What kind of failures can it classify?

It classifies failures into three main buckets: Platform (infrastructure issues), Code (playbook or logic errors), and Configuration (missing variables or environment settings).

Does this skill require specific MCP servers?

Yes, it requires the aap-mcp-job-management and aap-mcp-inventory-management servers to access job logs and host variables.

How does the Forensic Troubleshooter identify why a job failed?

The skill invokes a specialized analyzer that retrieves job status, extracts failure events from the AAP API, and compares these patterns against Red Hat troubleshooting documentation.

Can this skill fix the errors it finds?

This skill focuses on forensic analysis and advisory. To execute fixes, you should use the governance-executor skill after receiving the resolution recommendation.

Forensic Troubleshooter

Name: Forensic Troubleshooter
Author: RHEcosystemAppEng

byRHEcosystemAppEng

•

Deployment & DevOps

Automates root cause analysis for failed Ansible Automation Platform jobs by correlating events and host system states.

Forensic Troubleshooter is a specialized orchestration skill designed to diagnose failed automation jobs within Red Hat Ansible Automation Platform (AAP). It streamlines the troubleshooting process by automatically extracting failure events, correlating errors with specific host facts, and classifying issues into platform, code, or configuration categories. By consulting established troubleshooting documentation and classification taxonomies, it provides data-driven resolution advisories and detailed audit trails, significantly reducing mean time to recovery (MTTR) for complex automation workflows.

Key Features

01Detailed forensic audit trails summarizing all consulted documents and findings

02Automated failure event extraction and timeline reconstruction

035 GitHub stars

04Cross-correlation between job errors and host-specific system facts

05Standardized error classification into Platform, Code, or Configuration tiers

06Resolution recommendations backed by official Red Hat documentation

Use Cases

01Generating follow-up diagnostics automatically after a governed execution failure

02Investigating intermittent automation failures across diverse production environments

03Performing deep-dive root cause analysis on specific failed AAP job IDs

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add rhecosystemappeng/agentic-collections forensic-troubleshooter

For use in Claude.ai and ChatGPT

Key Features

01Detailed forensic audit trails summarizing all consulted documents and findings

02Automated failure event extraction and timeline reconstruction

035 GitHub stars

04Cross-correlation between job errors and host-specific system facts

05Standardized error classification into Platform, Code, or Configuration tiers

06Resolution recommendations backed by official Red Hat documentation

Use Cases

01Generating follow-up diagnostics automatically after a governed execution failure

02Investigating intermittent automation failures across diverse production environments

03Performing deep-dive root cause analysis on specific failed AAP job IDs

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add rhecosystemappeng/agentic-collections forensic-troubleshooter

For use in Claude.ai and ChatGPT