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debugging

Reproduce, isolate, and root-cause software defects with evidence-based debugging.

Updated Aug 23, 2026
Search Tags:#debugging#root cause analysis#logging#regression testing#git bisect#stack traces
One-click install
npx skills add https://github.com/SalesTeamToolbox/frood --skill debugging-salesteamtoolbox
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: debugging
Source: https://github.com/SalesTeamToolbox/frood/tree/main/skills/builtins/debugging
Command: npx skills add https://github.com/SalesTeamToolbox/frood --skill debugging-salesteamtoolbox

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

It solves the problem of wasting time guessing at bugs by guiding you through a repeatable process to reproduce, isolate, identify the root cause, and verify a correct fix.

Core Features & Use Cases

  • Systematic debugging workflow: Reproduce the issue reliably, isolate the smallest responsible scope, formulate and test root-cause hypotheses, then verify the fix and prevent regressions.
  • Practical diagnostic tools and signals: Use stack traces, logging, git bisect/diff/log, profiling, and static analysis to gather evidence across code and changes.
  • Bug-pattern targeting: Recognize common failure modes such as off-by-one errors, race conditions, null/undefined references, resource leaks, type coercion, stale caches, and swallowed exceptions.

Quick Start

Use the debugging skill to analyze a failing test by asking for a minimal reproduction, a narrowed isolation plan, and an evidence-based root-cause-and-fix writeup.

Frequently Asked Questions about debugging

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

FAQPage Schema
What is the best way to systematically debug a software defect?▼

Systematic debugging requires an evidence-first methodology that reproduces the issue reliably, isolates the smallest failing scope, formulates a root-cause hypothesis, and verifies the fix to prevent regressions.

How do I use git bisect to find the root cause of a regression?▼

Use git bisect alongside logging and diff analysis to narrow down code changes, isolating the specific commit that introduced the regression and establishing a minimal failing scope for your root-cause hypothesis.

How do I isolate a flaky behavior or race condition from observed failures?▼

Isolate flaky behavior by applying an evidence-first workflow that turns observed failures into reproducible evidence, utilizing stack traces and profiling to target common failure modes like race conditions.

How do I fix a runtime error using stack traces and logging?▼

Fix runtime errors by extracting reproducible evidence from stack traces and logging, then isolating the smallest responsible scope to formulate and test a root-cause hypothesis for an evidence-based fix.

Can this debugging workflow handle performance issues and test failures?▼

Yes, the evidence-first workflow handles regressions, runtime errors, flaky behavior, performance issues, and test failures by targeting common bug patterns like resource leaks, null references, and swallowed exceptions.

When should I not use guessing for root cause analysis?▼

You should avoid guessing during root cause analysis whenever a software defect occurs, instead relying on static analysis, profiling, and minimal reproduction to identify the underlying cause and verify a correct fix.

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