When should I use this skill instead of standard Claude debugging?

Use this skill for complex, mysterious, or deep-seated bugs where a single model's analysis might miss subtle interactions, race conditions, or specific edge cases.

What kind of output does the Council Debugger provide?

You receive a structured report detailing potential causes from each model, a deep root cause analysis, suggested code fixes, and a final synthesis that reconciles different viewpoints.

Does this skill require specific API access?

Yes, this skill is designed to work with environments where both Codex and Gemini commands are accessible via the CLI to perform the parallel analysis.

How does the AI Council Debugger work?

It triggers on specific commands to gather context from your code and logs, then runs parallel analysis using both Codex and Gemini models to provide a comprehensive, multi-perspective bug report.

AI Council Debugger

Name: AI Council Debugger
Author: kanlanc

bykanlanc

安全与测试

Diagnoses complex software bugs and identifies root causes by orchestrating parallel analysis from multiple high-reasoning AI models.

关于

AI Council Debugger is a high-reasoning skill designed for systematic root cause analysis of complex software issues. By leveraging both Codex (GPT-5.2) and Gemini models in parallel, it gathers error logs, stack traces, and relevant code to provide a multi-perspective diagnosis. The skill concludes with a synthesized 'Council Report' that identifies agreed-upon root causes, highlights conflicting theories, and recommends a verified fix strategy, making it ideal for resolving race conditions, performance bottlenecks, and mysterious system failures that require deep technical investigation.

主要功能

Systematic root cause analysis (RCA) for complex code issues
Automated synthesis of insights into a unified Council Report
High-reasoning (xhigh) processing for deep technical analysis
Context gathering from stack traces, logs, and code snippets
Parallel multi-model debugging using Codex and Gemini
0 GitHub stars

使用场景

Resolving performance bottlenecks where multiple subsystems interact
Analyzing deep stack traces from logs to find the primary failure point
Investigating intermittent race conditions or timing-related bugs

关于

主要功能

Systematic root cause analysis (RCA) for complex code issues
Automated synthesis of insights into a unified Council Report
High-reasoning (xhigh) processing for deep technical analysis
Context gathering from stack traces, logs, and code snippets
Parallel multi-model debugging using Codex and Gemini
0 GitHub stars

使用场景

Resolving performance bottlenecks where multiple subsystems interact
Analyzing deep stack traces from logs to find the primary failure point
Investigating intermittent race conditions or timing-related bugs