warden-second-opinion

Spawn fresh subagents to diagnose root causes when Claude loops.

2|Updated Feb 10, 2026
One-click install
npx skills add https://github.com/HawkannG/Claude-Warden --skill warden-second-opinion
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: warden-second-opinion
Source: https://github.com/HawkannG/Claude-Warden/tree/main/skills/warden-second-opinion
Command: npx skills add https://github.com/HawkannG/Claude-Warden --skill warden-second-opinion

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill helps Claude overcome persistent issues or "rabbit holes" by spawning a fresh subagent to provide an unbiased diagnosis, preventing wasted effort on ineffective solutions.

Core Features & Use Cases

  • Automated Triggering: Automatically activates after a set number of edits to the same file, indicating a potential loop.
  • Tiered Diagnosis: Offers a voluntary Tier 1 for structured thinking and a mandatory Tier 2 for deep root cause analysis and human handoff.
  • Use Case: If Claude repeatedly fails to fix a bug in a specific file after several attempts, this Skill will initiate a diagnostic process to identify the true root cause and provide a clear summary for human review.

Quick Start

Invoke the warden second opinion skill to get a fresh perspective on the current problem.

Frequently Asked Questions about warden-second-opinion

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

FAQPage Schema
How do I stop an AI coding assistant from getting stuck in a debugging loop?▼

To stop an AI coding assistant from getting stuck in a debugging loop, you can use a two-tier diagnostic protocol that spawns a fresh subagent for unbiased root cause analysis, breaking the repetitive cycle of ineffective fixes.

Why does Claude keep applying failed fixes to the same file repeatedly?▼

Claude repeats failed fixes due to contextual tunneling, but automated triggering can detect this loop by counting file edits and initiate a fresh subagent to perform structured problem solving and identify the true root cause.

What is the best way to perform root cause analysis when AI fails to resolve a bug?▼

The best way to perform root cause analysis when AI fails to resolve a bug is applying a tiered diagnosis system, where a mandatory second tier forces deep analysis and generates a human-readable summary for human handoff.

Do I need to provide a structured problem brief for AI debugging diagnosis?▼

Yes, you need to provide a structured problem brief and specific subagent prompts to ensure effective analysis and generate accurate human-readable summaries during the diagnostic protocol.

Can I use subagent spawning for workflow management and problem solving?▼

Yes, you can use subagent spawning for workflow management and problem solving to apply structured diagnosis, prevent wasted effort on ineffective solutions, and identify root causes in persistent issues.