tracing-downstream-lineage

Name: tracing-downstream-lineage
Availability: InStock
Author: miptah21

Trace downstream table and DAG dependencies to generate change impact reports.

2|Updated Apr 8, 2026

Search Tags:#dashboards #impact analysis #data engineering #DAG dependencies #downstream lineage #schema change risk

Ready to run

npx skills add https://github.com/miptah21/skills --skill tracing-downstream-lineage-miptah21

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: tracing-downstream-lineage
Source: https://github.com/miptah21/skills/tree/main/.agents/skills/tracing-downstream-lineage
Command: npx skills add https://github.com/miptah21/skills --skill tracing-downstream-lineage-miptah21

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill prevents risky database and orchestration changes by showing exactly what downstream tables, dashboards, DAGs, and stakeholders will be impacted.

Core Features & Use Cases

Downstream impact tracing: Identifies direct consumers of a target table or DAG using code search, view dependency checks, and BI query patterns.
Recursive dependency mapping: Builds a downstream dependency tree from produced artifacts (tables/views) and traces consumers repeatedly for broader blast-radius coverage.
Change risk assessment: Categorizes impacts by criticality and evaluates risk for schema changes, data changes, and deletion/deprecation scenarios.
Stakeholder discovery and reporting: Pinpoints owners (DAG owners, BI owners, team ownership) and outputs a structured impact report with recommended mitigation steps.

Quick Start

Use the tracing-downstream-lineage skill to generate an impact report for a proposed change to your target table or DAG before deploying it.

Frequently Asked Questions about tracing-downstream-lineage

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

FAQPage Schema

How do I trace downstream data lineage before changing a production table?▼

Downstream data lineage tracing builds a recursive dependency tree from your target table to identify all consuming views, DAGs, and dashboards. It maps the blast radius by repeatedly checking code dependencies and BI query patterns to expose impacted pipelines.

What is the best way to assess schema change risk for data pipelines?▼

Schema change risk assessment categorizes downstream impacts by criticality and evaluates specific risks for schema modifications, data changes, or deletions. It produces a structured report pinpointing affected DAG owners and BI stakeholders with recommended mitigation steps.

How do I find which dashboards and DAGs will break if I modify a dataset?▼

Finding impacted dashboards and DAGs involves recursive dependency mapping that traces direct consumers of your target dataset. It searches view dependencies and BI query patterns to classify criticality and generate an actionable impact report before deployment.

Can I identify downstream stakeholders and owners before deprecating a data pipeline?▼

Yes, stakeholder discovery identifies DAG owners, BI owners, and team ownership during downstream impact analysis. It outputs a structured impact report detailing who will be affected by the deprecation and provides recommended mitigation steps.

What is DAG dependency mapping and when do I need it?▼

DAG dependency mapping traces downstream data lineage to perform change impact analysis for your orchestration workflows. You need it to evaluate modification risk, prevent dependency breakage, and avoid downstream failures before altering production pipelines.