cm-debugging

Guide engineers through a phase-based debugging workflow to identify root causes.

48|23|Updated Mar 17, 2026
One-click install
npx skills add https://github.com/tody-agent/codymaster --skill cm-debugging
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: cm-debugging
Source: https://github.com/tody-agent/codymaster/tree/main/skills/cm-debugging
Command: npx skills add https://github.com/tody-agent/codymaster --skill cm-debugging

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Systematic debugging framework to identify root causes before applying fixes, reducing wasted effort and regression risk.

Core Features & Use Cases

  • Phase-driven workflow: memory integrity checks, evidence gathering, hypothesis testing, and safe implementation.
  • Guardrails for safe debugging: mandatory root-cause definition and mandatory learning-record after fixes.
  • Broad applicability: for test failures, production bugs, performance issues, and integration faults.

Quick Start

Describe the issue, reproduce it, then follow Phase 1 through Phase 4 before proposing any fix.

Frequently Asked Questions about cm-debugging

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

FAQPage Schema
What is a phase-based debugging workflow for finding root causes?

A phase-based debugging workflow systematically uncovers root causes before proposing fixes by guiding you through error interpretation, memory integrity checks, evidence gathering, hypothesis testing, and safe implementation across four distinct phases.

How do I debug a production bug without wasting effort on wrong fixes?

To debug a production bug efficiently, describe the issue, reproduce it, and follow a disciplined workflow that mandates root-cause definition and evidence gathering before applying any fix, reducing wasted effort and regression risk.

Does this systematic debugging approach work for test failures and integration faults?

Yes, this systematic debugging approach applies broadly to test failures, production bugs, performance issues, and integration faults, providing guardrails like mandatory root-cause definition and learning records after fixes.

How do I reproduce an issue and validate a fix during root-cause debugging?

To reproduce an issue and validate a fix, document findings during evidence gathering, use the cm-tdd skill to create failing tests, then proceed to Phase 4 validation to ensure the root-cause fix is effective.

What's the best way to prevent regressions when fixing complex code bugs?

The best way to prevent regressions is following a disciplined debugging workflow that requires documenting findings, reproducing issues, defining the root cause, creating failing tests, and recording learnings after implementing the fix.

Why should I gather evidence before proposing a code fix?

You should gather evidence before proposing a code fix because systematic root-cause identification reduces wasted effort on incorrect solutions and minimizes regression risk by ensuring the actual cause is addressed.