What is the postmortem-writing skill?

It is a specialized capability for Claude Code that provides templates and technical guidance for documenting software failures, their fixes, and preventive measures.

How does this prevent future bugs?

The skill guides users to create actionable prevention strategies that prioritize automated testing and AI context-loading triggers to catch similar issues during development.

Does this skill help with blameless culture?

Yes, it is designed around the blameless principle, focusing strictly on systemic improvements and technical analysis rather than individual attribution or blame.

Why use a standardized postmortem format?

Consistency ensures that issues are searchable via metadata and tags, making it easier for both humans and AI models to identify and learn from past technical patterns.

Postmortem Writing Assistant

Name: Postmortem Writing Assistant
Author: shfc

byshfc

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Aprendizaje y Documentación

Generates standardized, blameless postmortem documentation for code fixes to prevent future regressions through systemic learning.

Acerca de

The Postmortem Writing skill provides a structured framework for analyzing software failures and documenting fixes using a blameless, learning-oriented approach. It guides developers through extracting technical root causes, identifying specific risk patterns, and establishing automation-first prevention strategies. By utilizing a standardized format with YAML metadata and detailed technical sections, this skill transforms isolated bug fixes into a searchable knowledge base that helps both human developers and AI coding agents avoid repeating historical mistakes.

Características Principales

Blameless root cause analysis (RCA) framework
Standardized postmortem structure with YAML frontmatter
Risk pattern identification for future code reviews
Automation-focused prevention strategy generation
4 GitHub stars
Categorized severity assessment and tagging system

Casos de Uso

Creating high-context training data for AI coding agents to prevent recurring regressions.
Documenting a critical production bug fix to establish a permanent knowledge base.
Standardizing team-wide engineering reports after resolving complex technical debt or logic errors.

Acerca de

Características Principales

Blameless root cause analysis (RCA) framework
Standardized postmortem structure with YAML frontmatter
Risk pattern identification for future code reviews
Automation-focused prevention strategy generation
4 GitHub stars
Categorized severity assessment and tagging system

Casos de Uso

Creating high-context training data for AI coding agents to prevent recurring regressions.
Documenting a critical production bug fix to establish a permanent knowledge base.
Standardizing team-wide engineering reports after resolving complex technical debt or logic errors.