What is the core principle of Root Cause Tracing?

The core principle is to trace backward through the call chain until the original trigger is found, ensuring you fix the bug at its source rather than just patching the symptom where it manifests.

How does this skill handle test suite pollution?

It utilizes specialized bisection scripts for Python and TypeScript that run tests individually to identify exactly which test is modifying the environment or creating side effects.

What type of instrumentation does the skill recommend?

It suggests adding intentional stack trace logging using 'new Error().stack' and console.error() before problematic operations to capture the full execution context, including environment variables and working directories.

When is it best to use this skill?

Use it when an error occurs deep in execution, when a stack trace shows a long call chain, or when it is unclear where invalid data originated in your application flow.

Root Cause Tracing

Name: Root Cause Tracing
Author: carlopezzuto

bycarlopezzuto

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セキュリティとテスト

Traces software bugs systematically through the call stack to identify and resolve original triggers at the source.

The Root Cause Tracing skill empowers developers to move beyond superficial bug fixing by providing a structured methodology for tracing execution errors back through complex call chains. It guides users through identifying immediate causes, analyzing call stacks, and adding strategic instrumentation to expose where invalid data or incorrect state originated. By focusing on fixing the source trigger rather than the symptom, this skill helps implement defense-in-depth validation patterns and includes specialized scripts to identify test pollution in both TypeScript and Python environments.

主な機能

01Systematic backward call stack tracing methodology

02Bisection scripts to identify test environment pollution

03Stack trace analysis for identifying patterns in failed operations

04Defense-in-depth validation pattern implementation

05Deep execution state instrumentation and logging templates

060 GitHub stars

ユースケース

01Debugging 'ghost' files or directories created in incorrect locations during complex test suites

02Identifying the origin of empty strings or null values passed through multiple architectural layers

03Isolating specific tests that cause global state pollution in large CI/CD pipelines

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add carlopezzuto/agents root-cause-tracing

For use in Claude.ai and ChatGPT

Download Skill