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sj-gpt

Delegate advisory queries to GPT models via codex MCP with read-only sandboxing.

1|Updated May 12, 2026
Search Tags:#brainstorming#cross-validation#gpt#consultation#second opinion#fact checking#codex mcp
One-click install
npx skills add https://github.com/s0613/S-skills --skill sj-gpt
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: sj-gpt
Source: https://github.com/s0613/S-skills/tree/main/skills/sj-gpt
Command: npx skills add https://github.com/s0613/S-skills --skill sj-gpt

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill eliminates the need to manually switch to ChatGPT when you need alternative perspectives, up-to-date fact verification, or broad brainstorming beyond Claude's knowledge cutoff and native reasoning approach.

Core Features & Use Cases

  • Cross-model consultation: Delegate research, idea brainstorming, and second opinion requests to GPT via codex MCP to get perspectives that complement Claude's analysis.
  • Real-time fact checking: Verify unknown products, recent policy changes, current market prices, or other facts that may have shifted after Claude's knowledge cutoff using GPT's web search capabilities.
  • Use case example: If you are designing a new authentication system and want to compare security approach recommendations from both Claude and GPT to identify potential gaps, use this skill to gather both perspectives for a more robust design.

Quick Start

Use the sj-gpt skill to get a second opinion on the optimal caching strategy for a high-traffic API and compare GPT's recommendation with Claude's initial analysis.

Frequently Asked Questions about sj-gpt

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

FAQPage Schema
How do I get a second opinion from GPT without leaving my current workflow?▼

Cross-validation of ideas works by delegating advisory queries to GPT models via codex MCP. It retrieves alternative perspectives beyond native capabilities, enforces read-only sandboxing, and synthesizes cross-model responses with explicit source attribution.

Can I use GPT web search to fact-check information past Claude's knowledge cutoff?▼

Yes, you can fact-check post-knowledge-cutoff facts using GPT's web search. The skill supports optional web search activation for real-time information retrieval to verify recent policy changes, current market prices, or unknown products.

What is the best way to brainstorm product design ideas using multiple AI models?▼

The best way to brainstorm product design ideas across models is delegating broad challenges to GPT via codex MCP. The skill enforces read-only sandboxing for delegated tasks and synthesizes cross-model responses to identify potential design gaps.

Does cross-model consultation with codex MCP support read-only sandboxing?▼

Yes, cross-model consultation with codex MCP enforces read-only sandboxing for all delegated tasks. This ensures GPT securely retrieves advisory insights and alternative perspectives without modifying your native environment or data.

When do I need cross-validated insights from a GPT model for technical decisions?▼

You need cross-validated insights from GPT when comparing technical decisions like authentication system security approaches. Delegating to GPT via codex MCP identifies potential gaps by contrasting its recommendations against your initial analysis.

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