What is the TRACE framework used by Error Detective?

TRACE is a five-step debugging approach: Trace (collect error data), Read (parse messages), Analyze (examine context), Check (identify root cause), and Execute (implement and verify the fix).

Which programming languages are supported?

While the TRACE framework is language-agnostic, Error Detective includes specific optimization and patterns for Python, JavaScript, TypeScript, and Java.

How does this skill help with production outages?

It provides a structured assessment workflow to prioritize issues based on severity and uses systematic context analysis to isolate environment-specific variables from code logic.

Can Error Detective automate the fixing of bugs?

It guides the AI to design and implement targeted fixes that address the root cause rather than just the symptoms, followed by a rigorous verification and documentation phase.

Does it integrate with existing logging systems?

Yes, it provides best practices for structured logging and includes a helper script to parse and analyze external log files for pattern recognition.

Error Detective

Name: Error Detective
Author: icartsh

byicartsh

Security & Testing

Implements a systematic TRACE framework to identify, analyze, and resolve complex software errors efficiently.

About

Error Detective is a specialized debugging skill designed to eliminate guesswork by applying the structured TRACE methodology (Trace, Read, Analyze, Check, Execute). It empowers developers to parse complex stack traces across multiple languages, recognize recurring error patterns, and perform deep root cause analysis to distinguish surface symptoms from underlying architectural issues. Whether you are troubleshooting production outages or investigating intermittent logic bugs, this skill provides a rigorous workflow for hypothesis testing, implementation of verified fixes, and the creation of regression tests to ensure long-term stability.

Key Features

Systematic TRACE framework for structured debugging workflows
Integration with automated debug helper scripts for session logging
Hypothesis-driven investigation and verification techniques
Automated error pattern recognition and root cause classification
Multi-language stack trace parsing and semantic interpretation
0 GitHub stars

Use Cases

Analyzing obscure production stack traces to identify hidden root causes
Standardizing debugging procedures across a development team
Troubleshooting intermittent race conditions or environment-specific failures

About

Key Features

Systematic TRACE framework for structured debugging workflows
Integration with automated debug helper scripts for session logging
Hypothesis-driven investigation and verification techniques
Automated error pattern recognition and root cause classification
Multi-language stack trace parsing and semantic interpretation
0 GitHub stars

Use Cases

Analyzing obscure production stack traces to identify hidden root causes
Standardizing debugging procedures across a development team
Troubleshooting intermittent race conditions or environment-specific failures