How does this skill differ from standard debugging?

While standard debugging often focuses on where an error occurs, this skill enforces a 'trace-back' methodology to find the original logic error that triggered the failure, ensuring a permanent fix at the source.

How does instrumentation work with this skill?

It provides specific patterns for adding non-intrusive logging and stack captures using Error().stack to visualize data flow without disrupting the application logic.

Can this skill help find which test is breaking my CI/CD?

Yes, it includes specialized logic and bisection patterns to identify 'polluter' tests that leave the environment in a bad state for subsequent test suites.

Is this skill suitable for complex monorepo architectures?

Absolutely. It was designed specifically for environments like the FlashFusion monorepo where errors might surface many layers away from the actual bug.

Root Cause Tracing & Debugging

Name: Root Cause Tracing & Debugging
Author: Krosebrook

byKrosebrook

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Security & Testing

Systematically traces execution errors back through the call stack to identify and fix original triggers rather than surface symptoms.

About

This skill empowers Claude to perform deep-dive debugging by following a rigorous backward-tracing methodology. Instead of applying 'band-aid' fixes at the point of failure, it guides the process of instrumenting code, analyzing stack traces, and identifying the exact source of invalid data or incorrect state. It is particularly effective for complex monorepos where errors often manifest deep within execution layers far from their originating calls, providing a structured approach to ensure bugs are eliminated at the source while adding defense-in-depth validation.

Key Features

Multi-layer defense-in-depth validation patterns
Automated code instrumentation for deep-state debugging
Test pollution bisection and isolation scripts
Systematic backward call stack tracing methodology
Detailed stack trace interpretation and analysis
1 GitHub stars

Use Cases

Identifying the source of invalid data in long asynchronous call chains
Finding specific 'polluter' tests that corrupt the shared environment
Debugging complex monorepo execution errors far from the entry point

About

Key Features

Multi-layer defense-in-depth validation patterns
Automated code instrumentation for deep-state debugging
Test pollution bisection and isolation scripts
Systematic backward call stack tracing methodology
Detailed stack trace interpretation and analysis
1 GitHub stars

Use Cases

Identifying the source of invalid data in long asynchronous call chains
Finding specific 'polluter' tests that corrupt the shared environment
Debugging complex monorepo execution errors far from the entry point