failure-postmortem

Name: failure-postmortem
Availability: InStock
Author: m2ai-portfolio

Diagnose AI failures with structured post-mortem reports.

4|1|Updated Apr 11, 2026

Search Tags:#post-mortem #root-cause-analysis #5-whys #incident-analysis #report-generation #ai-failure

Ready to run

npx skills add https://github.com/m2ai-portfolio/m2ai-skills-pack --skill failure-postmortem-m2ai-portfolio

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: failure-postmortem
Source: https://github.com/m2ai-portfolio/m2ai-skills-pack/tree/main/skills/failure-postmortem
Command: npx skills add https://github.com/m2ai-portfolio/m2ai-skills-pack --skill failure-postmortem-m2ai-portfolio

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps teams structure and publish AI failure post-mortems, turning incidents into actionable reports that support learning and accountability.

Core Features & Use Cases

Structured incident capture across six failure patterns (Context Degradation, Specification Drift, Sycophantic Confirmation, Tool Selection Error, Cascade Failure, Silent Failure).
Guided root-cause analysis using the 5 Whys approach to identify systemic gaps and guardrails.
Produce a publication-ready post-mortem report with a standardized template ready for storage in your knowledge vault or project directory.

Quick Start

Document the latest AI failure incident using the six-pattern diagnosis to generate a publishable post-mortem report.

Frequently Asked Questions about failure-postmortem

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

FAQPage Schema

How do I write a post-mortem for an AI agent failure?▼

To write a post-mortem for an AI agent failure, use a guided workflow to capture the incident, classify it into one of six failure patterns, and generate a publication-ready report. This structured approach turns incorrect AI outputs into actionable documentation.

What are common AI system failure patterns I should look for during incident analysis?▼

During AI incident analysis, you should look for six common failure patterns: Context Degradation, Specification Drift, Sycophantic Confirmation, Tool Selection Error, Cascade Failure, and Silent Failure. Classifying incidents into these patterns helps identify systemic gaps.

How do I perform a 5 Whys root cause analysis on an incorrect AI output?▼

To perform a 5 Whys root cause analysis on an incorrect AI output, follow a guided workflow that iteratively asks why the failure occurred. This process identifies systemic gaps and missing guardrails, which are then documented in a structured post-mortem report.

Can I save AI failure post-mortem reports directly to a knowledge vault?▼

Yes, you can save AI failure post-mortem reports to a knowledge vault. After the guided workflow generates a publication-ready report using a standardized template, it provides an optional phase for verification and direct vault storage.

What is the best way to document AI incidents for team accountability?▼

The best way to document AI incidents for accountability is generating a standardized post-mortem report. By applying pattern classification and root-cause analysis to the AI failure, teams produce a publishable document that supports learning and accountability.

Do I need any specific tools to start diagnosing AI system failures?▼

No specific external tools are required to start diagnosing AI system failures. The post-mortem builder operates independently through a guided workflow, requiring only the details of the AI incident to classify failure patterns and generate a report.