debugger

Debug runtime errors and failing tests with a seven-step workflow.

8|3|Updated Jan 21, 2026
One-click install
npx skills add https://github.com/ydnikolaev/antigravity-factory --skill debugger-ydnikolaev
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: debugger
Source: https://github.com/ydnikolaev/antigravity-factory/tree/main/.agent/skills/debugger
Command: npx skills add https://github.com/ydnikolaev/antigravity-factory --skill debugger-ydnikolaev

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

The Debugger skill provides a disciplined, repeatable framework to diagnose and resolve runtime errors, failing tests, and unexpected software behavior.

Core Features & Use Cases

  • 7-step workflow: Reproduce, Minimize, Hypothesize, Instrument, Fix, Prevent, Verify to guide problem solving.
  • Cross-cutting guidance for backend and frontend issues, CI failures, and performance regressions.
  • Real-world example: when a build fails in CI due to a flaky test, apply the workflow to reproduce the failure, isolate the cause, instrument the code, implement a fix, and verify the regression is prevented.

Quick Start

Run the 7-step debugging workflow on a failing test or error log and follow the steps to reproduce, minimize, hypothesize, instrument, fix, prevent, and verify.

Frequently Asked Questions about debugger

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
What is a structured debugging workflow for fixing runtime errors and failing tests?

A structured debugging workflow systematically resolves runtime errors and failing tests through a seven-step process: reproduce, minimize, hypothesize, instrument, fix, prevent, and verify. This enforces reproducibility and rigorous verification to ensure reliable fixes.

How do I debug flaky tests and CI failures?

To debug flaky tests and CI failures, apply a structured workflow that reproduces the failure, isolates the root cause, instruments the code, implements a targeted fix, and verifies the regression is prevented across backend, frontend, and CI environments.

What's the best way to troubleshoot unexpected software behavior?

The best way to troubleshoot unexpected software behavior is applying a disciplined framework that minimizes the problem scope, forms a hypothesis, uses targeted instrumentation, and verifies the correction to ensure safe and reliable fixes.

Does this debugging workflow work for both frontend and backend issues?

Yes, this debugging workflow provides cross-cutting guidance applicable across backend, frontend, and CI environments. It guides reproduction, hypothesis, instrumentation, and verification to resolve runtime errors and performance regressions regardless of stack.

How do I verify a fix and prevent future regressions after troubleshooting?

To verify a fix and prevent future regressions, follow the final workflow steps: apply the correction, implement prevention mechanisms, and rigorously verify the resolution to ensure the original unexpected behavior is safely eliminated.

When should I use targeted instrumentation during root-cause analysis?

Targeted instrumentation should be used during the hypothesis and root-cause analysis steps to isolate variables and confirm the underlying cause of failing tests or runtime errors before applying corrections and verifying the fix.