When should I use Root Cause Tracing?

Use it when errors occur deep in execution, when stack traces are long and complex, or when the origin of invalid data is not immediately obvious.

How does this skill differ from standard debugging?

It enforces a rigorous backward-tracing methodology that prevents 'symptom patching' by requiring identification of the original trigger before applying any code changes.

Can this be used with other Claude Code skills?

Absolutely. It is designed to integrate with the systematic-debugging phase and pairs with defense-in-depth to add validation once the root cause is found.

Does this skill help with automated testing?

Yes, it includes specific techniques for adding instrumentation to tests and capturing debug logs that might otherwise be suppressed by test runners.

Root Cause Tracing

Name: Root Cause Tracing
Author: timequity

bytimequity

Security & Testing

Systematically traces bugs backward through call stacks to identify and fix the original source of invalid data.

About

Root Cause Tracing empowers Claude to move beyond surface-level fixes by following a structured methodology to find the origin of an error. Instead of patching symptoms where they appear, this skill guides the AI to navigate deep call chains, utilize manual instrumentation for visibility, and identify exactly where data corruption or logical failures begin. It is essential for complex debugging scenarios where the manifestation of a bug is far removed from its actual source, ensuring more robust and permanent software fixes.

Key Features

Manual instrumentation and stack trace capture techniques
0 GitHub stars
Systematic backward call stack tracing methodology
Contextual debugging for environment and directory variables
Integration with systematic debugging and defense-in-depth workflows
Source-level fix identification vs. symptom patching

Use Cases

Debugging null or undefined errors that originate multiple layers deep in the logic
Identifying why a build or test environment is inconsistent across different directories
Tracing data flow through complex asynchronous operations and middleware chains

About

Key Features

Manual instrumentation and stack trace capture techniques
0 GitHub stars
Systematic backward call stack tracing methodology
Contextual debugging for environment and directory variables
Integration with systematic debugging and defense-in-depth workflows
Source-level fix identification vs. symptom patching

Use Cases

Debugging null or undefined errors that originate multiple layers deep in the logic
Identifying why a build or test environment is inconsistent across different directories
Tracing data flow through complex asynchronous operations and middleware chains