vibe-sunsang-mentor

Analyze Codex conversations to identify prompt quality issues and collaboration anti-patterns.

114|19|Updated Apr 24, 2026
One-click install
npx skills add https://github.com/fivetaku/gptaku-plugins-codex --skill vibe-sunsang-mentor-fivetaku
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: vibe-sunsang-mentor
Source: https://github.com/fivetaku/gptaku-plugins-codex/tree/main/plugins/vibe-sunsang-codex/skills/vibe-sunsang-mentor
Command: npx skills add https://github.com/fivetaku/gptaku-plugins-codex --skill vibe-sunsang-mentor-fivetaku

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Coaches AI collaboration quality from recent Codex conversations using workspace type, prompt quality, anti-patterns, and the six growth axes. Use when the user says "멘토링해줘", "코칭해줘", "요청 코칭", "뭘 잘못하고 있는지", or "improve my AI collaboration".

Core Features & Use Cases

  • Analyze Codex conversations to identify prompt quality issues and collaboration anti-patterns.
  • Load mode-specific knowledge to tailor coaching for workspace types and growth axes.
  • Provide concrete, actionable feedback and a small practice for the next session.

Quick Start

Provide your Codex conversations and workspace config, then ask the mentor to begin coaching.

Frequently Asked Questions about vibe-sunsang-mentor

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

FAQPage Schema
How do I get coaching on my AI collaboration patterns from Codex conversations?

AI collaboration coaching analyzes your Codex conversations to identify prompt quality issues and anti-patterns, then generates structured feedback. You need to provide converted conversations and a workspace-type configuration to start.

What are collaboration anti-patterns in Codex sessions and how are they identified?

Collaboration anti-patterns in Codex sessions are inefficient prompt structures or interaction habits. The mentor identifies them by evaluating your conversations against mode-specific knowledge and workspace types to guide targeted coaching.

How do I analyze prompt quality across different workspace types?

Analyzing prompt quality across workspace types requires loading a workspace-type configuration and relevant knowledge references. This tailors the evaluation of your Codex sessions to identify specific growth axes for improvement.

Can I use this coaching approach for any AI session, or does it require Codex specifically?

This coaching approach requires Codex specifically, as it evaluates Codex conversations, workspace types, and prompt quality to generate guidance tailored to the Codex environment across multiple modes.

What do I need to prepare before starting AI collaboration coaching?

Before starting AI collaboration coaching, you need converted Codex conversations, a workspace-type configuration, and relevant knowledge references. These allow the mentor to load mode-specific guidance and generate structured feedback.