debugging

Diagnose root causes of failures in tests, builds, tool calls, or runtime behavior.

Updated Apr 16, 2026
One-click install
npx skills add https://github.com/seshxn/ai-swarm --skill debugging-seshxn
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: debugging
Source: https://github.com/seshxn/ai-swarm/tree/main/skills/debugging
Command: npx skills add https://github.com/seshxn/ai-swarm --skill debugging-seshxn

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill helps engineers identify the root causes of failures when tests, builds, tool calls, or runtime behavior diverge from expectations, replacing guesswork with evidence-driven analysis.

Core Features & Use Cases

  • Structured workflow: record expected vs actual behavior, gather evidence, form hypotheses, test them, and verify fixes.
  • Evidence-driven diagnostics: guide verification to ensure the original symptom is addressed and prevent regression.
  • Use Case: when a CI job fails due to a flaky test, reproduce, collect logs, isolate the failure, and confirm the fix.

Quick Start

Run the debugging workflow on a failing test to reproduce the issue, collect evidence, form a hypothesis, and validate the fix.

Frequently Asked Questions about debugging

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

FAQPage Schema
How do I diagnose the root cause of a flaky test in my CI pipeline?

To diagnose flaky test root causes, record expected versus actual behavior, gather evidence like logs, form hypotheses, test them, and verify minimal fixes to prevent regression.

What is the best way to debug failing CI jobs and unexpected runtime deviations?

Debugging failing CI jobs requires an evidence-driven approach: reproduce the issue, collect runtime logs, isolate the failure point, and confirm the fix resolves the original symptom.

How does evidence-driven root-cause analysis work for software failures?

Evidence-driven root-cause analysis works by systematically recording expected vs. actual behavior, gathering supporting evidence, testing hypotheses, and verifying that minimal fixes address the original failure.

Can I use a structured debugging workflow for build failures and tool call errors?

Yes, a structured debugging workflow applies to build failures and tool call errors by guiding you to gather evidence, form hypotheses about the failure, and verify fixes against expected behavior.

Why should I record expected vs. actual behavior when troubleshooting test failures?

Recording expected vs. actual behavior when troubleshooting test failures provides the baseline evidence needed to form accurate hypotheses and verify that your minimal fix resolves the deviation.

How do I verify a minimal fix prevents regression in failing tests?

To verify a minimal fix prevents regression, reproduce the original failing test, confirm the fix resolves the symptom, and check that expected behavior is restored without introducing new deviations.