rca-diagnostics

Trace multi-system logs backward to isolate initiating causes of cascading failures.

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

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

It helps you identify the true root cause behind incidents where multiple systems fail together, and prevents misattributing downstream errors to the wrong component.

Core Features & Use Cases

  • Cross-system incident tracing: Correlates failures across infrastructure, data pipelines, and code changes to isolate the initiating cause.
  • Timeline-driven RCA: Builds an event timeline and works backward from observed failures to the underlying trigger.
  • Actionable outcomes: Produces a clear explanation of why it failed plus immediate mitigation and long-term preventative measures, including post-mortem drafting when needed.

Quick Start

Use the rca-diagnostics skill to investigate why multiple pipelines broke after a deployment by correlating logs, building an incident timeline, tracing backward to the initiating change, and generating both remediation and a post-mortem.

Frequently Asked Questions about rca-diagnostics

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

FAQPage Schema
How do I perform root cause analysis for cascading failures across multiple systems?

Root cause analysis for cascading failures requires gathering multi-system logs, constructing an incident timeline, and performing backward tracing to isolate the initiating trigger. This approach prevents misattributing downstream errors to the wrong component.

What is the best way to investigate correlated failures after a data platform deployment?

Investigating correlated failures after a deployment involves correlating logs across infrastructure, data pipelines, and code changes. By building an event timeline and working backward from observed failures, you can isolate the initiating configuration or code change.

How does timeline tracing work for post-mortem incident response?

Timeline tracing for incident response works by mapping multi-system logs into a chronological event timeline. It then performs backward tracing from observed failures to the underlying trigger, producing actionable remediation and post-mortem recommendations.

Can I use this approach for recurring reliability issues in data pipelines?

Yes, this cross-system incident tracing approach is explicitly designed for systemic or recurring reliability issues in data platforms. It correlates upstream data changes and infrastructure failures to isolate the true initiating cause.

What do I need to diagnose cross-system incidents and prevent misattributing downstream errors?

Diagnosing cross-system incidents requires multi-system logs from infrastructure, data pipelines, and code deployments. Using these inputs to construct an incident timeline ensures accurate isolation of the initiating cause rather than downstream symptoms.

When should I not use backward tracing for root cause analysis?

Backward tracing for root cause analysis is not suitable when multi-system logs are unavailable or when incidents are isolated to a single component without correlated failures across infrastructure or data pipelines.