rlm-debugging

Perform systematic root cause analysis for software bugs and failing tests.

67|2|Updated Feb 7, 2026
One-click install
npx skills add https://github.com/doubleuuser/rlm-workflow --skill rlm-debugging
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: rlm-debugging
Source: https://github.com/doubleuuser/rlm-workflow/tree/main/skills/rlm-debugging
Command: npx skills add https://github.com/doubleuuser/rlm-workflow --skill rlm-debugging

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill prevents guesswork and symptom-based fixes by enforcing a structured Phase 1.5 root cause investigation that captures error analysis, reproduction steps, evidence, and a documented fix strategy before any code changes are attempted.

Core Features & Use Cases

  • Structured Phase 1.5 Template: Provides a ready artifact layout for error analysis, reproduction verification, recent changes review, data-flow tracing, pattern comparison, hypothesis tests, and a final root cause summary.
  • Defensive Workflow & Gates: Defines coverage and approval gates to ensure root causes are confirmed and tests are created before proceeding to implement fixes.
  • Use Case: Investigate failing CI tests, intermittent crashes, incorrect API responses, or performance regressions and produce a locked Phase 1.5 artifact that feeds into the Phase 3 fix plan.

Quick Start

Start Phase 1.5 by creating a 01.5-root-cause.md artifact and follow the prescribed error analysis, reproduction, evidence gathering, hypothesis testing, and summary steps to produce a locked root cause report for Phase 3.

Frequently Asked Questions about rlm-debugging

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

FAQPage Schema
How do I perform root cause analysis for failing CI tests and software bugs?▼

Root cause analysis for failing CI tests requires documenting error messages, reproduction steps, recent changes, data-flow traces, and hypothesis tests before attempting fixes. This process produces a locked Phase 1.5 artifact that feeds directly into your subsequent fix plan.

What is the best way to investigate intermittent crashes and performance regressions before fixing code?▼

Investigating intermittent crashes and performance regressions involves a structured template capturing error analysis, reproduction verification, evidence gathering, and hypothesis testing. This enforces a defensive workflow ensuring root causes are confirmed before any code modifications proceed.

How do I stop guessing and trace data-flow to find the root cause of incorrect API responses?▼

Tracing data-flow to find root causes of incorrect API responses involves pattern comparison and hypothesis testing within a structured artifact. This prevents symptom-based fixes by requiring evidence and reproduction verification before moving to implementation.

Does this debugging workflow require specific dependencies or components to investigate CI failures?▼

This debugging workflow requires no specific dependencies or components to investigate CI failures. It provides a ready artifact layout and defines coverage gates to ensure tests are created and root causes are confirmed before proceeding to implement fixes.

When do I need a Phase 1.5 artifact for bug fixing and what does it contain?▼

A Phase 1.5 artifact for bug fixing is needed before implementing code changes and contains error analysis, reproduction steps, recent changes review, data-flow tracing, hypothesis tests, and a final root cause summary to guide the fix strategy.

Why should I document reproduction steps and recent changes before fixing integration issues?▼

Documenting reproduction steps and recent changes before fixing integration issues prevents guesswork by enforcing a structured root cause investigation. This defensive workflow defines approval gates to ensure causes are confirmed and tests are created prior to code changes.