • Use case: If you need to debug why orders.total_amount is wrong, you can trace upstream sources and identify downstream consumers that may rely on the affected logic.

Quick Start

Ask for a lineage trace by sending: /lineage orders.total_amount

Frequently Asked Questions about lineage

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

FAQPage Schema
How do I trace column-level data lineage across SQL, Kafka, and Spark?▼

Column-level data lineage is traced by statically reading and searching the codebase to map upstream sources and downstream consumers across SQL, Kafka, Spark, JDBC, and ORM code. This produces a structured hop-by-hop path with confidence ratings and an SVG diagram.

Can I perform impact analysis on a data column without connecting to the database?▼

Yes, impact analysis requires no database connections or execution. It reads the codebase statically to identify downstream consumers and upstream sources for a given column, providing a structured path with file references and confidence ratings.

What is the best way to debug incorrect metrics in a heterogeneous data pipeline?▼

Debugging incorrect metrics is best done by tracing the column upstream to identify where the incorrect values originate. This process maps the hop-by-hop data path across SQL, Kafka, Spark, JDBC, and ORM layers while providing confidence ratings.

Does this column lineage tracing work with JDBC writes and ORM mappings?▼

Yes, column lineage tracing works with JDBC writes and reads, as well as ORM mappings. It statically analyzes these layers alongside SQL views, Kafka topics, and Spark jobs to map dependencies and generate visual diagrams.

How do I generate a visual data lineage diagram from my codebase?▼

A visual data lineage diagram is generated as a self-contained SVG, or an ASCII fallback for simple cases, after statically analyzing the codebase. This visual output traces upstream and downstream dependencies for a specified column.

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