Does it help with log correlation?

Yes, it includes specialized techniques for using request IDs and timestamps to reconstruct event timelines from complex application logs.

How does this skill help with production errors?

It provides a structured workflow to gather context, categorize the error type, and test hypotheses to find the true root cause rather than just fixing symptoms.

What kind of fixes does it suggest?

It provides a tiered approach, offering immediate short-term hotfixes to restore service and long-term architectural improvements like data validation and regression testing.

Can it handle different programming languages?

Yes, the skill is designed to identify universal error patterns like null references, timeouts, and memory leaks across various stack trace formats and languages.

Error Analysis

Name: Error Analysis
Author: jayteealao

byjayteealao

Analytics & Monitoring

Systematically analyzes stack traces and application logs to identify root causes and implement reliable bug fixes.

About

The Error Analysis skill provides a structured framework for developers to diagnose complex software failures by automating the interpretation of stack traces, log patterns, and environment context. It guides Claude through a rigorous multi-step workflow—from initial information gathering and error categorization to hypothesis testing and final resolution tracking—ensuring that fixes address the underlying architectural issues rather than just the symptoms. Whether dealing with production outages or intermittent race conditions, this skill helps standardize the debugging process and improve system reliability.

Key Features

Hypothesis-driven Root Cause Analysis (RCA) framework
0 GitHub stars
Automated stack trace parsing and component interpretation
Log correlation and chronological pattern identification
Structured error categorization by origin and severity
Standardized post-mortem and fix verification templates

Use Cases

Investigating intermittent connection timeouts and infrastructure failures
Debugging production runtime errors and null reference exceptions
Generating detailed post-mortem reports after critical system incidents

About

Key Features

Hypothesis-driven Root Cause Analysis (RCA) framework
0 GitHub stars
Automated stack trace parsing and component interpretation
Log correlation and chronological pattern identification
Structured error categorization by origin and severity
Standardized post-mortem and fix verification templates

Use Cases

Investigating intermittent connection timeouts and infrastructure failures
Debugging production runtime errors and null reference exceptions
Generating detailed post-mortem reports after critical system incidents