debug

Orchestrate AI investigators to test hypotheses and identify root causes.

23|4|Updated Sep 5, 2013
One-click install
npx skills add https://github.com/drn/dots --skill debug-drn
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: debug
Source: https://github.com/drn/dots/tree/main/agents/skills/debug
Command: npx skills add https://github.com/drn/dots --skill debug-drn

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill tackles complex bugs by employing multiple AI agents to investigate different hypotheses simultaneously, fostering a debate that rapidly converges on the root cause.

Core Features & Use Cases

  • Multi-Agent Investigation: Spawns multiple investigators, each exploring a distinct debugging theory.
  • Hypothesis Debate: Agents challenge each other's findings, accelerating root cause identification.
  • Root Cause Analysis: Delivers a clear report detailing the problem, the confirmed root cause, and the fix.
  • Use Case: When faced with an intermittent bug that defies standard debugging, this Skill can systematically explore various potential causes, from recent code changes to environment misconfigurations, and present a definitive answer.

Quick Start

Use the debug skill to find the root cause of the 'user login fails intermittently' bug.

Frequently Asked Questions about debug

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

FAQPage Schema
How does multi-agent debugging work for finding complex bug root causes?

Multi-agent debugging works by spawning multiple AI investigators that each explore a distinct hypothesis for your bug. The agents analyze codebase context and recent commit history, then debate their competing theories to rapidly converge on a confirmed root cause and suggest fixes.

How do I debug an intermittent bug that defies standard root cause analysis?

To debug an intermittent bug, provide the observed symptoms and relevant codebase context to an automated investigator. The system formulates multiple hypotheses, from recent code changes to environment misconfigurations, and systematically tests them to deliver a definitive root cause answer.

Do I need agent teams enabled to run automated code investigation?

Yes, you need agent teams enabled in your AI environment to run this automated code investigation. The multi-agent hypothesis testing requires an environment that supports spawning and orchestrating multiple AI investigators to debate competing bug theories.

What is the best way to automate bug fixing when multiple competing theories exist?

The best way to automate bug fixing with competing theories is using a multi-agent approach where separate investigators independently test different hypotheses. By challenging each other's findings through structured debate, the agents quickly eliminate incorrect theories and identify the true root cause.

Can I use hypothesis testing to investigate bugs across recent commit history?

Yes, you can use hypothesis testing to investigate bugs across recent commit history. The debugging process analyzes recent commits alongside codebase context and bug symptoms to formulate theories, allowing agents to trace whether specific code changes introduced the root cause.